153 results on '"Modélisation mathématique des maladies infectieuses"'
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2. Changes in the Transmission Dynamic of Chikungunya Virus in Southeastern Senegal
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Scott C. Weaver, Oumar Ndiaye, Abdourahmane Sow, Mawlouth Diallo, Bakary Djilocalisse Sadio, Amadou A. Sall, Ousmane Faye, Anta Tall Dia, Birgit Nikolay, Oumar Faye, Denis Malvy, Jorge Cano, Simon Cauchemez, Arbovirus et Virus de Fièvres Hémorragiques [Dakar, Sénégal], Institut Pasteur de Dakar, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Team MORPH3EUS (INSERM U1219 - UB - ISPED), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Modélisation mathématique des maladies infectieuses, Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris], Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), London School of Hygiene and Tropical Medicine (LSHTM), Unité d'Entomologie Médicale [Dakar] (UEM), The University of Texas Medical Branch (UTMB), The research was supported by the National Institutes of Health (NIH), Grant Number AI1069145., Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), and Limouzin, Cécile
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Male ,Rural Population ,0301 basic medicine ,Veterinary medicine ,lcsh:QR1-502 ,environmental risk ,MESH: Chikungunya Fever ,Forests ,Antibodies, Viral ,medicine.disease_cause ,Logistic regression ,spatial autocorrelation ,Population density ,lcsh:Microbiology ,law.invention ,MESH: Aged, 80 and over ,0302 clinical medicine ,MESH: Rural Population ,Seroepidemiologic Studies ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,law ,MESH: Child ,Chikungunya ,Child ,[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST] ,Aged, 80 and over ,MESH: Aged ,MESH: Immunoglobulin G ,MESH: Middle Aged ,Age Factors ,virus diseases ,Middle Aged ,MESH: Forests ,MESH: Mining ,MESH: Infant ,Senegal ,3. Good health ,Infectious Diseases ,Transmission (mechanics) ,MESH: Young Adult ,Child, Preschool ,Female ,Sylvatic cycle ,Adult ,Adolescent ,MESH: Population Density ,030231 tropical medicine ,Environment ,Biology ,Article ,Mining ,gold mining ,Young Adult ,03 medical and health sciences ,MESH: Senegal ,Virology ,medicine ,Humans ,Seroprevalence ,MESH: Environment ,Aged ,Population Density ,MESH: Adolescent ,MESH: Age Factors ,MESH: Seroepidemiologic Studies ,MESH: Humans ,MESH: Child, Preschool ,Infant ,Outbreak ,MESH: Adult ,Odds ratio ,15. Life on land ,MESH: Male ,030104 developmental biology ,Immunoglobulin G ,Chikungunya Fever ,MESH: Female ,MESH: Antibodies, Viral - Abstract
In Senegal, chikungunya virus (CHIKV) is maintained in a sylvatic cycle and causes sporadic cases or small outbreaks in rural areas. However, little is known about the influence of the environment on its transmission. To address the question, 120 villages were randomly selected in the Kedougou region of southeastern Senegal. In each selected village, 10 persons by randomly selected household were sampled and tested for specific anti-CHIKV IgG antibodies by ELISA. We investigated the association of CHIKV seroprevalence with environmental variables using logistic regression analysis and the spatial correlation of village seroprevalence based on semivariogram analysis. Fifty-four percent (51%&ndash, 57%) of individuals sampled during the survey tested positive for CHIKV-specific IgG. CHIKV seroprevalence was significantly higher in populations living close to forested areas (Normalized Difference Vegetation Index (NDVI), Odds Ratio (OR) = 1.90 (1.42&ndash, 2.57)), and was negatively associated with population density (OR = 0.76 (0.69&ndash, 0.84)). In contrast, in gold mining sites where population density was >, 400 people per km2, seroprevalence peaked significantly among adults (46% (27%&ndash, 67%)) compared to all other individuals (20% (12%&ndash, 31%)). However, traditional gold mining activities significantly modify the transmission dynamic of CHIKV, leading to a potential increase of the risk of human exposition in the region.
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- 2020
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3. Estimated protection against COVID-19 based on predicted neutralisation titres from multiple antibody measurements in a longitudinal cohort, France, April 2020 to November 2021
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Woudenberg, Tom, Pinaud, Laurie, Garcia, Laura, Tondeur, Laura, Pelleau, Stephane, de Thoisy, Alix, Donnadieu, Françoise, Backovic, Marija, Attia, Mikaël, Hozé, Nathanaël, Duru, Cécile, Koffi, Aymar Davy, Castelain, Sandrine, Ungeheuer, Marie-Noelle, Fernandes Pellerin, Sandrine, Planas, Delphine, Bruel, Timothée, Cauchemez, Simon, Schwartz, Olivier, Fontanet, Arnaud, White, Michael, Epidémiologie et Analyse des Maladies Infectieuses - Infectious Disease Epidemiology and Analytics, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Université Paris Cité (UPCité)-Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Virologie Structurale - Structural Virology, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Génétique Moléculaire des Virus à ARN - Molecular Genetics of RNA Viruses (GMV-ARN (UMR_3569 / U-Pasteur_2)), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Hôpital de Crépy-en-Valois, Agents infectieux, résistance et chimiothérapie - UR UPJV 4294 (AGIR ), Université de Picardie Jules Verne (UPJV)-CHU Amiens-Picardie, Investigation Clinique et d’Accès aux Ressources Biologiques (Plate-forme) - Clinical Investigation and Access to BioResources (ICAReB), Institut Pasteur [Paris] (IP), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Virus et Immunité - Virus and immunity (CNRS-UMR3569), This work was supported by the Fondation pour la Recherche Médicale (CorPopImm to MW), and the French Government's Laboratoire d'Excellence 'Integrative Biology of Emerging Infectious Diseases' (Investissement d'Avenir grant n°ANR-10-LABX-62-IBEID), and INCEPTION programs (Investissement d’Avenir grant ANR-16-CONV-0005), and 'URGENCE COVID-19' fundraising campaign of Institut Pasteur (TooLab project awarded to M.B.). The COVID-Oise cohort is funded by 'Alliance Tous Unis contre le virus' Institut Pasteur, AP-HP and Fondation de France., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), and ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016)
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seroprevalence ,SARS-CoV-2 ,humoral immunity ,sero-epidemiology ,viral immunity ,COVID-19 ,antibodies ,protection ,neutralising antibodies ,[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology - Abstract
International audience; BackgroundThe risk of SARS-CoV-2 (re-)infection remains present given waning of vaccine-induced and infection-acquired immunity, and ongoing circulation of new variants.AimTo develop a method that predicts virus neutralisation and disease protection based on variant-specific antibody measurements to SARS-CoV-2 antigens.MethodsTo correlate antibody and neutralisation titres, we collected 304 serum samples from individuals with either vaccine-induced or infection-acquired SARS-CoV-2 immunity. Using the association between antibody and neutralisation titres, we developed a prediction model for SARS-CoV-2-specific neutralisation titres. From predicted neutralising titres, we inferred protection estimates to symptomatic and severe COVID-19 using previously described relationships between neutralisation titres and protection estimates. We estimated population immunity in a French longitudinal cohort of 905 individuals followed from April 2020 to November 2021.ResultsWe demonstrated a strong correlation between anti-SARS-CoV-2 antibodies measured using a low cost high-throughput assay and antibody response capacity to neutralise live virus. Participants with a single vaccination or immunity caused by infection were especially vulnerable to symptomatic or severe COVID-19. While the median reduced risk of COVID-19 from Delta variant infection in participants with three vaccinations was 96% (IQR: 94–98), median reduced risk among participants with infection-acquired immunity was only 42% (IQR: 22–66).ConclusionOur results are consistent with data from vaccine effectiveness studies, indicating the robustness of our approach. Our multiplex serological assay can be readily adapted to study new variants and provides a framework for development of an assay that would include protection estimates.
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- 2023
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4. One assay to test them all: Multiplex assays for expansion of respiratory virus surveillance
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Narjis Boukli, Claude Flamand, Kim Lay Chea, Leangyi Heng, Seangmai Keo, Kimhoung Sour, Sophea In, Panha Chhim, Bunthea Chhor, Lomor Kruy, Jelena D. M. Feenstra, Manoj Gandhi, Obiageli Okafor, Camilla Ulekleiv, Heidi Auerswald, Viseth Srey Horm, Erik A. Karlsson, Institut Pasteur du Cambodge, Réseau International des Instituts Pasteur (RIIP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Thermo Fisher Scientific Inc., and This work was supported by Thermo Fisher Scientific, who loaned the QuantStudio 5™ RT-PCR, 96 well, 0.2 ml instrument (Applied Biosystems) and laptop to IPC for the purpose of the study, provided TaqPath™ COVID-19, FluA/B, RSV Combo Kits, and co-authors included were involved in the study design, analysis and interpretation of TaqPath results and reviewed the report. French Agency for Development funded the ECOMORE II project and a COVID-19 top-up (project no. CZZ 2146 01A), providing payed salary to NB for a senior medical virologist position under a temporary contract with the Institut Pasteur du Cambodge. HA is supported by the German Centre for International Migration and Development (CIM). Influenza, COVID-19, and RSV work at IPC and EK are supported, in part, by the World Health Organization and the Food and Agriculture Association of the United Nations.
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SARS-CoV-2 ,diagnostic test ,respiratory syncytial virus ,[SDV]Life Sciences [q-bio] ,surveillance ,COVID-19 ,General Medicine ,influenza ,multiplex assay - Abstract
Molecular multiplex assays (MPAs) for simultaneous detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza and respiratory syncytial virus (RSV) in a single RT-PCR reaction reduce time and increase efficiency to identify multiple pathogens with overlapping clinical presentation but different treatments or public health implications. Clinical performance of XpertXpress® SARS-CoV-2/Flu/RSV (Cepheid, GX), TaqPath™ COVID−19, FluA/B, RSV Combo kit (Thermo Fisher Scientific, TP), and PowerChek™ SARS-CoV-2/Influenza A&B/RSV Multiplex RT-PCR kit II (KogeneBiotech, PC) was compared to individual Standards of Care (SoC). Thirteen isolates of SARS-CoV-2, human seasonal influenza, and avian influenza served to assess limit of detection (LoD). Then, positive and negative residual nasopharyngeal specimens, collected under public health surveillance and pandemic response served for evaluation. Subsequently, comparison of effectiveness was assessed. The three MPAs confidently detect all lineages of SARS-CoV-2 and influenza viruses. MPA-LoDs vary from 1 to 2 Log10 differences from SoC depending on assay and strain. Clinical evaluation resulted in overall agreement between 97 and 100%, demonstrating a high accuracy to detect all targets. Existing differences in costs, testing burden and implementation constraints influence the choice in primary or community settings. TP, PC and GX, reliably detect SARS-CoV-2, influenza and RSV simultaneously, with reduced time-to-results and simplified workflows. MPAs have the potential to enhance diagnostics, surveillance system, and epidemic response to drive policy on prevention and control of viral respiratory infections.
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- 2023
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5. A cross-sectional study on infectious health risks regarding freshwater sports practice in Brittany, France
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Lucie Adélaïde, Maylis Layan, Jonathan Roux, Martine Ledrans, Fanny Velardo, Delphine Berthod, Hanifa Bouziri, Emma Oliosi, Mathilde Lefort, Alan R. Patlán-Hernández, Alexandre Descamps, Pascal Crépey, Mathilde Pivette, Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité), Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Université Paris-Saclay, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Sorbonne Université - Faculté de Médecine (SU FM), Sorbonne Université (SU), CIC Cochin Pasteur (CIC 1417), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôtel-Dieu-Groupe hospitalier Broca-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Hôpital du Valais [Sion, Switzerland], Santé publique France - French National Public Health Agency [Saint-Maurice, France], Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Centre de Recherches sur l'Action Politique en Europe (ARENES), Université de Rennes (UR)-Institut d'Études Politiques [IEP] - Rennes-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Centre National de la Recherche Scientifique (CNRS), École des Hautes Études en Santé Publique [EHESP] (EHESP), Département Méthodes quantitatives en santé publique (METIS), and Gestionnaire, Hal Sorbonne Université
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Microbiology (medical) ,Adolescent ,Cross-sectional study ,freshwater sports ,Public Health, Environmental and Occupational Health ,Fresh Water ,Conjunctivitis ,Cross-Sectional Studies ,Geography ,Infectious Diseases ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Environmental health ,[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Humans ,leptospirosis ,epidemiology ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,France ,human activities ,Waste Management and Disposal ,water-related infections ,Sports ,Water Science and Technology - Abstract
Freshwater sports expose practitioners to pathogens in the water environment and may result in infection. In French Brittany, these infections are particularly worrying, especially since 2016 with an increase in the incidence of leptospirosis reaching 1 case per 100,000 inhabitants, which represents the highest incidence observed since 1920. We aimed to estimate the prevalence of infectious diseases related to freshwater sports practice and to identify the factors associated with these infections among freshwater sports licensees in Brittany, France. From March 18, 2019, to May 8, 2019, we interviewed freshwater sports licensees (online study) and club presidents and instructors (phone study) in Brittany. Licensee participants were 18 years old or more and practiced at least one freshwater sport in one of the 79 Brittany clubs. We used logistic regression models to study the association between our variables of interest and potential risk factors. In total, 551 licensees (20.3% of the total number of licensees) and 38 clubs (48.1%) were surveyed. Among the licensees, 29 (5.3%) reported being diagnosed with leptospirosis, of which 12 (41.3%) occurred in the last 5 years. The most reported symptoms were skin irritation/itchy skin (24.3%) and 39 individuals (7.1%) reported at least one hospitalization in their lifetime for a disease related to freshwater sports. The occurrence of leptospirosis was negatively associated with boarding from a pontoon (odds ratio (OR)=0.20, 95% confidence interval (95% CI) 0.06–0.56), practicing for less than 4 years (OR=0.17, 95% CI 0.04–0.56) compared to more than 10 years, and the occurrence of leptospirosis was positively associated with taking a soapy shower after practice (OR=4.38, 95% CI 1.90–10.51). Eskimo roll was positively associated with the occurrence of otitis and conjunctivitis (OR=3.22, 95% CI 1.82–6.03), and skin irritation/itchy skin (OR=1.66, 95% CI 0.99–2.84). Otitis, conjunctivitis, and skin irritation/itchy skin are the most commonly reported freshwater sport-related diseases in French Brittany. Despite a good level of knowledge of prevention measures, their implementation by licensees and clubs remains low. Further studies are needed to identify practices associated with infectious risk in freshwater sports.
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- 2022
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6. Impact of non-pharmaceutical interventions, weather, vaccination, and variants on COVID-19 transmission across departments in France
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Juliette Paireau, Marie-Laure Charpignon, Sophie Larrieu, Clémentine Calba, Nathanaël Hozé, Pierre-Yves Boëlle, Rodolphe Thiebaut, Mélanie Prague, Simon Cauchemez, Direction des maladies infectieuses - Infectious Diseases Division [Saint-Maurice], Santé publique France - French National Public Health Agency [Saint-Maurice, France], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), MIT Institute for Data, Systems, and Society [Cambridge, MA] (IDSS), Massachusetts Institute of Technology (MIT), Boston Children's Hospital, Harvard Medical School [Boston] (HMS), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Santé publique France Nouvelle-Aquitaine [Bordeaux], Santé publique France Provence-Alpes-Côte d'azur et Corse - Provence-Alps-French Riviera and Corsica [Marseille], Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), Santé publique France, the INCEPTION project (PIA/ANR16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grants 101003589 (RECOVER) and 874735 (VEO), AXA, Groupama, the French Agency for Research on AIDS and Emerging Infectious Diseases via the EMERGEN project (ANRS0151), and the National Research Agency (ANR) through the ANR-Flash call for COVID-19 (grant ANR-20-COVI-0018)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), ANR-20-COVI-0018,TheraCoV,Dynamique virale au niveau individuel et populationnel : implications pour l'optimisation des stratégies antivirales(2020), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), and European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020)
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variants ,Infectious Diseases ,SARS-CoV-2 ,COVID-19 ,reproduction number ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,vaccination ,non-pharmaceutical interventions ,climate ,multivariable regression model - Abstract
Background Multiple factors shape the temporal dynamics of the COVID-19 pandemic. Quantifying their relative contributions is key to guide future control strategies. Our objective was to disentangle the individual effects of non-pharmaceutical interventions (NPIs), weather, vaccination, and variants of concern (VOC) on local SARS-CoV-2 transmission. Methods We developed a log-linear model for the weekly reproduction number (R) of hospital admissions in 92 French metropolitan departments. We leveraged (i) the homogeneity in data collection and NPI definitions across departments, (ii) the spatial heterogeneity in the timing of NPIs, and (iii) an extensive observation period (14 months) covering different weather conditions, VOC proportions, and vaccine coverage levels. Findings Three lockdowns reduced R by 72.7% (95% CI 71.3–74.1), 70.4% (69.2–71.6) and 60.7% (56.4–64.5), respectively. Curfews implemented at 6/7 pm and 8/9 pm reduced R by 34.3% (27.9–40.2) and 18.9% (12.04–25.3), respectively. School closures reduced R by only 4.9% (2.0–7.8). We estimated that vaccination of the entire population would have reduced R by 71.7% (56.4–81.6), whereas the emergence of VOC (mainly Alpha during the study period) increased transmission by 44.6% (36.1–53.6) compared with the historical variant. Winter weather conditions (lower temperature and absolute humidity) increased R by 42.2% (37.3–47.3) compared to summer weather conditions. Additionally, we explored counterfactual scenarios (absence of VOC or vaccination) to assess their impact on hospital admissions. Interpretation Our study demonstrates the strong effectiveness of NPIs and vaccination and quantifies the role of weather while adjusting for other confounders. It highlights the importance of retrospective evaluation of interventions to inform future decision-making.
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- 2023
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7. Mosquito diversity (Diptera: Culicidae) and medical importance in four Cambodian forests
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Antsa Rakotonirina, Pierre-Olivier Maquart, Claude Flamand, Chea Sokha, Sébastien Boyer, Institut Pasteur du Cambodge, Réseau International des Instituts Pasteur (RIIP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Wildlife Conservation Society [Phnom Penh, Cambodia], Wildlife Conservation Society (WCS), Écologie et Émergence des Pathogènes Transmis par les Arthropodes / Ecology and Emergence of Arthropod-borne Pathogens, and This study was by the Defense Advanced Research Projects Agency (DARPA).
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Infectious Diseases ,Vector mosquitoes ,[SDV]Life Sciences [q-bio] ,Parasitology ,Forest ,Cambodia ,Entomology - Abstract
Background A total of 290 mosquito species are recorded in Cambodia among which 43 are known vectors of pathogens. As Cambodia is heavily affected by deforestation, a potential change in the dynamic of vector-borne diseases (VDBs) could occur through alteration of the diversity and density of sylvatic vector mosquitoes and induce an increase in their interactions with humans. Understanding mosquito diversity is therefore critical, providing valuable data for risk assessments concerning the (re)emergence of local VBDs. Consequently, this study mainly aimed to understand the spatial and temporal distribution of sylvatic mosquito populations of Cambodia by determining which factors impact on their relative abundance and presence. Methods A study was conducted in 12 sites from four forests in Cambodia. All mosquitoes, collected during the dry and rainy seasons, were morphologically identified. The diversity and relative density of mosquito species in each site were calculated along with the influence of meteorological and geographical factors using a quasi-Poisson generalized linear model. Results A total of 9392 mosquitoes were collected belonging to 13 genera and 85 species. The most represented genera were Culex, accounting for 46% of collected mosquitoes, and Aedes (42%). Besides being the most abundant species, Culex pseudovishnui and Aedes albopictus, which are known vectors of numerous arboviruses, were present in all sites during both dry and rainy seasons. The presence of mosquito species reported to be zoo-anthropophilic feeders was also observed in both forested and urban areas. Finally, this study demonstrated that altitude, temperature and precipitation impacted the abundance of mosquitoes but also influenced species community composition. Conclusion The results indicate an important diversity of mosquitoes in the four forests and an influence of meteorological and geographical factors on their community. Additionally, this work highlights in parallel the abundance of species considered to be of medical importance and therefore underlines the high risk of pathogen emergence/re-emergence in the region. Graphical Abstract
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- 2023
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8. Modeling the impact of national and regional lockdowns on the 2020 spring wave of COVID-19 in France
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Roux, Jonathan, Massonnaud, Clément, Colizza, Vittoria, Cauchemez, Simon, Crepey, Pascal, Département Méthodes quantitatives en santé publique (METIS), École des Hautes Études en Santé Publique [EHESP] (EHESP), Centre de Recherches sur l'Action Politique en Europe (ARENES), Université de Rennes (UR)-Institut d'Études Politiques [IEP] - Rennes-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Centre National de la Recherche Scientifique (CNRS), Recherche sur les services et le management en santé (RSMS), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Rouen, Normandie Université (NU), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This work was supported by the French national research agency (ANR), through the SPHINx (Spread of Patho-gens on Healthcare Institutions Networks) project [Grant number SPHINX-17-CE36-0008-01]., and ANR-17-CE36-0008,SPHINx,Diffusion de pathogènes au sein des réseaux de soins : une étude de modélisation(2017)
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COVID - 19 ,[SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health ,Impact ,Multidisciplinary ,Lockdown ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,France ,Covid-19 ,Confinement ,[SHS]Humanities and Social Sciences - Abstract
Several countries have implemented lockdowns to control their COVID-19 epidemic. However, questions like “where” and “when” still require answers. We assessed the impact of national and regional lockdowns considering the French first epidemic wave of COVID-19 as a case study. In a regional lockdown scenario aimed at preventing intensive care units (ICU) saturation, almost all French regions would have had to implement a lockdown within 10 days and 96% of ICU capacities would have been used. For slowly growing epidemics, with a lower reproduction number, the expected delays between regional lockdowns increase. However, the public health costs associated with these delays tend to grow with time. In a quickly growing pandemic wave, defining the timing of lockdowns at a regional rather than national level delays by a few days the implementation of a nationwide lockdown but leads to substantially higher morbidity, mortality, and stress on the healthcare system.
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- 2023
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9. SARS-CoV-2 IgG seroprevalence surveys in blood donors before the vaccination campaign, France 2020-2021
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Pierre Gallian, Nathanaël Hozé, Nadège Brisbarre, Paola Mariela Saba Villarroel, Elif Nurtop, Christine Isnard, Boris Pastorino, Pascale Richard, Pascal Morel, Simon Cauchemez, Xavier de Lamballerie, Dubois Frid, Caroline, Etablissement Français du Sang [La Plaine Saint-Denis] (EFS), Unité des Virus Emergents (UVE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Etablissement Français du Sang Provence-Alpes Côte-d'Azur et Corse (EFS), Interactions hôte-greffon-tumeur, ingénierie cellulaire et génique - UFC (UMR INSERM 1098) (RIGHT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS [Bourgogne-Franche-Comté])-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS BFC)-Université de Franche-Comté (UFC)
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[SDV] Life Sciences [q-bio] ,Multidisciplinary ,Virology ,[SDV]Life Sciences [q-bio] ,Immunology ,Immune response - Abstract
Covidonneur Codes and Data for the paper “SARS-CoV-2 IgG seroprevalence surveys in blood donors before the vaccination campaign, France 2020-2021”. Overview This repository contains scripts to Read and format the serological data. Launch MCMC scripts to fit models of infection and antibody decay and estimate parameters of infection-hospitalisation ratio (IHR) and force of infection in each region. Infer prevalence and plot the output of the MCMC The first script to be launched is Setup_data.R; The model is launch with the script launch_analysis. Data The folder Data contains the seroneutralisation result for 32605 samples acquired from blood donors in 2020-2021 in metropolitan France (Covdon_v3.csv) corresponding to anti-S1 IgG samples and additional anti-NIgG samples (Etude antiN T3T4T6.csv). Data were aggregated in a format that maintains anonymity of the participants: For each individual, we provide the age group (in groups 18-30, 31-40, 41-50, 51-60, 61-70), department, survey period and median date of the survey. Additional necessary data are provided: the population size by age and region, the public daily hospital admissions. Scripts All analyses can be run from the main.R file, which calls scripts to run the analysis (contained in the scripts folder) and functions (contained in the R folder). The purpose of each R file is described below. main.R Launch all the necessary codes Setup_data.R Setup the data for further analysis functions.R Some usefuls functions launch_MCMC.R Launch the MCMC scripts. In the directory StanModels three models are provided. posthoc_analysis.R A script containing some posthoc analysis of the MCMC; It allows plotting the IHR by age and the decay of the assay capacity as a function of the time since seroconversion. IHR_Covidonneur.R Plot the IHR as estimated by the MCMC script. Here, a chain was uploaded (Model3b.rds and Model3f.rds). Seroprevalence_age.R This scripts plots the observed seroprevalence, the reconstructed number of infection, the inferred seroprevalence given by the exponential decay of the antibody response following infection.
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- 2023
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10. Reconstructing Mayotte 2018–19 Rift Valley Fever outbreak in humans by combining serological and surveillance data
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Jonathan Bastard, Guillaume André Durand, Fanny Parenton, Youssouf Hassani, Laure Dommergues, Juliette Paireau, Nathanaël Hozé, Marc Ruello, Gilda Grard, Raphaëlle Métras, Harold Noël, Santé publique France - French National Public Health Agency [Saint-Maurice, France], Institut de Recherche Biomédicale des Armées [Antenne Marseille] (IRBA), Unité des Virus Emergents (UVE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Groupement de Défense Sanitaire Mayotte (GDS 976), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), and This work was funded by internal resources of Santé Publique France.
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[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie - Abstract
Rift Valley Fever (RVF) is a zoonosis that affects large parts of Africa and the Arabian Peninsula. RVF virus (RVFV) is transmitted to humans through contacts with infected animals, animal products, mosquito bites or aerosols. Its pathogenesis in humans ranges from asymptomatic forms to potentially deadly haemorrhagic fevers, and the true burden of human infections during outbreaks is generally unknown.We build a model fitted to both passive surveillance data and serological data collected throughout a RVF epidemic that occurred in Mayotte Island in 2018-2019.We estimate that RVFV infected 10,797 (95% CrI 4,728-16,127) people aged ≥15 years old in Mayotte during the entire outbreak, among which only 1.2% (0.67%-2.2%) were reported to the syndromic surveillance system. RVFV IgG seroprevalence in people ≥15 years old was estimated to increase from 5.5% (3.6%-7.7%) before the outbreak to 12.9% (10.4%-16.3%) thereafter.Our results suggest that a large part of RVFV infected people present subclinical forms of the disease and/or do not reach medical care that could lead to their detection by the surveillance system. This may threaten the implementation of exhaustive RVF surveillance and adequate control programs in affected countries.Rift Valley Fever (RVF) is a disease caused by a virus transmitted from livestock animals to humans by mosquito bites, aerosols or direct contact with infected animals or animal products. In some parts of Africa and the Arabian Peninsula, the virus can lead to large outbreaks in both humans and animals. Despite some infected people developing severe forms of the disease, some experience no or mild symptoms. Therefore, infection is often not detected by surveillance systems based on the reporting of symptoms by patients. Here, we use data collected during a RVF outbreak that occurred in 2018–2019 in Mayotte Island, in the Indian Ocean, to model the course of the outbreak in humans. We estimate that, throughout the epidemic, only 1.2% of infected people were detected by the surveillance system. Our results highlight that most human cases may go unreported during RVF outbreaks, making it difficult to monitor the burden of infections.
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- 2022
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11. Quantitative studies of infectious diseases transmission in populations : from pathogen genetic sequences to individual-level epidemiological data
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Layan, Maylis, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Sorbonne Université, Simon Cauchemez, and Hervé Bourhy
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Household studies ,Rabies ,SARS-CoV-2 ,Modélisation ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Molecular epidemiology ,Modeling ,Infectious diseases ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Maladies infectieuses ,Epidémiologie moléculaire ,Rage ,Études de ménages - Abstract
Among the methods for the quantitative study of infectious diseases transmission in host populations, molecular epidemiology that reconstructs pathogen phylogenies by using pathogen genetic sequences and mathematical modelling of infectious diseases that fits mechanistic models of disease transmission to epidemiological data such as case counts are of particular interest to epidemiologists. These two approaches rely on different data sources whose availability depends on the setting. They also rely on different concepts and models leading to complementary pictures of disease transmission. The main objective of this thesis is to better understand how viral infectious diseases such as rabies and COVID-19 circulate in host populations using respectively geolocated and timestamped viral genetic sequences and detailed epidemiological data at the individual level. The first part of this thesis focuses on rabies, a neglected tropical zoonosis, that is estimated to cause 59,000 human deaths per year mostly among rural and poor populations in Africa and Asia. Its causing agent, rabies virus (RABV), mainly circulates in domestic dog populations. Despite being a vaccine-preventable disease in both humans and dogs, rabies remains poorly studied and its circulation in dogs poorly understood. First, we reviewed from the literature all mathematical models and molecular epidemiology studies on dog rabies circulation to synthesize the contribution of both approaches to the understanding of rabies dynamics in dogs. Then, we described RABV spread in Cambodia, one of the most affected countries worldwide, using RABV genomes isolated from dogs and Bayesian continuous phylogeography methods. We used Cambodia as a model of endemic circulation of RABV and exemplified how phylogeography can help characterize circulation in such context. We found that introductions from foreign countries are not necessary to sustain transmission in Cambodia. However, these results are conditional on the sampling of the RABV genomes. To further understand how sampling affects Bayesian phylogeography methods, we performed a simulation study where we evaluated the performances of three Bayesian discrete phylogeography algorithms under increasing levels of bias, and tested whether alternative sampling strategies, and integration of incidence data improve the performances of the algorithms under biased sampling conditions. The second part of this thesis concentrates on SARS-CoV-2 transmission at one of the smallest population scale, households. This setting is particularly suitable to detailed follow-up of household members after introduction of a case, and thus, enables to evaluate how susceptibility and infectivity vary between individuals. First, we estimated BNT162b2 vaccine effectiveness against infection and against transmission if infected during the Alpha wave in Israel using a mathematical model of SARS-CoV-2 transmission in partially vaccinated households. We further explored how model misspecification in a context of differing contact patterns between adults and children would impact estimates of relative infectivity and susceptibility of children compared to adults. Overall, this thesis explores how molecular epidemiology and modelling contribute to the understanding of infectious diseases transmission at the population level and highlights the need for data integration.; Parmi les méthodes pour l'étude quantitative de la transmission des maladies infectieuses dans les populations, les épidémiologistes ont récemment focalisé leur attention sur l'épidémiologie moléculaire qui vise à reconstruire la phylogénie des pathogènes en utilisant leurs séquences génétiques, et la modélisation mathématique des maladies infectieuses qui ajuste des modèles mécanistes de transmission des maladies à des données épidémiologiques telles que le nombre de cas. Ces deux approches se basent sur des données très différentes dont la disponibilité varie selon le contexte. Les concepts et les modèles qu'elles utilisent permettent d'explorer des facettes différentes de la transmission des maladies. L'objectif principal de cette thèse est de mieux comprendre comment les maladies virales comme la rage et la covid-19 circulent dans les populations hôtes en utilisant pour la première des séquences génétiques virales datées et géolocalisées, et pour la deuxième, des données épidémiologiques à l'échelle individuelle. La première partie de cette thèse s'intéresse à la rage, une zoonose tropicale négligée, responsable d'environ 59,000 morts chaque année principalement dans les populations pauvres et rurales d'Afrique et d'Asie. Son agent étiologique, le virus de la rage (RABV), circule principalement dans les populations canines domestiques dont les modes de transmission restent peu étudiés et mal compris malgré l'existence de vaccins efficaces chez l'homme et l'animal. Nous avons tout d'abord synthétisé dans une revue de la littérature l'apport relatif des modèles mathématiques et de l'épidémiologie moléculaire dans la compréhension des dynamiques de la rage chez le chien. Puis, nous avons décrit la circulation endémique de la rage au Cambodge, un des pays les plus affectés, à partir de génomes de la rage isolés chez le chien et analysés avec des méthodes de phylogéographie Bayésienne continue. Nous avons montré que les introductions depuis d'autres pays ne sont pas nécessaires au maintien de la circulation. Toutefois, ces résultats sont conditionnés par l'échantillonnage des génomes. Pour mieux comprendre leurs impacts sur les méthodes de phylogéographie Bayésienne, nous avons entrepris une étude de simulation dans laquelle nous avons comparé les performances de trois algorithmes de phylogéographie discrète face à un échantillonnage plus ou moins biaisé. Nous avons testé des stratégies d'échantillonnage alternatives et intégré des données épidémiologiques afin d'atténuer l'effet potentiel des biais d'échantillonnage sur la performance des trois algorithmes. La deuxième partie de la thèse se concentre sur la transmission du SARS-CoV-2 dans une des plus petites populations, les ménages. Cette configuration est particulièrement adaptée au suivi détaillé de l'ensemble des membres du foyer après l'introduction d'un cas et permet ainsi d'évaluer comment la susceptibilité et l'infectivité varient au niveau individuel. Dans un premier temps, nous avons estimé l'effectivité vaccinale contre l'infection et la transmission si infecté pendant la vague de variant Alpha en Israël grâce à un modèle de transmission dans des ménages partiellement vaccinés. Nous avons ensuite exploré comment l'hétérogénéité de contact dans les ménages, notamment entre les adultes et les enfants, impacte les estimations de l'infectivité et de la susceptibilité relatives des enfants par rapport aux adultes. En conclusion, cette thèse explore les contributions de l'épidémiologie moléculaire et de la modélisation pour la compréhension de la transmission des maladies infectieuses à différentes échelles de population et souligne la nécessité d'intégrer les données génétiques et épidémiologiques.
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- 2022
12. Modelling the end of a Zero-COVID strategy using nirmatrelvir/ritonavir, vaccination and NPIs in Wallis and Futuna
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Antoine Brault, Cécile Tran-Kiem, Clément Couteaux, Valérie Olié, Juliette Paireau, Yazdan Yazdanpanah, Jade Ghosn, Guillaume Martin-Blondel, Paolo Bosetti, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), Agence de Santé des îles Wallis & Futuna, Santé publique France - French National Public Health Agency [Saint-Maurice, France], Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Institut Toulousain des Maladies Infectieuses et Inflammatoires (Infinity), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), Duchange, Nathalie, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), CHU Toulouse [Toulouse], and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
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NPIs ,SARS-CoV-2 ,Nirmatrelvir/ritonavir ,Health Policy ,Public Health, Environmental and Occupational Health ,Paxlovid ,Obstetrics and Gynecology ,COVID-19 ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,Zero-COVID ,Treatment ,Psychiatry and Mental health ,Infectious Diseases ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,Pediatrics, Perinatology and Child Health ,Internal Medicine ,[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation ,Geriatrics and Gerontology ,Antiviral ,Vaccine - Abstract
International audience; Ending Zero-COVID is challenging, particularly when vaccine coverage is low. Considering Wallis and Futuna, a French Zero-COVID territory affected by reluctance to vaccination, low immunity and high levels of comorbidities, we investigate how targeted use of nirmatrelvir/ritonavir (brand name Paxlovid) can complement vaccination and non-pharmaceutical interventions (NPIs) and mitigate the epidemic rebound expected when Zero-COVID ends.We developed a discrete age-stratified compartmental model describing SARS-CoV-2 spread and healthcare impact once Wallis and Futuna reopens. It accounts for comorbidity risk groups (CRG), vaccine coverage (2 doses, 3 doses), the effectiveness of vaccines (recent or old injection), treatments and NPIs. In our baseline scenario, cases aged 65+ in intermediate/high CRG and 40+ in high CRG are eligible for treatment.FindingsThe epidemic is expected to start 13-20 days after reopening with a doubling time of 1·6-3·7 days. For medium transmission intensity (R0=5), 134 (115-156) hospital admissions are expected within 3 months, with no pharmaceutical measures. In our baseline scenario, admissions are reduced by 11%-21% if 50% of the target group receive treatment, with maximum impact when combined with NPIs and vaccination. The number of hospitalisations averted (HA) per patient treated (PT) is maximum when 65+ in high CRG are targeted (0·124 HA/PT), quickly followed by 65+ in intermediate/high CRG (0·097 HA/PT), and any 65+ (0·093 HA/PT). Expanding the target group increases both PT and HA, but marginal gains diminish.Modelling suggests that test and treat may contribute to the mitigation of epidemic rebounds at the end of Zero-COVID, particularly in populations with low immunity and high levels of comorbidities.
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- 2022
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13. The transfer of maternal antibodies and dynamics of maternal and natural infection-induced antibodies against coxsackievirus A16 in Chinese children 0–13 years of age: a longitudinal cohort study
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Zhou, Jiaxin, Zhou, Yonghong, Luo, Kaiwei, Liao, Qiaohong, Zheng, Wen, Gong, Hui, Shi, Huilin, Zhao, Shanlu, Wang, Kai, Qiu, Qi, Dai, Bingbing, Ren, Lingshuang, Wang, Lili, Gao, Lidong, Xu, Meng, Liu, Nuolan, Lu, Wanying, Zheng, Nan, Chen, Xinhua, Chen, Zhiyuan, Yang, Juan, Cauchemez, Simon, Yu, Hongjie, Fudan University [Shanghai], Hunan provincial center for disease control and prevention, Anhua County Center for Disease Control and Prevention [Yiyang, China], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This work was supported by the Key Program of the National Natural Science Foundation of China (82130093), Li Ka Shing Oxford Global Health Programme (No. LG33), AXA Research Fund, the Investissement d’Avenir program, Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), Models of Infectious Disease Agent Study of the National Institute of General Medical Sciences, INCEPTION project (PIA/ANR-16-CONV-0005), Chinese Preventive Medicine Association (No. 20101801), Hunan Provincial Natural Science Foundation (2019JJ80115), and the Scientific Research Project of Hunan Provincial Health Commission (B2019039)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), and ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016)
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China ,Infant, Newborn ,Infant ,General Medicine ,Antibodies, Neutralizing ,Enterovirus A, Human ,Cohort Studies ,Seroepidemiologic Studies ,Child, Preschool ,Animals ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Longitudinal Studies ,Child ,Hand, Foot and Mouth Disease ,Enterovirus - Abstract
Background A major hand-foot-and-mouth disease (HFMD) pathogen, coxsackievirus A16 (CVA16), has predominated in several of the last 10 years and caused the largest number of HFMD outbreaks between 2011 and 2018 in China. We evaluated the efficacy of maternal anti-CVA16 antibody transfer via the placenta and explored the dynamics of maternal and natural infection-induced neutralizing antibodies in children. Methods Two population-based longitudinal cohorts in southern China were studied during 2013–2018. Participants were enrolled in autumn 2013, including 2475 children aged 1–9 years old and 1066 mother-neonate pairs, and followed for 3 years. Blood/cord samples were collected for CVA16-neutralizing antibody detection. The maternal antibody transfer efficacy, age-specific seroprevalence, geometric mean titre (GMT) and immune response kinetics were estimated. Results The average maternal antibody transfer ratio was 0.88 (95% CI 0.80–0.96). Transferred maternal antibody levels declined rapidly (half-life: 2.0 months, 95% CI 1.9–2.2 months). The GMT decayed below the positive threshold (8) by 1.5 months of age. Due to natural infections, it increased above 8 after 1.4 years and reached 32 by 5 years of age, thereafter dropping slightly. Although the average duration of maternal antibody-mediated protection was < 3 months, the duration extended to 6 months on average for mothers with titres ≥ 64. Conclusions Anti-CVA16 maternal antibodies are efficiently transferred to neonates, but their levels decline quickly. Children aged 0–5 years are the main susceptible population and should be protected by CVA16 vaccination, with the optimal vaccination time between 1.5 months and 1 year of age.
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- 2022
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14. Reconstructing long-term dengue virus immunity in French Polynesia
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Takahiro Nemoto, Maite Aubry, Yoann Teissier, Richard Paul, Van-Mai Cao-Lormeau, Henrik Salje, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Kyoto University, Institut Louis Malardé [Papeete] (ILM), Institut de Recherche pour le Développement (IRD), Direction de la Santé [Papeete], Génétique fonctionnelle des maladies infectieuses - Functional Genetics of Infectious Diseases, Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics [Kyoto, Japan], Institut Pasteur [Paris] (IP), University of Cambridge [UK] (CAM), This work was supported by the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID https://anr.fr/ProjetIA-10-LABX-0062 to SC and HS), the European Research Council (No. 804744 https://cordis.europa.eu/project/id/804744 to SC and HS), and the European Commission Seventh Framework Program [FP7/2007-2013] (DENFREE project No.282378 https://cordis.europa.eu/project/id/282378 to RP and VMCL)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), European Project: 804744,H2020-EU.1.1.,ARBODYNAMIC(2019), European Project: 282378,EC:FP7:HEALTH,FP7-HEALTH-2011-single-stage,DENFREE(2012), Nemoto, Takahiro [0000-0003-2981-4035], and Apollo - University of Cambridge Repository
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Islands ,Medicine and health sciences ,Biology and life sciences ,[SDV]Life Sciences [q-bio] ,Public Health, Environmental and Occupational Health ,Immunity ,French Polynesia ,Dengue Virus ,Dengue fever ,Serogroup ,Antibodies ,Polynesia ,Dengue ,Medical risk factors ,Earth sciences ,Infectious Diseases ,Serology ,Seroepidemiologic Studies ,Humans ,People and places ,Child ,Research Article - Abstract
Funder: FP7 Ideas: European Research Council; funder-id: http://dx.doi.org/10.13039/100011199; Grant(s): 282378, BACKGROUND: Understanding the underlying risk of infection by dengue virus from surveillance systems is complicated due to the complex nature of the disease. In particular, the probability of becoming severely sick is driven by serotype-specific infection histories as well as age; however, this has rarely been quantified. Island communities that have periodic outbreaks dominated by single serotypes provide an opportunity to disentangle the competing role of serotype, age and changes in surveillance systems in characterising disease risk. METHODOLOGY: We develop mathematical models to analyse 35 years of dengue surveillance (1979-2014) and seroprevalence studies from French Polynesia. We estimate the annual force of infection, serotype-specific reporting probabilities and changes in surveillance capabilities using the annual age and serotype-specific distribution of dengue. PRINCIPAL FINDINGS: Eight dengue epidemics occurred between 1979 and 2014, with reporting probabilities for DENV-1 primary infections increasing from 3% to 5%. The reporting probability for DENV-1 secondary infections was 3.6 times that for primary infections. We also observed heterogeneity in reporting probabilities by serotype, with DENV-3 having the highest probability of being detected. Reporting probabilities declined with age after 14 y.o. Between 1979 and 2014, the proportion never infected declined from 70% to 23% while the proportion infected at least twice increased from 4.5% to 45%. By 2014, almost half of the population had acquired heterotypic immunity. The probability of an epidemic increased sharply with the estimated fraction of susceptibles among children. CONCLUSION/SIGNIFICANCE: By analysing 35 years of dengue data in French Polynesia, we characterised key factors affecting the dissemination profile and reporting of dengue cases in an epidemiological context simplified by mono-serotypic circulation. Our analysis provides key estimates that can inform the study of dengue in more complex settings where the co-circulation of multiple serotypes can greatly complicate inference.
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- 2022
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15. Impact of non-pharmaceutical interventions, weather, vaccination, and variants on COVID-19 transmission across departments in France: a modelling study
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Paireau, Juliette, Charpignon, Marie-Laure, Larrieu, Sophie, Calba, Clémentine, Hozé, Nathanaël, Boëlle, Pierre-Yves, Thiébaut, Rodolphe, Prague, Mélanie, Cauchemez, Simon, Direction des maladies infectieuses - Infectious Diseases Division [Saint-Maurice], Santé publique France - French National Public Health Agency [Saint-Maurice, France], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), MIT Institute for Data, Systems, and Society [Cambridge, MA] (IDSS), Massachusetts Institute of Technology (MIT), Boston Children's Hospital, Harvard Medical School [Boston] (HMS), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Santé publique France Nouvelle-Aquitaine [Bordeaux], Santé publique France Provence-Alpes-Côte d'azur et Corse - Provence-Alps-French Riviera and Corsica [Marseille], Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), Santé publique France, the INCEPTION project (PIA/ANR16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grants 101003589 (RECOVER) and 874735 (VEO), AXA, Groupama, the French Agency for Research on AIDS and Emerging Infectious Diseases via the EMERGEN project (ANRS0151), and the National Research Agency (ANR) through the ANR-Flash call for COVID-19 (grant ANR-20-COVI-0018)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), ANR-20-COVI-0018,TheraCoV,Dynamique virale au niveau individuel et populationnel : implications pour l'optimisation des stratégies antivirales(2020), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020), PAIREAU, Juliette, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Dynamique virale au niveau individuel et populationnel : implications pour l'optimisation des stratégies antivirales - - TheraCoV2020 - ANR-20-COVI-0018 - COVID-19 - VALID, Rapid European COVID-19 Emergency Response research - RECOVER - - H2020-SC1-PHE-CORONAVIRUS-20202020-02-14 - 2022-02-13 - 101003589 - VALID, and Versatile Emerging infectious disease Observatory - VEO - - H2020-SC1-2019-Single-Stage-RTD2020-01-01 - 2024-12-31 - 874735 - VALID
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variants ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,SARS-CoV-2 ,COVID-19 ,reproduction number ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,vaccination ,non-pharmaceutical interventions ,climate ,multivariable regression model - Abstract
Background: Multiple factors shape the temporal dynamics of the COVID-19 pandemic. Quantifying their relative contributions is key to guide future control strategies. Our objective was to disentangle the individual effects of non-pharmaceutical interventions (NPIs), weather, vaccination, and variants of concern (VOC) on local SARS-CoV-2 transmission.Methods: We developed a log-linear model for the weekly reproduction number (R) of hospital admissions in 92 French metropolitan departments. We leveraged (i) the homogeneity in data collection and NPI definitions across departments, (ii) the spatial heterogeneity in the timing of NPIs, and (iii) an extensive observation period (14 months) covering different meteorological conditions, VOC proportions, and vaccine coverage levels.Results: Three lockdowns reduced R by 72.9% (95%CI: 71.4-74.2), 70.4% (69.2-71.6) and 60.4% (56.1-64.3), respectively. Curfews implemented at 6/7pm and 8/9pm reduced R by 34.5% (28.1-40.4) and 18.4% (11.4-24.8), respectively. School closures reduced R by only 4.6% (1.6-7.4). We estimated that vaccination of the entire population would have reduced R by 74.0% (59.4-83.3), whereas the emergence of VOC (mainly Alpha during the study period) increased transmission by 46.9% (38.2-56.0) compared with the historical variant. Winter weather conditions (lower temperature and absolute humidity) increased R by 41.7% (37.0-46.7) compared to summer weather conditions. Additionally, we explored counterfactual scenarios (absence of VOC or vaccination) to assess their impact on hospital admissions.Conclusions: Our study demonstrates the strong effectiveness of NPIs and vaccination and quantifies the role of meteorological factors while adjusting for other confounders. It highlights the importance of retrospective evaluation of interventions to inform future decision-making.
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- 2022
16. Impact of test and treat with nirmatrelvir/ritonavir to mitigate the epidemic rebound when Zero-COVID ends in Wallis and Futuna
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Brault, Antoine, Tran-Kiem, Cécile, Couteaux, Clément, Olié, Valérie, Paireau, Juliette, Yazdanpanah, Yazdan, Ghosn, Jade, Martin-Blondel, Guillaume, Bosetti, Paolo, Cauchemez, Simon, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), Agence de Santé des îles Wallis & Futuna, Santé publique France - French National Public Health Agency [Saint-Maurice, France], Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Institut Toulousain des Maladies Infectieuses et Inflammatoires (Infinity), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010)
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[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation - Abstract
Ending Zero-COVID is challenging, particularly when vaccine coverage is low. Considering Wallis and Futuna, a French Zero-COVID territory affected by reluctance to vaccination, low immunity and high levels of comorbidities, we investigate how targeted use of nirmatrelvir/ritonavir (brand name Paxlovid) can complement vaccination and non-pharmaceutical interventions (NPIs) and mitigate the epidemic rebound expected when Zero-COVID ends.
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- 2022
17. Indirect Protection from Vaccinating Children against Influenza A Virus Infection in Households
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Tim K. Tsang, Can Wang, Vicky J. Fang, Ranawaka A. P. M. Perera, Hau Chi So, Dennis K. M. Ip, J. S. Malik Peiris, Gabriel M. Leung, Simon Cauchemez, Benjamin J. Cowling, The University of Hong Kong (HKU), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), and This study was supported by the Research Fund for the Control of Infectious Diseases of the Health, Welfare and Food Bureau of the Hong Kong SAR Government (grant CHP-CE-03), the Theme-based Research Scheme project no. T11-712/19N from the Hong Kong Government, the Health and Medical Research Fund, Food and Health Bureau, Government of the Hong Kong Special Administrative Region (grant no. 05190097), and the Laboratory of Excellence Integrative Biology of Emerging Infectious Diseases (research funding to SC), AXA Research Fund to SC.
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influenza ,vaccination ,indirect protection ,Influenza A Virus, H1N1 Subtype ,Infectious Diseases ,Influenza Vaccines ,Influenza A Virus, H3N2 Subtype ,Virology ,Influenza, Human ,Vaccination ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Child - Abstract
International audience; Influenza vaccination is an important intervention to prevent influenza virus infection. Our previous analysis suggested that indirect protection is limited in an influenza B epidemic in Hong Kong. We further analyzed six influenza A epidemics to determine such potential. We applied a statistical model to estimate household transmission dynamics in the 3 influenza A(H3N2) and 3 pandemic influenza A(H1N1) epidemics. Then, we estimated the reduction in infection risk among unvaccinated household members when all children in households are vaccinated, with different assumptions on vaccine efficacy (VE). In the optimal scenario that VE was 70%, the reduction to the total probability of infection was only marginal, with relative probabilities ranged from 0.91–0.94 when all children in households were vaccinated because community was by far the main source of infection during the six epidemics in our study. The proportion of cases attributed to household transmission was 10% (95% CrI: 7%, 13%). Individual influenza vaccination is important even when other household members are vaccinated, given the degree of indirect protection is small.
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- 2022
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18. Evaluating the impact of curfews and other measures on SARS-CoV-2 transmission in French Guiana
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Andronico, Alessio, Tran Kiem, Cécile, Paireau, Juliette, Succo, Tiphanie, Bosetti, Paolo, Lefrancq, Noémie, Nacher, Mathieu, Djossou, Félix, Sanna, Alice, Flamand, Claude, Salje, Henrik, Rousseau, Cyril, Cauchemez, Simon, Gestionnaire, Hal Sorbonne Université, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), Santé publique France - French National Public Health Agency [Saint-Maurice, France], Santé publique France Guyane, Centre d'investigation clinique Antilles-Guyane (CIC - Antilles Guyane), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -CHU de la Martinique [Fort de France]-Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Université de Guyane (UG), Unité d'Epidémiologie [Cayenne, Guyane française], Institut Pasteur de la Guyane, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), University of Cambridge [UK] (CAM), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), Sante Publique France, the INCEPTION project (PIA/ANR-16-CONV-0005) and European Union V.E.O and RECOVER projects., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Collège doctoral [Sorbonne universités], Andronico, Alessio [0000-0002-3542-7245], Tran Kiem, Cécile [0000-0003-0563-8428], Paireau, Juliette [0000-0002-5143-6256], Lefrancq, Noémie [0000-0001-5991-6169], Flamand, Claude [0000-0002-8064-445X], Salje, Henrik [0000-0003-3626-4254], Cauchemez, Simon [0000-0001-9186-4549], and Apollo - University of Cambridge Repository
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Adult ,Male ,141 ,Adolescent ,Statistical methods ,Epidemiology ,[SDV]Life Sciences [q-bio] ,Science ,Basic Reproduction Number ,Young Adult ,631/114/2397 ,Humans ,Computational models ,129 ,Child ,Pandemics ,631/326/596/4130 ,Aged ,Aged, 80 and over ,Models, Statistical ,SARS-CoV-2 ,Infant, Newborn ,article ,COVID-19 ,Infant ,Middle Aged ,631/114/2415 ,692/700/478/174 ,French Guiana ,Hospitalization ,[SDV] Life Sciences [q-bio] ,Child, Preschool ,Quarantine ,Female - Abstract
While general lockdowns have proven effective to control SARS-CoV-2 epidemics, they come with enormous costs for society. It is therefore essential to identify control strategies with lower social and economic impact. Here, we report and evaluate the control strategy implemented during a large SARS-CoV-2 epidemic in June–July 2020 in French Guiana that relied on curfews, targeted lockdowns, and other measures. We find that the combination of these interventions coincided with a reduction in the basic reproduction number of SARS-CoV-2 from 1.7 to 1.1, which was sufficient to avoid hospital saturation. We estimate that thanks to the young demographics, the risk of hospitalisation following infection was 0.3 times that of metropolitan France and that about 20% of the population was infected by July. Our model projections are consistent with a recent seroprevalence study. The study showcases how mathematical modelling can be used to support healthcare planning in a context of high uncertainty., Identifying effective combinations of control measures in different populations is important for SARS-CoV-2 control. Here, the authors show that in French Guiana, which has a relatively young population, curfews and localised lockdowns appeared to contribute to reducing transmission.
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- 2021
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19. Association between the COVID-19 pandemic and pertussis derived from multiple nationwide data sources, France, 2013 to 2020
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Soraya Matczak, Corinne Levy, Camille Fortas, Jérémie F Cohen, Stéphane Béchet, Fatima Aït El Belghiti, Sophie Guillot, Sabine Trombert-Paolantoni, Véronique Jacomo, Yann Savitch, Juliette Paireau, Sylvain Brisse, Nicole Guiso, Daniel Lévy-Bruhl, Robert Cohen, Julie Toubiana, Biodiversité et Epidémiologie des Bactéries pathogènes - Biodiversity and Epidemiology of Bacterial Pathogens, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Association Clinique et Thérapeutique Infantile du Val de Marne (ACTIV), Groupe de Pathologie Infectieuse Pédiatrique [Paris] (GPIP), Société Française de Pédiatrie (SFP), Centre de Recherche Clinique [Créteil] (CRC), Centre Hospitalier Intercommunal de Créteil (CHIC), Association Française de Pédiatrie Ambulatoire (AFPA), Santé publique France - French National Public Health Agency [Saint-Maurice, France], Equipe 1 : EPOPé - Épidémiologie Obstétricale, Périnatale et Pédiatrique (CRESS - U1153), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre national de Référence de la Coqueluche et autres Bordetelloses - National Reference Center for Whooping Cough and other Bordetella infections (CNR), Institut Pasteur [Paris] (IP), Laboratoire CERBA [Saint Ouen l'Aumône], Eurofins Biomnis, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)
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Epidemiology ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Whooping Cough ,Virology ,Communicable Disease Control ,Public Health, Environmental and Occupational Health ,COVID-19 ,Humans ,Information Storage and Retrieval ,France ,Child ,Pandemics - Abstract
Background Interventions to mitigate the COVID-19 pandemic may impact other respiratory diseases. Aims We aimed to study the course of pertussis in France over an 8-year period including the beginning of the COVID-19 pandemic and its association with COVID-19 mitigation strategies, using multiple nationwide data sources and regression models. Methods We analysed the number of French pertussis cases between 2013 and 2020, using PCR test results from nationwide outpatient laboratories (Source 1) and a network of the paediatric wards from 41 hospitals (Source 2). We also used reports of a national primary care paediatric network (Source 3). We conducted a quasi-experimental interrupted time series analysis, relying on negative binomial regression models. The models accounted for seasonality, long-term cycles and secular trend, and included a binary variable for the first national lockdown (start 16 March 2020). Results We identified 19,039 pertussis cases from these data sources. Pertussis cases decreased significantly following the implementation of mitigation measures, with adjusted incidence rate ratios of 0.10 (95% CI: 0.04–0.26) and 0.22 (95% CI: 0.07–0.66) for Source 1 and Source 2, respectively. The association was confirmed in Source 3 with a median of, respectively, one (IQR: 0–2) and 0 cases (IQR: 0–0) per month before and after lockdown (p = 0.0048). Conclusions The strong reduction in outpatient and hospitalised pertussis cases suggests an impact of COVID-19 mitigation measures on pertussis epidemiology. Pertussis vaccination recommendations should be followed carefully, and disease monitoring should be continued to detect any resurgence after relaxation of mitigation measures.
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- 2022
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20. Modelling the spread and control of SARS-CoV-2 in France
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Tran Kiem, Cécile, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Sorbonne Université, Simon Cauchemez, and STAR, ABES
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[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,SARS-CoV-2 ,Dynamique de transmission ,COVID-19 pandemic ,Mesures de contrôle ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Modélisation mathématique et statistique ,Mathematical and statistical modelling ,Pandémie de COVID-19 - Abstract
The COVID-19 pandemic has had a tremendous impact on societies worldwide. As epidemics are only partially observed processes characterized by non-linear dynamics, their study requires the development of appropriate statistical and mathematical models to capture their complexity. The aim of this thesis is to develop modelling analyses to characterize the spread of SARS-CoV-2 in France as well as the impact of different interventions.In a first part, we estimated the burden of SARS-CoV-2 in France at the end of the first lockdown in spring 2020. This study enabled us to produce the first estimates of the fraction of the population infected by SARS-CoV-2. In a second part, we present a modelling study that enabled us to characterize the patterns of SARS-CoV-2 transmission between age groups in a pre-vaccination era. From this, we derived the impact of control measures targeting specific age groups, including strategies shielding the elderly population. In a third part, we report a series of modelling analyses that helped quantifying the impact of different control measures on the dynamics of the COVID-19 epidemic. These included the comparison of different vaccine prioritization strategies, the evaluation of risks and benefits associated with different vaccine distribution strategies or the use of lockdown as a last resort option in case of a COVID-19 epidemic rebound.The analyses reported in this thesis illustrate how modelling may be used to study the spread of pathogens in populations and eventually inform control strategies. The results detailed in this manuscript were shared along the course of the pandemic with French governmental and public health agencies., La pandémie de COVID-19 a eu un impact majeur sur l’organisation des sociétés. Comme les épidémies ne sont généralement que partiellement observées et caractérisées par des dynamiques non linéaires, leur étude nécessite le développement de modèles mathématique et statistiques permettent de prendre en compte cette complexité. L’objectif de cette thèse est de développer des modèles pour caractériser la propagation du SARS-CoV-2 en France ainsi que l’impact de différentes interventions. Dans une première partie, nous avons estimé le fardeau du SARS-CoV-2 en France à la fin du premier confinement en mai 2020. Dans une deuxième partie, nous avons étudié la dynamique de transmission du SARS-CoV-2 entre les groupes d’âge. Nous en avons déduit l’impact de mesures de contrôle ciblant différents groupes d’âge, notamment des stratégies fondées sur l’isolement des personnes âgées. La troisième partie est constituée de plusieurs analyses ayant permis d’évaluer l’impact de mesures de contrôle sur la dynamique de l’épidémie, notamment la comparaison de stratégies de priorisation des vaccins, l’utilisation du confinement comme solution de dernier recours en cas de reprise épidémique et l’évaluation des risques et bénéfices associés à différentes stratégies de distribution des vaccins. Les analyses rapportées dans cette thèse illustrent comment la modélisation peut permettre d’étudier la propagation de pathogènes dans des populations et potentiellement éclairer les mesures de contrôle pouvant être mises en place. Les résultats détaillés dans ce manuscrit ont été partagés au cours de la pandémie avec les décideurs et les agences de santé publique en France.
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- 2022
21. Comparing the age and sex trajectories of SARS-CoV-2 morbidity and mortality with other respiratory pathogens
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Metcalf, C Jessica E, Paireau, Juliette, O'Driscoll, Megan, Pivette, Mathilde, Hubert, Bruno, Pontais, Isabelle, Nickbakhsh, Sema, Cummings, Derek AT, Cauchemez, Simon, Salje, Henrik, Metcalf, C Jessica E [0000-0003-3166-7521], Hubert, Bruno [0000-0003-3640-718X], Apollo - University of Cambridge Repository, Princeton University, Direction des maladies infectieuses - Infectious Diseases Division [Saint-Maurice], Santé publique France - French National Public Health Agency [Saint-Maurice, France], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of Cambridge [UK] (CAM), University of Florida [Gainesville] (UF), University of Glasgow, We acknowledge financial support from European Research Council (no. 804744) the EPSRC Impact Acceleration Grant (no. RG90413), European Project: 804744,H2020-EU.1.1.,ARBODYNAMIC(2019), Metcalf, C. Jessica E. [0000-0003-3166-7521], and Salje, Henrik [0000-0003-3626-4254]
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SARS ,Multidisciplinary ,age ,Research articles ,CoV-2 ,[SDV]Life Sciences [q-bio] ,comparing ,virus diseases ,sex ,trajectories ,Science, society and policy - Abstract
Peer reviewed: True, Comparing age and sex differences in SARS-CoV-2 hospitalization and mortality with MERS-CoV, seasonal coronaviruses, influenza and other health outcomes opens the way to generating hypotheses as to underlying mechanisms driving disease risk. Using 60-year-olds as a reference age group, we find that relative rates of hospitalization and mortality associated with the emergent coronaviruses are lower during childhood and start to increase earlier (around puberty) as compared with influenza and seasonal coronaviruses. The changing distribution of disease risk by age for emerging pathogens appears to broadly track the gradual deterioration of the immune system (immunosenescence), which starts around puberty. By contrast, differences in severe disease risk by age from endemic pathogens are more decoupled from the immune ageing process. Intriguingly, age-specific sex differences in hospitalizations are largely similar across endemic and emerging infections. We discuss potential mechanisms that may be associated with these patterns.
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- 2022
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22. Measuring Basic Reproduction Number to Assess Effects of Nonpharmaceutical Interventions on Nosocomial SARS-CoV-2 Transmission
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George, Shirreff, Jean-Ralph, Zahar, Simon, Cauchemez, Laura, Temime, Lulla, Opatowski, Cynthia, Tamandjou, Institut Pasteur [Paris] (IP), Université Paris Cité (UPCité), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Université de Versailles Saint-Quentin-en-Yvelines - UFR Sciences de la santé Simone Veil (UVSQ Santé), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, This work was supported directly by internal resources from the French National Institute for Health and Medical Research, the Institut Pasteur, the Conservatoire National des Arts et Métiers, and the University of Versailles-Saint-Quentin-en-Yvelines/University of Paris-Saclay. This study received funding through the MODCOV project from the Fondation de France (grant no. 106059) as part of the alliance framework 'Tous unis contre le virus,' the Université Paris-Saclay (no. AAP Covid-19 2020) and the French government through its National Research Agency (project no. SPHINX-17-CE36-0008-01)., ANR-17-CE36-0008,SPHINx,Diffusion de pathogènes au sein des réseaux de soins : une étude de modélisation(2017), Bertram, Marie-Liesse, Diffusion de pathogènes au sein des réseaux de soins : une étude de modélisation - - SPHINx2017 - ANR-17-CE36-0008 - AAPG2017 - VALID, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)
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Microbiology (medical) ,[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,Cross Infection ,Infection Control ,Epidemiology ,SARS-CoV-2 ,Basic Reproduction Number ,COVID-19 ,Infectious Diseases ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie - Abstract
International audience; Outbreaks of SARS-CoV-2 infection frequently occur in hospitals. Preventing nosocomial infection requires insight into hospital transmission. However, estimates of the basic reproduction number (R0) in care facilities are lacking. Analyzing a closely monitored SARS-CoV-2 outbreak in a hospital in early 2020, we estimated the patient-to-patient transmission rate and R0. We developed a model for SARS-CoV-2 nosocomial transmission that accounts for stochastic effects and undetected infections and fit it to patient test results. The model formalizes changes in testing capacity over time, and accounts for evolving PCR sensitivity at different stages of infection. R0 estimates varied considerably across wards, ranging from 3 to 15 in different wards. During the outbreak, the hospital introduced a contact precautions policy. Our results strongly support a reduction in the hospital-level R0 after this policy was implemented, from 8.7 to 1.3, corresponding to a policy efficacy of 85% and demonstrating the effectiveness of nonpharmaceutical interventions.
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- 2022
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23. Seroepidemiology of enterovirus A71 infection in prospective cohort studies of children in southern China, 2013-2018
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Yang, J, Liao, Q, Luo, K, Liu, F, Zhou, Y, Zou, G, Huang, W, Yu, S, Wei, X, Zhou, J, Dai, B, Qiu, Q, Altmeyer, R, Hu, H, Paireau, J, Luo, L, Gao, L, Nikolay, B, Hu, S, Xing, W, Wu, P, van Doorn, HR, Horby, PW, Simmonds, P, Leung, GM, Cowling, BJ, Cauchemez, S, Yu, H, Fudan University [Shanghai], Chinese Center for Disease Control and Prevention, Hunan provincial center for disease control and prevention, Institut Pasteur de Shanghai, Académie des Sciences de Chine - Chinese Academy of Sciences (IPS-CAS), Réseau International des Instituts Pasteur (RIIP), Direction des maladies infectieuses - Infectious Diseases Division [Saint-Maurice], Santé publique France - French National Public Health Agency [Saint-Maurice, France], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Shandong First Medical University, Shandong Academy of Medical Sciences, The University of Hong Kong (HKU), Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), University of Oxford, ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), and ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016)
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China ,Multidisciplinary ,Infant, Newborn ,General Physics and Astronomy ,General Chemistry ,General Biochemistry, Genetics and Molecular Biology ,Enterovirus A, Human ,Seroepidemiologic Studies ,Child, Preschool ,Enterovirus Infections ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Prospective Studies ,Child ,Hand, Foot and Mouth Disease ,Antigens, Viral ,Enterovirus - Abstract
Enterovirus A71 (EV-A71)–related hand, foot, and mouth disease (HFMD) imposes a substantial clinical burden in the Asia Pacific region. To inform policy on the introduction of the EV-A71 vaccine into the National Immunization Programme, we investigated the seroepidemiological characteristics of EV-A71 in two prospective cohorts of children in southern China conducted between 2013 and 2018. Our results show that maternal antibody titres declined rapidly in neonates, with over half becoming susceptible to EV-A71 at 1 month of age. Between 6 months and 2 years of age, over 80% of study participants were susceptible, while one third remained susceptible at 5 years old. The highest incidence of EV-A71 infections was observed in children aged 5-6 months. Our findings support EV-A71 vaccination before 6 months for birth cohorts in southern China, potentially with a one-time catch-up vaccination for children 6 months-5 years old. More regionally representative longitudinal seroepidemiological studies are needed to further validate these findings.
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- 2022
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24. An ensemble model based on early predictors to forecast COVID-19 health care demand in France
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Juliette Paireau, Alessio Andronico, Nathanaël Hozé, Maylis Layan, Pascal Crépey, Alix Roumagnac, Marc Lavielle, Pierre-Yves Boëlle, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Direction des maladies infectieuses - Infectious Diseases Division [Saint-Maurice], Santé publique France - French National Public Health Agency [Saint-Maurice, France], Centre de Recherches sur l'Action Politique en Europe (ARENES), Université de Rennes (UR)-Institut d'Études Politiques [IEP] - Rennes-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Centre National de la Recherche Scientifique (CNRS), Recherche sur les services et le management en santé (RSMS), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Predict Services [Castelnau-le-Lez], Modélisation en pharmacologie de population (XPOP), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut Polytechnique de Paris (IP Paris), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62- IBEID), Santé publique France, the INCEPTION project (PIA/ANR16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grants 101003589(RECOVER) and 874735 (VEO), AXA, Groupama, and EMERGEN, ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020), Lassailly-Bondaz, Anne, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Rapid European COVID-19 Emergency Response research - RECOVER - - H2020-SC1-PHE-CORONAVIRUS-20202020-02-14 - 2022-02-13 - 101003589 - VALID, and Versatile Emerging infectious disease Observatory - VEO - - H2020-SC1-2019-Single-Stage-RTD2020-01-01 - 2024-12-31 - 874735 - VALID
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MESH: Health Services Needs and Demand ,Health Services Needs and Demand ,MESH: Pandemics ,Multidisciplinary ,MESH: Humans ,MESH: Delivery of Health Care ,COVID-19 ,forecasting ,MESH: Retrospective Studies ,MESH: France ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,Humans ,MESH: COVID-19 ,ensemble model ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,France ,Delivery of Health Care ,Pandemics ,Retrospective Studies - Abstract
Short-term forecasting of the COVID-19 pandemic is required to facilitate the planning of COVID-19 health care demand in hospitals. Here, we evaluate the performance of 12 individual models and 19 predictors to anticipate French COVID-19-related health care needs from September 7, 2020, to March 6, 2021. We then build an ensemble model by combining the individual forecasts and retrospectively test this model from March 7, 2021, to July 6, 2021. We find that the inclusion of early predictors (epidemiological, mobility, and meteorological predictors) can halve the rms error for 14-d–ahead forecasts, with epidemiological and mobility predictors contributing the most to the improvement. On average, the ensemble model is the best or second-best model, depending on the evaluation metric. Our approach facilitates the comparison and benchmarking of competing models through their integration in a coherent analytical framework, ensuring that avenues for future improvements can be identified.
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- 2022
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25. Epidemic models: why and how to use them
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Mircea T. Sofonea, Simon Cauchemez, Pierre-Yves Boëlle, Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM), Université de Montpellier (UM), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)
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[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS] ,Critical Care and Intensive Care Medicine ,[SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy ,PYB -0000-0002-5367-8232 Infectious disease modelling ,[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM] ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO] ,Humans ,[SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology ,Epidemics ,non-pharmaceutical interventions ,ComputingMilieux_MISCELLANEOUS ,[SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,[SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE] ,MTS -0000-0002-4499-0435 ,SARS-CoV-2 ,[SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE] ,public health ,COVID-19 ,General Medicine ,Models, Theoretical ,[SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,[MATH.MATH-LO]Mathematics [math]/Logic [math.LO] ,Anesthesiology and Pain Medicine ,SC -0000-0001-9186-4549 ,[SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,mathematical epidemiology ,[SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis - Abstract
International audience
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- 2022
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26. Reconstructing Mayaro virus circulation in French Guiana shows frequent spillovers
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Antoine Enfissi, Matthieu Najm, Sarah Bailly, Nathanaël Hozé, Dominique Rousset, Jessica Vanhomwegen, Jean-Claude Manuguerra, Camille Fritzell, Claude Flamand, Simon Cauchemez, Henrik Salje, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Centre National de Référence pour les Arbovirus - Laboratoire associé de Virologie [Cayenne, Guyane] (CNR), Institut Pasteur de la Guyane, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Unité d'Epidémiologie, Environnement et Risques infectieux - Environment and Infectious Risks (ERI), Institut Pasteur [Paris], This study was supported by the 'European Regional Development Fund' under EPI-ARBO grant agreement (GY0008695), the 'Regional Health Agency of French Guiana', the 'National Center of Spatial Studies'. C.Fl. and C. Fr. acknowledge funding from Calmette and Yersin allocated by the 'Pasteur Institut Department of International Affairs'. N.H. and S.C. acknowledge financial support from the AXA Research Fund, the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), the Models of Infectious Disease Agent Study of the National Institute of General Medical Sciences, the INCEPTION project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation programme under ZIKAlliance grant agreement No. 734548., We wish to thank Mirdad Kazanji (Institut Pasteur in French Guiana), Félix Djossou (Cayenne hospital center), Sandrine Fernandes-Pellerin (Institut Pasteur - CRT), and Léna Berthelot, Séverine Matheus, Laetitia Bremand, Bhety Labeau, David Moua, and Marine Rangon from the Arbovirus National Reference Center for their valuable contribution in the laboratory analyses. We thank Juliette Paireau and Quirine ten Bosch for insightful discussions., ANR-10-LABX-62-IBEID,IBEID,Laboratoire d'Excellence 'Integrative Biology of Emerging Infectious Diseases'(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l’étude de l’Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 734548,ZIKAlliance(2016), University of Cambridge [UK] (CAM), Centre National de Référence pour les Arbovirus - Laboratoire de Virologie [Cayenne, Guyane française] (CNR - laboratoire associé), Réseau International des Instituts Pasteur (RIIP), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris] (IP), Hozé, Nathanaël [0000-0002-3977-8966], Salje, Henrik [0000-0003-3626-4254], Rousset, Dominique [0000-0002-1473-3147], Manuguerra, Jean-Claude [0000-0002-5202-6531], Flamand, Claude [0000-0002-8064-445X], and Apollo - University of Cambridge Repository
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Male ,0301 basic medicine ,Statistical methods ,Epidemiology ,[SDV]Life Sciences [q-bio] ,viruses ,General Physics and Astronomy ,Rural Health ,Antibodies, Viral ,medicine.disease_cause ,Communicable Diseases, Emerging ,Viral infection ,MESH: Cross Reactions ,13/1 ,Seroepidemiologic Studies ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,MESH: Arboviruses ,MESH: Child ,MESH: Communicable Diseases, Emerging ,692/308/174 ,Chikungunya ,[MATH]Mathematics [math] ,Child ,MESH: Alphavirus Infections ,lcsh:Science ,MESH: Immunoglobulin G ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,Multidisciplinary ,MESH: Middle Aged ,article ,virus diseases ,Middle Aged ,631/114/2415 ,MESH: Infant ,French Guiana ,3. Good health ,[STAT]Statistics [stat] ,Geography ,MESH: Young Adult ,Child, Preschool ,Epidemiological Monitoring ,[SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology ,Female ,Sylvatic cycle ,Chikungunya virus ,Adult ,Adolescent ,Science ,030106 microbiology ,Cross Reactions ,Arbovirus ,General Biochemistry, Genetics and Molecular Biology ,Virus ,Young Adult ,03 medical and health sciences ,MESH: Cross-Sectional Studies ,692/699/255/2514 ,Environmental health ,MESH: French Guiana ,medicine ,Humans ,Natural reservoir ,Viral immunology ,MESH: Adolescent ,MESH: Seroepidemiologic Studies ,MESH: Humans ,Alphavirus Infections ,MESH: Child, Preschool ,Infant ,[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology ,MESH: Adult ,MESH: Chikungunya virus ,General Chemistry ,MESH: Rural Health ,biochemical phenomena, metabolism, and nutrition ,medicine.disease ,MESH: Male ,Cross-Sectional Studies ,030104 developmental biology ,Immunoglobulin G ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,lcsh:Q ,MESH: Epidemiological Monitoring ,MESH: Female ,Arboviruses ,MESH: Antibodies, Viral - Abstract
Characterizing the circulation of Mayaro virus (MAYV), an emerging arbovirus threat, is essential for risk assessment but challenging due to cross-reactivity with other alphaviruses such as chikungunya virus (CHIKV). Here, we develop an analytical framework to jointly assess MAYV epidemiology and the extent of cross-reactivity with CHIKV from serological data collected throughout French Guiana (N = 2697). We find strong evidence of an important sylvatic cycle for MAYV with most infections occurring near the natural reservoir in rural areas and in individuals more likely to go to the forest (i.e., adult males) and with seroprevalences of up to 18% in some areas. These findings highlight the need to strengthen MAYV surveillance in the region and showcase how modeling can improve interpretation of cross-reacting assays., Mayaro virus (MAYV) is an emerging arbovirus, but cross-reactivity with other alphaviruses makes analysis of its epidemiology difficult. Here, the authors develop an analytical framework to assess MAYV epidemiology and find evidence for an important sylvatic cycle and seroprevalences of up to 18% in some areas of French Guiana.
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- 2020
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27. Risk for Transportation of Coronavirus Disease from Wuhan to Other Cities in China
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Zhanwei Du, Xianwen Wang, Benjamin J. Cowling, Xiaoke Xu, Simon Cauchemez, Lin Wang, Lauren Ancel Meyers, University of Texas at Austin [Austin], Institut Pasteur [Paris] (IP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Dalian Minzu University, Dalian University of Technology, The University of Hong Kong (HKU), Santa Fe Institute, We acknowledge the financial support from National Institutes of Health (grant no. U01 GM087719), the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant no. ANR-10-LABX-62-IBEID), European Union V.E.O project, the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources (grant no. KF-2019-04-034), and the National Natural Science Foundation of China (grant no. 61773091)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), Institut Pasteur [Paris], Wang, Lin [0000-0002-5371-2138], and Apollo - University of Cambridge Repository
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Risk for Transportation of 2019 Novel Coronavirus Disease from Wuhan to Other Cities in China ,MESH: Coronavirus Infections ,Epidemiology ,coronavirus ,lcsh:Medicine ,Transportation ,medicine.disease_cause ,MESH: Risk Assessment ,Disease Outbreaks ,law.invention ,0302 clinical medicine ,law ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,Pandemic ,MESH: COVID-19 ,030212 general & internal medicine ,MESH: Disease Outbreaks ,Socioeconomics ,Coronavirus ,MESH: China ,3. Good health ,Geography ,Infectious Diseases ,MESH: Stochastic Processes ,2019-nCoV ,Quarantine ,MESH: Betacoronavirus ,Coronavirus Infections ,Risk assessment ,MESH: Quarantine ,severe acute respiratory syndrome coronavirus 2 ,Wuhan ,MESH: Forecasting ,Microbiology (medical) ,China ,MESH: Pandemics ,Coronavirus disease 2019 (COVID-19) ,Pneumonia, Viral ,030231 tropical medicine ,Risk Assessment ,lcsh:Infectious and parasitic diseases ,2019 novel coronavirus disease ,Betacoronavirus ,03 medical and health sciences ,Research Letter ,medicine ,MESH: Cities ,Humans ,lcsh:RC109-216 ,viruses ,MESH: SARS-CoV-2 ,Cities ,Pandemics ,Stochastic Processes ,Models, Statistical ,MESH: Humans ,outbreak ,SARS-CoV-2 ,MESH: Transportation ,lcsh:R ,importation ,Outbreak ,COVID-19 ,Metropolitan area ,MESH: Pneumonia, Viral ,MESH: Models, Statistical ,Forecasting - Abstract
International audience; On January 23, 2020, China quarantined Wuhan to contain coronavirus disease (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 other cities in China before the quarantine. Expected COVID-19 risk is >50% in 130 (95% CI 89-190) cities and >99% in the 4 largest metropolitan areas.
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- 2020
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28. The epidemiology of hepatitis delta virus infection in Cameroon
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Juliette Paireau, Mathurin Cyrille Tejiokem, Jacques Pépin, Richard Njouom, Arnaud Fontanet, Guillaume Lachenal, Simon Cauchemez, Gaëtan Texier, Camille Besombes, Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Centre Pasteur du Cameroun, Réseau International des Instituts Pasteur (RIIP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Médialab (Sciences Po) (Médialab), Sciences Po (Sciences Po), Université de Sherbrooke (UdeS), This study was funded by the Agence Nationale de Recherche sur le Sida et les Hépatites Virales (grant ANRS 12289) and got support from the INCEPTION project (PIA/ANR-16-CONV-0005)., ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), and médialab (Sciences Po) (médialab)
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Adult ,Male ,0301 basic medicine ,medicine.medical_specialty ,HBsAg ,Adolescent ,viruses ,Hepatitis C virus ,medicine.disease_cause ,Virus ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,Risk Factors ,Epidemiology ,Prevalence ,medicine ,Humans ,Cameroon ,Geography, Medical ,Hepatitis B virus ,Family Characteristics ,biology ,Transmission (medicine) ,business.industry ,Gastroenterology ,virus diseases ,biochemical phenomena, metabolism, and nutrition ,Middle Aged ,medicine.disease ,[SDE.ES]Environmental Sciences/Environmental and Society ,Hepatitis D ,Virology ,3. Good health ,030104 developmental biology ,biology.protein ,Female ,030211 gastroenterology & hepatology ,Hepatitis Delta Virus ,Antibody ,business - Abstract
ObjectiveTo investigate the distribution and risk factors of hepatitis delta virus (HDV) infection in Cameroon.DesignWe tested for hepatitis B virus (HBV) surface antigen (HBsAg) and anti-HDV antibody 14 150 samples collected during a survey whose participants were representative of the Cameroonian adult population. The samples had already been tested for hepatitis C virus and HIV antibodies.ResultsOverall, 1621/14 150 (weighted prevalence=11.9%) participants were HBsAg positive, among whom 224/1621 (10.6%) were anti-HDV positive. In 2011, the estimated numbers of HBsAg positive and HDV seropositives were 1 160 799 and 122 910 in the 15–49 years age group, respectively. There were substantial regional variations in prevalence of chronic HBV infection, but even more so for HDV (from 1% to 54%). In multivariable analysis, HDV seropositivity was independently associated with living with an HDV-seropositive person (OR=8.80; 95% CI: 3.23 to 24.0), being HIV infected (OR=2.82; 95% CI: 1.32 to 6.02) and living in the South (latitude ConclusionWe found evidence for effective intra-household transmission of HDV in Cameroon. We also identified large differences in prevalence between regions, with cases concentrated in forested areas close to the Equator, as described in other tropical areas. The reasons underlying these geographical variations in HDV prevalence deserve further investigation.
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- 2020
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29. Specificity, kinetics and longevity of antibody responses to avian influenza A(H7N9) virus infection in humans
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Peter Horby, Xiaowei Deng, Yi Guan, Hui Jiang, Hongjie Yu, Wei Wang, Jiaxin Zhou, Qianli Wang, Simon Cauchemez, Tianchen Zhang, Hongbo Zhu, Yongli Zhang, Timothy M. Uyeki, Xinhua Chen, Liwei Liu, Junbo Chen, Birgit Nikolay, Shanghai Medical College, Fundan University [Shanghai China], Shantou University [Shantou, China], The University of Hong Kong (HKU), University of Oxford, Capital University of Medical Sciences [Beijing] (CUMS), Beijing Tuberculosis and Thoracic Tumor Research Institute, Partenaires INRAE, Jiangxi Province People’s Hospital, University of Chinese Academy of Sciences [Beijing] (UCAS), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Centers for Disease Control and Prevention [Atlanta] (CDC), Centers for Disease Control and Prevention, and ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010)
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0301 basic medicine ,Microbiology (medical) ,animal structures ,[SDV]Life Sciences [q-bio] ,viruses ,030106 microbiology ,Disease ,medicine.disease_cause ,Antibodies, Viral ,Influenza A Virus, H7N9 Subtype ,Virus ,Article ,Serology ,03 medical and health sciences ,0302 clinical medicine ,Influenza, Human ,Medicine ,Animals ,Humans ,Clinical severity ,030212 general & internal medicine ,Influenza A(H7N9) ,Hemagglutination assay ,business.industry ,Follow-up ,Antibody titer ,virus diseases ,Influenza A virus subtype H5N1 ,Titer ,Kinetics ,Infectious Diseases ,Respiratory failure ,Influenza in Birds ,Immunology ,Antibody response ,Antibody Formation ,business ,Follow-Up Studies - Abstract
Highlights • A(H7N9) patients mounted strong serum HAI antibody responses against A(H7N9) virus. • Mean A(H7N9) virus-specific HAI antibody titers remained above 80 for 11 months. • Severely ill patients mounted higher HAI antibody responses against A(H7N9) virus., Objectives The long-term dynamics of antibody responses in patients with influenza A(H7N9) virus infection are not well understood. Methods We conducted a longitudinal serological follow-up study in patients who were hospitalized with A(H7N9) virus infection, during 2013–2018. A(H7N9) virus-specific antibody responses were assessed by hemagglutination inhibition (HAI) and neutralization (NT) assays. A random intercept model was used to fit a curve to HAI antibody responses over time. HAI antibody responses were compared by clinical severity. Results Of 67 patients with A(H7N9) virus infection, HAI antibody titers reached 40 on average 11 days after illness onset and peaked at a titer of 290 after three months, and average titers of ≥80 and ≥40 were present until 11 months and 22 months respectively. HAI antibody responses were significantly higher in patients who experienced severe disease, including respiratory failure and acute respiratory distress syndrome, compared with patients who experienced less severe illness. Conclusions Patients with A(H7N9) virus infection who survived severe disease mounted higher antibody responses that persisted for longer periods compared with those that experienced moderate disease. Studies of convalescent plasma treatment for A(H7N9) patients should consider collection of donor plasma from survivors of severe disease between 1 and 11 months after illness onset.
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- 2020
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30. Zika Virus Circulation in Mali
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Abdoulaye Dabo, Simon Cauchemez, Souleymane Sacko, Bourema Kouriba, Abdoulaye Djimde, Jan Felix Drexler, Anna-Bella Failloux, Pierre Gallian, Abdoul Karim Sangaré, Ogobara K. Doumbo, Issa Diarra, Drissa Coulibaly, Amatigue Zeguime, Xavier de Lamballerie, Nathanaël Hozé, Elif Nurtop, Bakary Fofana, Boris Pastorino, Stéphane Priet, Issaka Sagara, Mahamadou Ali Thera, Unité des Virus Emergents (UVE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Malaria Research and Training Center [Bamako, Mali], Université de Bamako, Ministère de la Santé et des Affaires Sociales du Mali [Bamako, Mali], Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), Etablissement Français du Sang - Alpes-Méditerranée (EFS - Alpes-Méditerranée), Etablissement Français du Sang, German Center for Infection Research, Partnersite Munich (DZIF), Arbovirus et Insectes Vecteurs - Arboviruses and Insect Vectors, Institut Pasteur [Paris] (IP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), BUISINE, Soline, Aix Marseille Université (AMU)-Institut de Recherche pour le Développement (IRD)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université des sciences, des techniques et des technologies de Bamako (USTTB), Institut Pasteur [Paris], and Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)
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Microbiology (medical) ,Male ,Epidemiology ,030231 tropical medicine ,Population ,vector-borne infections ,lcsh:Medicine ,Blood Donors ,Zika Virus Circulation in Mali ,Mali ,Asymptomatic ,Arbovirus ,lcsh:Infectious and parasitic diseases ,Zika virus ,Serology ,03 medical and health sciences ,0302 clinical medicine ,Seroepidemiologic Studies ,medicine ,Seroprevalence ,Humans ,lcsh:RC109-216 ,viruses ,030212 general & internal medicine ,education ,mosquitoes ,[SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology ,education.field_of_study ,biology ,seroprevalence ,Transmission (medicine) ,Zika Virus Infection ,Research ,lcsh:R ,Outbreak ,Zika Virus ,biology.organism_classification ,medicine.disease ,Virology ,3. Good health ,Infectious Diseases ,arbovirus ,[SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology ,Female ,medicine.symptom - Abstract
International audience; The circulation of Zika virus (ZIKV) in Mali has not been clearly characterized. Therefore, we conducted a serologic survey of 793 asymptomatic volunteers >15 years of age (2016), and 637 blood donors (2013) to assess the seroprevalence of ZIKV infection in 2 ecoclimatic regions of Mali, tropical savannah and warm semiarid region, using ELISA and seroneutralization assays. The overall seroprevalence was ≈12% and increased with age, with no statistical difference between male and female participants. In the warm semiarid study sites we detected immunological markers of an outbreak that occurred in the late 1990s in 18% (95% CI 13%-23%) of participants. In tropical savannah sites, we estimated a low rate of endemic transmission, with 2.5% (95% CI 2.0%-3.1%) of population infected by ZIKV annually. These data demonstrate the circulation of ZIKV in Mali and provide evidence of a previously unidentified outbreak that occurred in the late 1990s.
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- 2020
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31. Global spatial dynamics and vaccine-induced fitness changes of Bordetella pertussis
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Noémie Lefrancq, Valérie Bouchez, Nadia Fernandes, Alex-Mikael Barkoff, Thijs Bosch, Tine Dalby, Thomas Åkerlund, Jessica Darenberg, Katerina Fabianova, Didrik F. Vestrheim, Norman K. Fry, Juan José González-López, Karolina Gullsby, Adele Habington, Qiushui He, David Litt, Helena Martini, Denis Piérard, Paola Stefanelli, Marc Stegger, Jana Zavadilova, Nathalie Armatys, Annie Landier, Sophie Guillot, Samuel L. Hong, Philippe Lemey, Julian Parkhill, Julie Toubiana, Simon Cauchemez, Henrik Salje, Sylvain Brisse, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of Cambridge [UK] (CAM), Biodiversité et Epidémiologie des Bactéries pathogènes - Biodiversity and Epidemiology of Bacterial Pathogens, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Centre national de Référence de la Coqueluche et autres Bordetelloses - National Reference Center for Whooping Cough and other Bordetella infections (CNR), University of Turku, National Institute for Public Health and the Environment [Bilthoven] (RIVM), Statens Serum Institut [Copenhagen], The Public Health Agency of Sweden, National Institute of Public Health [Prague], Norwegian Institute of Public Health [Oslo] (NIPH), Public Health England [London], Vall d'Hebron University Hospital [Barcelona], Universitat Autònoma de Barcelona (UAB), Uppsala University, Children's Health Ireland [Crumlin, Dublin, Ireland] (CHI), Vrije Universiteit Brussel (VUB), Istituto Superiore di Sanità (ISS), Rega Institute, Département de Pédiatrie et maladies infectieuses [CHU Necker], CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), The study was supported financially by the French Government Investissement d’Avenir grant ANR-16-CONV-0005 (INCEPTION project, to S.B. and H.S.). The National Reference Center for Whooping Cough and Other Bordetella Infections receives support from Institut Pasteur and Public Health France (Santé publique France, Saint Maurice, France). This work was also supported financially by the French Government’s Investissement d’Avenir program Laboratoire d’Excellence 'Integrative Biology of Emerging Infectious Diseases' (ANR-10-LABX-62-IBEID) to S.B. and a European Research Council (no. 804744 to H.S.). P.L. acknowledges funding from the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 725422-ReservoirDOCS)., ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), European Project: 804744,H2020-EU.1.1.,ARBODYNAMIC(2019), European Project: 725422,ERC-2016-COG,ReservoirDOCS(2017), Supporting clinical sciences, Microbiology and Infection Control, Clinical Biology, Lefrancq, Noémie [0000-0001-5991-6169], Bouchez, Valérie [0000-0002-5947-6383], Fernandes, Nadia [0000-0003-4595-9939], Dalby, Tine [0000-0003-4774-7091], Åkerlund, Thomas [0000-0001-7516-0218], Darenberg, Jessica [0000-0002-8528-8570], Fabianova, Katerina [0000-0001-8374-4395], Fry, Norman K [0000-0003-4862-6507], González-López, Juan José [0000-0003-2419-5909], Gullsby, Karolina [0000-0002-9673-0483], Habington, Adele [0000-0001-6997-3327], Litt, David [0000-0002-9215-0553], Martini, Helena [0000-0002-5877-9948], Piérard, Denis [0000-0002-7756-3691], Stefanelli, Paola [0000-0003-1620-4385], Stegger, Marc [0000-0003-0321-1180], Armatys, Nathalie [0000-0003-2042-4241], Landier, Annie [0000-0002-8278-4026], Hong, Samuel L [0000-0001-6354-4943], Lemey, Philippe [0000-0003-2826-5353], Parkhill, Julian [0000-0002-7069-5958], Cauchemez, Simon [0000-0001-9186-4549], Salje, Henrik [0000-0003-3626-4254], Brisse, Sylvain [0000-0002-2516-2108], and Apollo - University of Cambridge Repository
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Europe ,Pertussis Vaccine ,Genotype ,Whooping Cough ,[SDV]Life Sciences [q-bio] ,Humans ,General Medicine ,[SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology ,[SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology ,Bordetella pertussis - Abstract
As with other pathogens, competitive interactions between Bordetella pertussis strains drive infection risk. Vaccines are thought to perturb strain diversity through shifts in immune pressures; however, this has rarely been measured because of inadequate data and analytical tools. We used 3344 sequences from 23 countries to show that, on average, there are 28.1 transmission chains circulating within a subnational region, with the number of chains strongly associated with host population size. It took 5 to 10 years for B. pertussis to be homogeneously distributed throughout Europe, with the same time frame required for the United States. Increased fitness of pertactin-deficient strains after implementation of acellular vaccines, but reduced fitness otherwise, can explain long-term genotype dynamics. These findings highlight the role of vaccine policy in shifting local diversity of a pathogen that is responsible for 160,000 deaths annually.
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- 2022
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32. Transmission of Antimicrobial Resistant Yersinia pestis during a Pneumonic Plague Outbreak
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Jason W. Sahl, Minoarisoa Rajerison, Nawarat Somprasong, Birgit Nikolay, Carina M. Hall, Harimahefa Razafimandimby, Christophe Rogier, Voahangy Andrianaivoarimanana, David M. Wagner, Amy J. Vogler, Lovasoa Nomena Randriantseheno, Herbert P. Schweizer, Simon Cauchemez, Faniry Rakotoarimanana, Dawn N. Birdsell, Institut Pasteur de Madagascar, Réseau International des Instituts Pasteur (RIIP), Northern Arizona University [Flagstaff], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of Florida [Gainesville] (UF), Ministère de la Santé Publique - Ministry of Public Health [Antananarivo, Madagascar], and This work was supported by the Institut Pasteur de Madagascar
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Microbiology (medical) ,Pneumonic plague ,Yersinia pestis ,[SDV]Life Sciences [q-bio] ,Virulence ,Bubonic plague ,Disease Outbreaks ,Antibiotic resistance ,medicine ,Animals ,antimicrobial resistance ,Retrospective Studies ,Plague ,biology ,outbreak ,Transmission (medicine) ,business.industry ,Outbreak ,biology.organism_classification ,medicine.disease ,Virology ,Anti-Bacterial Agents ,Infectious Diseases ,Streptomycin ,pneumonic plague ,business ,medicine.drug - Abstract
Background Pneumonic plague (PP), caused by Yersinia pestis, is the most feared clinical form of plague due to its rapid lethality and potential to cause outbreaks. PP outbreaks are now rare due to antimicrobial therapy. Methods A PP outbreak in Madagascar involving transmission of a Y. pestis strain resistant to streptomycin, the current recommended first-line treatment in Madagascar, was retrospectively characterized using epidemiology, clinical diagnostics, molecular characterization, and animal studies. Results The outbreak occurred in February 2013 in the Faratsiho district of Madagascar and involved 22 cases, including 3 untreated fatalities. The 19 other cases participated in funeral practices for the fatal cases and fully recovered after combination antimicrobial therapy: intramuscular streptomycin followed by oral co-trimoxazole. The Y. pestis strain that circulated during this outbreak is resistant to streptomycin resulting from a spontaneous point mutation in the 30S ribosomal protein S12 (rpsL) gene. This same mutation causes streptomycin resistance in 2 unrelated Y. pestis strains, one isolated from a fatal PP case in a different region of Madagascar in 1987 and another isolated from a fatal PP case in China in 1996, documenting this mutation has occurred independently at least 3 times in Y. pestis. Laboratory experiments revealed this mutation has no detectable impact on fitness or virulence, and revertants to wild-type are rare in other species containing it, suggesting Y. pestis strains containing it could persist in the environment. Conclusions Unique antimicrobial resistant (AMR) strains of Y. pestis continue to arise in Madagascar and can be transmitted during PP outbreaks.
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- 2022
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33. Early chains of transmission of COVID-19 in France, January to March 2020
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Juliette Paireau, Alexandra Mailles, Catherine Eisenhauer, Franck de Laval, François Delon, Paolo Bosetti, Henrik Salje, Valérie Pontiès, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Santé publique France - French National Public Health Agency [Saint-Maurice, France], Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'épidémiologie et de santé publique des armées [Marseille] (CESPA), Service de Santé des Armées, Institut des sciences de la santé publique [Marseille] (ISSPAM), University of Cambridge [UK] (CAM), Santé publique France, Haut-de-France [Lille, France], This work was supported by the LabEx Integrative Biology of Emerging Infectious Diseases (IBEID) (Grant Number ANR-10-LABX-62-IBEID), Santé Publique France, project Theracov, the INCEPTION project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grants 101003589 (RECOVER) and 874735 (VEO), and the National Research Agency (ANR) through the ANR-Flash call for COVID-19 (Grant ANR-20-COVI-0018)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), ANR-20-COVI-0018,TheraCoV,Dynamique virale au niveau individuel et populationnel : implications pour l'optimisation des stratégies antivirales(2020), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020), PAIREAU, Juliette, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Dynamique virale au niveau individuel et populationnel : implications pour l'optimisation des stratégies antivirales - - TheraCoV2020 - ANR-20-COVI-0018 - COVID-19 - VALID, Rapid European COVID-19 Emergency Response research - RECOVER - - H2020-SC1-PHE-CORONAVIRUS-20202020-02-14 - 2022-02-13 - 101003589 - VALID, and Versatile Emerging infectious disease Observatory - VEO - - H2020-SC1-2019-Single-Stage-RTD2020-01-01 - 2024-12-31 - 874735 - VALID
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MESH: Pandemics ,MESH: Humans ,SARS-CoV-2 ,Epidemiology ,transmission ,Public Health, Environmental and Occupational Health ,COVID-19 ,MESH: Retrospective Studies ,contact tracing ,secondary clinical attack rate ,MESH: Contact Tracing ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,Virology ,Humans ,MESH: COVID-19 ,superspreading ,MESH: SARS-CoV-2 ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,cluster ,Pandemics ,Retrospective Studies - Abstract
Introduction SARS-CoV-2, the virus that causes COVID-19, has spread rapidly worldwide. In January 2020, a surveillance system was implemented in France for early detection of cases and their contacts to help limit secondary transmissions. Aim To use contact-tracing data collected during the initial phase of the COVID-19 pandemic to better characterise SARS-CoV-2 transmission. Methods We analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterised the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread. Results During the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95% confidence interval (CI): 3.6–4.6), increasing with age of index case and contact. Compared with co-workers/friends, family contacts were at higher risk of becoming cases (adjusted odds ratio (AOR): 2.1, 95% CI: 1.4–3.0) and nosocomial contacts were at lower risk (AOR: 0.3, 95% CI: 0.1–0.7). Of 328 infector/infectee pairs, 49% were family members. The distribution of secondary cases was highly over-dispersed: 80% of secondary cases were caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range (IQR): 2–8 days) in contact tracing pairs, where late transmission events may be censored, and 6.8 (3–8) days in pairs investigated retrospectively. Conclusion This study increases knowledge of SARS-CoV-2 transmission, including the importance of superspreading events during the onset of the pandemic.
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34. Impact of booster vaccination on the control of COVID-19 Delta wave in the context of waning immunity: application to France in the winter 2021/22
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Paolo Bosetti, Cécile Tran Kiem, Alessio Andronico, Juliette Paireau, Daniel Levy-Bruhl, Lise Alter, Arnaud Fontanet, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), Santé publique France - French National Public Health Agency [Saint-Maurice, France], Haute Autorité de Santé [Saint-Denis La Plaine] (HAS), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Université Paris Cité (UPCité)-Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), HAS, Santé Publique France, the EMERGEN project (ANRS0151), the INCEPTION project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grant 101003589 (RECOVER) and 874735 (VEO), AXA and Groupama., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), European Project: 874735,VEO, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPC), Université Paris Cité (UPC)-Pasteur-Cnam Risques infectieux et émergents (PACRI), HESAM Université (HESAM)-HESAM Université (HESAM)-Université Paris Cité (UPC)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université (HESAM)-HESAM Université (HESAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-Université Paris Cité (UPC)
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0303 health sciences ,COVID-19 Vaccines ,SARS-CoV-2 ,Epidemiology ,Vaccination ,Immunization, Secondary ,Public Health, Environmental and Occupational Health ,COVID-19 ,3. Good health ,modelling ,03 medical and health sciences ,0302 clinical medicine ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Virology ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,France ,Seasons ,030212 general & internal medicine ,Rapid Communication ,030304 developmental biology - Abstract
Europe has experienced a large COVID-19 wave caused by the Delta variant in winter 2021/22. Using mathematical models applied to Metropolitan France, we find that boosters administered to ≥ 65, ≥ 50 or ≥ 18 year-olds may reduce the hospitalisation peak by 25%, 36% and 43% respectively, with a delay of 5 months between second and third dose. A 10% reduction in transmission rates might further reduce it by 41%, indicating that even small increases in protective behaviours may be critical to mitigate the wave.
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35. Screening and vaccination against COVID-19 to minimise school closure: a modelling study
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Elisabetta Colosi, Giulia Bassignana, Diego Andrés Contreras, Canelle Poirier, Pierre-Yves Boëlle, Simon Cauchemez, Yazdan Yazdanpanah, Bruno Lina, Arnaud Fontanet, Alain Barrat, Vittoria Colizza, Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Centre de Physique Théorique - UMR 7332 (CPT), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), CPT - E5 Physique statistique et systèmes complexes, Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Virology and human respiratory Pathologies - Virology and human respiratory Pathologies (VirPath), Centre International de Recherche en Infectiologie (CIRI), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Université Paris Cité (UPCité)-Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Tokyo Institute of Technology [Tokyo] (TITECH), EU Framework Programme for Research and Innovation Horizon 2020, Horizon Europe Framework Programme, Agence Nationale de la Recherche, ANRS – Maladies infectieuses émergentes, ANR-20-COV1-0005,GravCOVID19Fr,Facteurs d'hospitalisation et de décès pour COVID-19 dans la population française(2020), Centre International de Recherche en Infectiologie - UMR (CIRI), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Bassignana, Giulia
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[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,Schools ,SARS-CoV-2 ,education ,Vaccination ,COVID-19 ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,[SDV.IMM.VAC] Life Sciences [q-bio]/Immunology/Vaccinology ,Infectious Diseases ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation ,[SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology ,Child ,Pandemics - Abstract
Background Schools were closed extensively in 2020–21 to counter SARS-CoV-2 spread, impacting students’ education and wellbeing. With highly contagious variants expanding in Europe, safe options to maintain schools open are urgently needed. By estimating school-specific transmissibility, our study evaluates costs and benefits of different protocols for SARS-CoV-2 control at school. Methods We developed an agent-based model of SARS-CoV-2 transmission in schools. We used empirical contact data in a primary and a secondary school and data from pilot screenings in 683 schools during the alpha variant (B.1.1.7) wave in March–June, 2021, in France. We fitted the model to observed school prevalence to estimate the schoolspecific effective reproductive number for the alpha (Ralpha) and delta (B.1.617.2; Rdelta) variants and performed a cost– benefit analysis examining different intervention protocols. Findings We estimated Ralpha to be 1·40 (95% CI 1·35–1·45) in the primary school and 1·46 (1·41–1·51) in the secondary school during the spring wave, higher than the time-varying reproductive number estimated from community surveillance. Considering the delta variant and vaccination coverage in Europe as of mid-September, 2021, we estimated Rdelta to be 1·66 (1·60–1·71) in primary schools and 1·10 (1·06–1·14) in secondary schools. Under these conditions, weekly testing of 75% of unvaccinated students (PCR tests on saliva samples in primary schools and lateral flow tests in secondary schools), in addition to symptom-based testing, would reduce cases by 34% (95% CI 32–36) in primary schools and 36% (35–39) in secondary schools compared with symptom-based testing alone. Insufficient adherence was recorded in pilot screening (median ≤53%). Regular testing would also reduce studentdays lost up to 80% compared with reactive class closures. Moderate vaccination coverage in students would still benefit from regular testing for additional control—ie, weekly testing 75% of unvaccinated students would reduce cases compared with symptom-based testing only, by 23% in primary schools when 50% of children are vaccinated. Interpretation The COVID-19 pandemic will probably continue to pose a risk to the safe and normal functioning of schools. Extending vaccination coverage in students, complemented by regular testing with good adherence, are essential steps to keep schools open when highly transmissible variants are circulating.
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- 2022
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36. Impact of BNT162b2 Vaccination and Isolation on SARS-CoV-2 Transmission in Israeli Households: An Observational Study
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Layan, Maylis, Gilboa, Mayan, Gonen, Tal, Goldenfeld, Miki, Meltzer, Lilac, Andronico, Alessio, Hozé, Nathanaël, Cauchemez, Simon, Regev-Yochay, Gili, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), Chaim Sheba Medical Center, Tel Aviv University (TAU), Sheba Medical CenterEMERGEN project (ANRS0151)Haute Autorité de Santé (HAS)AXA, and Groupama, ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-20-COVI-0018,TheraCoV,Dynamique virale au niveau individuel et populationnel : implications pour l'optimisation des stratégies antivirales(2020), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), and European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020)
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Adult ,Family Characteristics ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,Adolescent ,vaccine effectiveness ,Epidemiology ,SARS-CoV-2 ,COVID-19 ,Bayes Theorem ,infectious disease transmission ,vaccination ,household ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Humans ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Israel ,[SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology ,Child ,physical distancing ,BNT162 Vaccine - Abstract
Several studies have characterized the effectiveness of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. However, estimates of their impact on transmissibility remain limited. Here, we evaluated the impact of isolation and vaccination (7 days after the second dose) on SARS-CoV-2 transmission within Israeli households. From December 2020 to April 2021, confirmed cases were identified among health-care workers of the Sheba Medical Centre and their family members. Recruited households were followed up with repeated PCR for at least 10 days after case confirmation. Data were analyzed using a data augmentation Bayesian framework. A total of 210 households with 215 index cases were enrolled; 269 out of 667 (40%) susceptible household contacts developed a SARS-CoV-2 infection. Of those, 170 (63%) developed symptoms. Compared with unvaccinated and unisolated adult/teenager (aged >12 years) contacts, vaccination reduced the risk of infection among unisolated adult/teenager contacts (relative risk (RR) = 0.21, 95% credible interval (CrI): 0.08, 0.44), and isolation reduced the risk of infection among unvaccinated adult/teenager (RR = 0.12, 95% CrI: 0.06, 0.21) and child contacts (RR = 0.17, 95% CrI: 0.08, 0.32). Infectivity was reduced in vaccinated cases (RR = 0.25, 95% CrI: 0.06, 0.77). Within households, vaccination reduces both the risk of infection and of transmission if infected. When contacts were unvaccinated, isolation also led to important reductions in the risk of transmission.
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- 2022
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37. Analytical framework to evaluate and optimize the use of imperfect diagnostics to inform outbreak response : Application to the 2017 plague epidemic in Madagascar
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Quirine ten Bosch, Voahangy Andrianaivoarimanana, Beza Ramasindrazana, Guillain Mikaty, Rado J. L. Rakotonanahary, Birgit Nikolay, Soloandry Rahajandraibe, Maxence Feher, Quentin Grassin, Juliette Paireau, Soanandrasana Rahelinirina, Rindra Randremanana, Feno Rakotoarimanana, Marie Melocco, Voahangy Rasolofo, Javier Pizarro-Cerdá, Anne-Sophie Le Guern, Eric Bertherat, Maherisoa Ratsitorahina, André Spiegel, Laurence Baril, Minoarisoa Rajerison, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Wageningen University and Research [Wageningen] (WUR), Unité Peste - Plague Unit [Antananarivo, Madagascar], Institut Pasteur de Madagascar, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Environnement et Risques infectieux - Environment and Infectious Risks (ERI), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Cellule d'Intervention Biologique d'Urgence (Centre National de Référence) - Laboratory for Urgent Response to Biological Threats (National Reference Center) (CIBU), Université Paris Cité (UPCité)-Environnement et Risques infectieux - Environment and Infectious Risks (ERI), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP), Unité d’Épidémiologie et de Recherche clinique [Antananarivo, Madagascar], Réseau International des Instituts Pasteur (RIIP), Yersinia, Université Paris Cité (UPCité)-Microbiologie Intégrative et Moléculaire (UMR6047), Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre National de Référence de la Peste et autres Yersinioses - National Reference Center Plague and Yersinioses (CNR), Centre collaborateur de l'OMS Yersinia - WHO Collaborating Center Yersinia (CC-OMS / WHO-CC), Institut Pasteur [Paris] (IP)-Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO)-Université Paris Cité (UPCité), and Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO)
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Plague ,General Immunology and Microbiology ,Yersinia pestis ,General Neuroscience ,[SDV]Life Sciences [q-bio] ,Kwantitatieve Veterinaire Epidemiologie ,Quantitative Veterinary Epidemiology ,General Biochemistry, Genetics and Molecular Biology ,Disease Outbreaks ,Madagascar ,WIAS ,Humans ,Life Science ,Epidemics ,General Agricultural and Biological Sciences - Abstract
During outbreaks, the lack of diagnostic “gold standard” can mask the true burden of infection in the population and hamper the allocation of resources required for control. Here, we present an analytical framework to evaluate and optimize the use of diagnostics when multiple yet imperfect diagnostic tests are available. We apply it to laboratory results of 2,136 samples, analyzed with 3 diagnostic tests (based on up to 7 diagnostic outcomes), collected during the 2017 pneumonic (PP) and bubonic plague (BP) outbreak in Madagascar, which was unprecedented both in the number of notified cases, clinical presentation, and spatial distribution. The extent of these outbreaks has however remained unclear due to nonoptimal assays. Using latent class methods, we estimate that 7% to 15% of notified cases were Yersinia pestis-infected. Overreporting was highest during the peak of the outbreak and lowest in the rural settings endemic to Y. pestis. Molecular biology methods offered the best compromise between sensitivity and specificity. The specificity of the rapid diagnostic test was relatively low (PP: 82%, BP: 85%), particularly for use in contexts with large quantities of misclassified cases. Comparison with data from a subsequent seasonal Y. pestis outbreak in 2018 reveal better test performance (BP: specificity 99%, sensitivity: 91%), indicating that factors related to the response to a large, explosive outbreak may well have affected test performance. We used our framework to optimize the case classification and derive consolidated epidemic trends. Our approach may help reduce uncertainties in other outbreaks where diagnostics are imperfect.
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- 2022
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38. How do i bite thee? let me count the ways: Exploring the implications of individual biting habits of Aedes aegypti for dengue transmission
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Christofferson, Rebecca C, Wearing, Helen J, Turner, Erik A, Walsh, Christine S, Salje, Henrik, Tran-Kiem, Cécile, Cauchemez, Simon, Louisiana State University (LSU), The University of New Mexico [Albuquerque], University of Cambridge [UK] (CAM), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), This work was partially supported by NIH/NIGMS grant R01GM122077 (RCC & HJW) and the Burroughs Wellcome Fund 2019 Collaborative Research Travel Grant (RCC)., Christofferson, Rebecca C [0000-0003-2806-1131], Wearing, Helen J [0000-0002-9837-9797], Cauchemez, Simon [0000-0001-9186-4549], and Apollo - University of Cambridge Repository
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Medicine and health sciences ,Biology and life sciences ,[SDV]Life Sciences [q-bio] ,Public Health, Environmental and Occupational Health ,FOS: Social sciences ,Mosquito Vectors ,Dengue Virus ,Social sciences ,Dengue ,Habits ,Infectious Diseases ,Aedes ,Animals ,Humans ,Research Article - Abstract
Acknowledgements: Thanks to Elizabeth Barrett Browning for the convenient title pun and to Mr. John A. Carriere, Jr. (RCC’s dad) for construction of a custom mosquito-feeding stand., In models of mosquito-borne transmission, the mosquito biting rate is an influential parameter, and understanding the heterogeneity of the process of biting is important, as biting is usually assumed to be relatively homogeneous across individuals, with time-between-bites described by an exponentially distributed process. However, these assumptions have not been addressed through laboratory experimentation. We experimentally investigated the daily biting habits of Ae. aegypti at three temperatures (24°C, 28°C, and 32°C) and determined that there was individual heterogeneity in biting habits (number of bites, timing of bites, etc.). We further explored the consequences of biting heterogeneity using an individual-based model designed to examine whether a particular biting profile determines whether a mosquito is more or less likely to 1) become exposed given a single index case of dengue (DENV) and 2) transmit to a susceptible human individual. Our experimental results indicate that there is heterogeneity among individuals and among temperature treatments. We further show that this results in altered probabilities of transmission of DENV to and from individual mosquitoes based on biting profiles. While current model representation of biting may work under some conditions, it might not uniformly be the best fit for this process. Our data also confirm that biting is a non-monotonic process with temperatures around 28°C being optimum.
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- 2022
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39. Leveraging serology to titrate immunisation programme functionality for diphtheria in Madagascar
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Solohery L. Razafimahatratra, Arthur Menezes, Amy Wesolowski, Lala Rafetrarivony, Simon Cauchemez, Richter Razafindratsimandresy, Aina Harimanana, Tania Crucitti, Jean Marc Collard, C. J. E. Metcalf, Institut Pasteur de Madagascar, Réseau International des Instituts Pasteur (RIIP), Princeton University, Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Unité de Bactériologie Expérimentale [Antananarivo, Madagascar] (IPM), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Unité de Virologie [Antananarivo, Madagascar] (IPM), and AW and CJEM were supported by the Wellcome Trust (106866/Z/15/Z). AW was also supported by a Career Award at the Scientific Interface by the Burroughs Wellcome Fund.
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Male ,Vaccination Coverage ,Adolescent ,Immunization Programs ,Whooping Cough ,Epidemiology ,[SDV]Life Sciences [q-bio] ,Corynebacterium diphtheriae ,Infant ,Diphtheria ,Antibodies, Bacterial ,Bordetella pertussis ,Infectious Diseases ,Seroepidemiologic Studies ,Immunoglobulin G ,Madagascar ,Humans ,Female ,Child ,Diphtheria-Tetanus-Pertussis Vaccine - Abstract
Diphtheria is a potentially devastating disease whose epidemiology remains poorly described in many settings, including Madagascar. Diphtheria vaccination is delivered in combination with pertussis and tetanus antigens and coverage of this vaccine is often used as a core measure of health system functioning. However, coverage is challenging to estimate due to the difficulty in translating numbers of doses delivered into numbers of children effectively immunised. Serology provides an alternative lens onto immunisation, but is complicated by challenges in discriminating between natural and vaccine-derived seropositivity. Here, we leverage known features of the serological profile of diphtheria to bound expectations for vaccine coverage for diphtheria, and further refine these using serology for pertussis. We measured diphtheria antibody titres in 185 children aged 6–11 months and 362 children aged 8–15 years and analysed them with pertussis antibody titres previously measured for each individual. Levels of diphtheria seronegativity varied among age groups (18.9% of children aged 6–11 months old and 11.3% of children aged 8–15 years old were seronegative) and also among the districts. We also find surprisingly elevated levels of individuals seropositive to diphtheria but not pertussis in the 6–11 month old age group suggesting that vaccination coverage or efficacy of the pertussis component of the DTP vaccine remains low or that natural infection of diphtheria may be playing a significant role in seropositivity in Madagascar.
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- 2022
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40. Model-based assessment of Chikungunya and O’nyong-nyong virus circulation in Mali in a serological cross-reactivity context
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Hozé, Nathanaël, Diarra, Issa, Sangaré, Abdoul Karim, Pastorino, Boris, Pezzi, Laura, Kouriba, Bourèma, Sagara, Issaka, Dabo, Abdoulaye, Djimdé, Abdoulaye, Thera, Mahamadou Ali, Doumbo, Ogobara K., de Lamballerie, Xavier, Cauchemez, Simon, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Unité des Virus Emergents (UVE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Malaria Research and Training Center [Bamako, Mali], Université de Bamako, Centre d'Infectiologie Charles Mérieux, Bamako, Mali, Laboratoire de Virologie [UNIV Corse-Inserm] (EA7310), Université Pascal Paoli (UPP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Nathanaël Hozé and Simon Cauchemez acknowledge financial support from the AXA Research Fund, the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), the INCEPTION project (PIA/ANR-16-CONV-0005), We thank the European Union’s Horizon 2020 research and innovation program under ZIKAlliance grant agreement No. 734548 and the Minister of Health and Hygiene of Mali supported this work through the subvention no. 2016/668116-0 from the Mali World Health Organization Local Office., We dedicate this article to Ogobara K. Doumbo, who initiated this project before he passed. May he rest in peace. We thank Christine Isnard from EFS, Marseille for invaluable technical contribution. We are grateful to Ismaila Thera, from MRTC, Bamako who developed the electronic database using ODK and provided the data management service for the study. We also thank the study district health officers and the study population for their cooperation. Specifically, we are indebted to Hamma Maiga, Bakary Sidibé, Modibo Diarra, Kassoum Kayentao, Souleymane Dama, Hamidou Niangaly, Amadou Bamadio, Hamadoun Diaité, Karim Traoré and Balla Diarra for their support to field investigations., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 734548,ZIKAlliance(2016), Limouzin, Cécile, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, A global alliance for Zika virus control and prevention - ZIKAlliance - 2016-10-01 - 2019-09-30 - 734548 - VALID, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pascal Paoli (UPP)
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Statistical methods ,Viral epidemiology ,Epidemiology ,viruses ,Science ,MESH: Algorithms ,[MATH] Mathematics [math] ,MESH: Chikungunya Fever ,Cross Reactions ,Mali ,Sensitivity and Specificity ,Article ,MESH: Cross Reactions ,Seroepidemiologic Studies ,MESH: Martinique ,parasitic diseases ,Humans ,O'nyong-nyong Virus ,Martinique ,[MATH]Mathematics [math] ,Models, Statistical ,MESH: Seroepidemiologic Studies ,MESH: Humans ,Reproducibility of Results ,virus diseases ,MESH: Chikungunya virus ,MESH: Mali ,MESH: Sensitivity and Specificity ,MESH: O'nyong-nyong Virus ,MESH: Reproducibility of Results ,Viral infection ,Chikungunya Fever ,Chikungunya virus ,Algorithms ,MESH: Models, Statistical - Abstract
Serological surveys are essential to quantify immunity in a population but serological cross-reactivity often impairs estimates of the seroprevalence. Here, we show that modeling helps addressing this key challenge by considering the important cross-reactivity between Chikungunya (CHIKV) and O’nyong-nyong virus (ONNV) as a case study. We develop a statistical model to assess the epidemiology of these viruses in Mali. We additionally calibrate the model with paired virus neutralization titers in the French West Indies, a region with known CHIKV circulation but no ONNV. In Mali, the model estimate of ONNV and CHIKV prevalence is 30% and 13%, respectively, versus 27% and 2% in non-adjusted estimates. While a CHIKV infection induces an ONNV response in 80% of cases, an ONNV infection leads to a cross-reactive CHIKV response in only 22% of cases. Our study shows the importance of conducting serological assays on multiple cross-reactive pathogens to estimate levels of virus circulation., O’nyong nyong and Chikungunya virus are arboviruses present in Africa but their prevalence is unknown, partly due to high antibody cross-reactivity with one another. Here, the authors develop a statistical model that accounts for cross-reactivity to characterise circulation of both viruses from seroprevalence surveys.
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- 2021
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41. Impact of booster vaccination on the control of COVID-19 in the context of waning immunity: Application to France in the autumn-winter 2021-2022
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Bosetti, Paolo, Tran Kiem, Cécile, Andronico, Alessio, Paireau, Juliette, Levy-Bruhl, Daniel, ALTER, Lise, Fontanet, Arnaud, Cauchemez, Simon, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Collège doctoral [Sorbonne universités], Sorbonne Université (SU), Santé publique France - French National Public Health Agency [Saint-Maurice, France], Haute Autorité de Santé [Saint-Denis La Plaine] (HAS), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Conservatoire National des Arts et Métiers [CNAM] (CNAM), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), HAS, Santé Publique France, the EMERGEN project (ANRS0151), the INCEPTION project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grant 101003589 (RECOVER) and 874735 (VEO), AXA and Groupama., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), European Project: 874735,VEO, Noel, Anne-Laure, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Rapid European COVID-19 Emergency Response research - RECOVER - - H2020-SC1-PHE-CORONAVIRUS-20202020-02-14 - 2022-02-13 - 101003589 - VALID, Versatile Emerging infectious disease Observatory - VEO - - H2020-SC1-2019-Single-Stage-RTD2020-01-01 - 2024-12-31 - 874735 - VALID, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Université Paris Cité (UPCité)-Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), and European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020)
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[SDV] Life Sciences [q-bio] ,[SDV]Life Sciences [q-bio] - Abstract
Europe is confronted with a large COVID-19 wave caused by the Delta variant in autumnwinter 2021-2022. Using a mathematical model applied to Metropolitan France, we find that the hospitalisation peak might be reduced by 25%, 36% and 43% if boosters are administered to those aged 65+, 50+ or 18+, respectively, with a delay of 5 months between the second and third dose. Ten percent reduction in transmission rates might further reduce peak size by 41%, indicating that even small increases in protective behaviours may play a critical role to mitigate the wave.Most European countries have experienced an important rise in SARS-CoV-2 infections and hospitalisations in the Autumn 2021. In response to this resurgence and to the reported partial decay of immunity, countries have started administering vaccine booster doses, relying on different eligibility criteria. Here, we present modelling analyses assessing different administration strategies for booster doses that informed the recommendations of the French National Immunization Technical Advisory Group (Haute Autorité de Santé) in the context of Metropolitan France.
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- 2021
42. Selection for infectivity profiles in slow and fast epidemics, and the rise of SARS-CoV-2 variants
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François Blanquart, Nathanaël Hozé, Benjamin J. Cowling, Florence Débarre, Simon Cauchemez, Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), The University of Hong Kong (HKU), Hong Kong Science and Technology Parks Corporation (HKSTP), Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris ), Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), FB was funded by a Momentum grant from CNRS., Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), and Blanquart, François
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General Immunology and Microbiology ,Coinfection ,SARS-CoV-2 ,General Neuroscience ,[SDV]Life Sciences [q-bio] ,evolutionary biology ,global health ,COVID-19 ,General Medicine ,adaptation ,variants of concern ,General Biochemistry, Genetics and Molecular Biology ,[SDV] Life Sciences [q-bio] ,Humans ,epidemiology ,viruses ,Pandemics - Abstract
Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary infections (transmissibility advantage) or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the transmissibility advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate impact. Here we develop an analytical framework to investigate the contribution of both the transmissibility advantage and generation time to the growth advantage of a variant. We find that the growth advantage depends on the epidemiological context (level of epidemic control). More specifically, variants conferring earlier transmission are more strongly favoured when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favoured when historical strains have slow or negative growth. We develop these conceptual insights into a statistical framework to infer both the transmissibility advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a +54% [95% CI, 45-63%] transmissibility advantage compared to previous strains, and Delta +140% [98-182%] compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency and will strengthen risk assessment for future variants of concern.
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- 2021
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43. Seroprevalence of anti-SARS-CoV-2 IgG at the first epidemic peak in French Guiana, July 2020
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Anais Perilhou, Elodie Boizon, Dominique Rousset, Nathalie Clement, Antoine Enfissi, Véronique Servas, Didier Musso, Thierry Carage, Félix Djossou, Céline Michaud, E. Beillard, Christelle Alves Sarmento, Stephanie Eustache, Sarah Bailly, Simon Cauchemez, Jean-François Carod, Samantha James, Mélanie Gaillet, Claude Flamand, Henrik Salje, Celine Tourbillon, Institut Pasteur de la Guyane, Réseau International des Instituts Pasteur (RIIP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Centre de Recherche Translationnelle - Center for Translational Science (CRT), Institut Pasteur [Paris], Laboratoire d'Analyses Médicales [Kourou], Eurofins Labazur, Vecteurs - Infections tropicales et méditerranéennes (VITROME), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut de Recherche Biomédicale des Armées (IRBA), Centre Hospitalier de l'Ouest Guyanais Franck Joly [Saint-Laurent-du-Maroni, Guyane Française], Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of Cambridge [UK] (CAM), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), This study was supported by the National Research Agency to CF, the 'European Regional Development Fund' (GY0027257) to CF, the 'Regional Health Agency of French Guiana' to CF and the « URGENCE COVID-19 » fundraising campaign of Institut Pasteur to CF., Unité d'Epidémiologie [Cayenne, Guyane française], Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire de virologie [Cayenne, Guyane française], Laboratoire de biologie médicale [Cayenne, Guyane française] (LBM), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut de Recherche Biomédicale des Armées [Brétigny-sur-Orge] (IRBA), This study was supported by the National Research Agency to CF, the 'European Regional Development Fund' (GY0027257) to CF, the 'Regional Health Agency of French Guiana' to CF and the « URGENCE COVID-19 » fundraising campaign of Institut Pasteur to CF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript, We are grateful to all field workers, collaborators, technical and medical staff from Health Centers Department of Cayenne Hospital Center and biological laboratories and health centers involved in the EPI-COVID-19 project. We thank Bhety LABEAU, David MOUA, Laetitia BREMAND, Sylvie ALOEPOE, Elisabeth CHAN from Institut Pasteur in French Guiana, Nathalie JOLLY from Clinical Core of the Center for Translational Research of Institut Pasteur. We also thank Sophie GAULIN, Lysiane ROMAIN, Véronique TOGNERI and Tadens MPWENE from La Liberté., ANR-20-COVI-0014,EPI-COVID-19,Étude de la transmission intra-ménage autour des cas confirmés de COVID-19 en Guyane(2020), Flamand, Claude [0000-0002-8064-445X], Beillard, Emmanuel [0000-0002-2546-7614], Michaud, Céline [0000-0001-5410-6298], Cauchemez, Simon [0000-0001-9186-4549], Apollo - University of Cambridge Repository, and Salje, Henrik [0000-0003-3626-4254]
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RNA viruses ,Viral Diseases ,Pulmonology ,Coronaviruses ,Physiology ,RC955-962 ,030204 cardiovascular system & hematology ,Antibodies, Viral ,Serology ,MESH: Aged, 80 and over ,Medical Conditions ,0302 clinical medicine ,Seroepidemiologic Studies ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Arctic medicine. Tropical medicine ,MESH: Child ,Pandemic ,MESH: COVID-19 ,Medicine ,030212 general & internal medicine ,[MATH]Mathematics [math] ,Enzyme-Linked Immunoassays ,Child ,Pathology and laboratory medicine ,Virus Testing ,MESH: Immunoglobulin G ,MESH: Aged ,Aged, 80 and over ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,MESH: Middle Aged ,Medical microbiology ,Middle Aged ,MESH: Infant ,French Guiana ,3. Good health ,Bioassays and Physiological Analysis ,Infectious Diseases ,Physiological Parameters ,MESH: Young Adult ,Child, Preschool ,Viruses ,Public aspects of medicine ,RA1-1270 ,SARS CoV 2 ,Pathogens ,Research Article ,Adult ,SARS coronavirus ,Adolescent ,Coronavirus disease 2019 (COVID-19) ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Research and Analysis Methods ,Microbiology ,Respiratory Disorders ,Young Adult ,03 medical and health sciences ,MESH: Cross-Sectional Studies ,Diagnostic Medicine ,MESH: French Guiana ,Humans ,Seroprevalence ,MESH: SARS-CoV-2 ,Immunoassays ,Enzyme Assays ,Aged ,MESH: Adolescent ,Medicine and health sciences ,MESH: Humans ,MESH: Seroepidemiologic Studies ,Routine screening ,Biology and life sciences ,SARS-CoV-2 ,business.industry ,MESH: Child, Preschool ,Body Weight ,Organisms ,Viral pathogens ,Public Health, Environmental and Occupational Health ,COVID-19 ,Infant ,Spike Protein ,MESH: Adult ,Covid 19 ,Microbial pathogens ,Cross-Sectional Studies ,Young population ,Immunoglobulin G ,Respiratory Infections ,Immunologic Techniques ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Biochemical Analysis ,business ,MESH: Antibodies, Viral ,Demography - Abstract
Background While Latin America has been heavily affected by the pandemic, only a few seroprevalence studies have been conducted there during the first epidemic wave in the first half of 2020. Methodology/Principal findings A cross-sectional survey was performed between 15 July 2020 and 23 July 2020 among individuals who visited 4 medical laboratories or 5 health centers for routine screening or clinical management, with the exception of symptomatic suggestive cases of covid-19. Samples were screened for the presence of anti-SARS-CoV-2 IgG directed against domain S1 of the SARS-CoV-2 spike protein using the anti-SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) from Euroimmun. Conclusions/Significance The overall seroprevalence was 15.4% [9.3%-24.4%] among 480 participants, ranging from 4.0% to 25.5% across the different municipalities. The seroprevalence did not differ according to gender (p = 0.19) or age (p = 0.51). Among SARS-CoV-2 positive individuals, we found that 24.6% [11.5%-45.2%] reported symptoms consistent with COVID-19. Our findings revealed high levels of infection across the territory but a low number of resulting deaths, which can be explained by French Guiana’s young population structure., Author summary While Latin America has been heavily affected by the pandemic, only a few seroprevalence studies have been conducted there during the first epidemic wave in the first half of 2020. A cross-sectional survey was performed between 15 July 2020 and 23 July 2020 among individuals who visited 4 medical laboratories or 5 health centers for routine screening or clinical management, with the exception of symptomatic suggestive cases of covid-19. Samples were screened for the presence of anti-SARS-CoV-2 IgG using the anti-SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) from Euroimmun. The overall seroprevalence was 15.4% [9.3%-24.4%] among 480 participants, ranging from 4.0% to 25.5% across the different municipalities. The seroprevalence did not differ according to gender (p = 0.19) or age (p = 0.51). Among SARS-CoV-2 positive individuals, we found that 24.6% [11.5%-45.2%] reported symptoms consistent with COVID-19. Our findings revealed high levels of infection across the territory but a low number of resulting deaths, which can be explained by French Guiana’s young population structure.
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- 2021
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44. Using secondary cases to characterize the severity of an emerging or re-emerging infection
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Can Wang, Benjamin J. Cowling, Bingyi Yang, Tim K. Tsang, Simon Cauchemez, Li Kashing Faculty of Medicine, The University of Hong Kong (HKU), Hong Kong Science and Technology Parks Corporation (HKSTP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This project was supported by the Health and Medical Research Fund, Food and Health Bureau, Government of the Hong Kong Special Administrative Region (grant no. COVID190118, B.J.C.) and the Collaborative Research Fund (Project No. C7123-20G, B.J.C.) of the Research Grants Council of the Hong Kong SAR Government. BJC is supported by the AIR@innoHK program of the Innovation and Technology Commission of the Hong Kong SAR Government., and Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)
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Index (economics) ,Statistical methods ,Epidemiology ,General Physics and Astronomy ,Disease ,MESH: Hospitalization ,Severity of Illness Index ,0302 clinical medicine ,Credible interval ,MESH: COVID-19 ,030212 general & internal medicine ,050207 economics ,[MATH]Mathematics [math] ,Sampling bias ,0303 health sciences ,050208 finance ,Multidisciplinary ,05 social sciences ,MESH: China ,3. Good health ,Hospitalization ,Emerging infectious disease ,medicine.symptom ,China ,medicine.medical_specialty ,Coronavirus disease 2019 (COVID-19) ,Science ,MEDLINE ,macromolecular substances ,Asymptomatic ,Article ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,Disease severity ,MESH: Severity of Illness Index ,Internal medicine ,0502 economics and business ,Severity of illness ,medicine ,Humans ,030304 developmental biology ,Models, Statistical ,MESH: Humans ,SARS-CoV-2 ,business.industry ,COVID-19 ,General Chemistry ,medicine.disease ,Risk factors ,Middle East respiratory syndrome ,business ,MESH: Models, Statistical ,Contact tracing ,Demography - Abstract
The methods to ascertain cases of an emerging infectious disease are typically biased toward cases with more severe disease, which can bias the average infection-severity profile. Here, we conducted a systematic review to extract information on disease severity among index cases and secondary cases identified by contact tracing of index cases for COVID-19. We identified 38 studies to extract information on measures of clinical severity. The proportion of index cases with fever was 43% higher than for secondary cases. The proportion of symptomatic, hospitalized, and fatal illnesses among index cases were 12%, 126%, and 179% higher than for secondary cases, respectively. We developed a statistical model to utilize the severity difference, and estimate 55% of index cases were missed in Wuhan, China. Information on disease severity in secondary cases should be less susceptible to ascertainment bias and could inform estimates of disease severity and the proportion of missed index cases., Estimates of the severity of emerging infections did not consider the case ascertainment method, but secondary cases identified by contact tracing of index cases may be more reliable as they are less susceptible to ascertainment bias. Here, the authors perform a systematic review to quantify these differences and model their impacts for COVID-19.
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- 2021
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45. Reconstructing antibody dynamics to estimate the risk of influenza virus infection
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Vicky J. Fang, Gabriel M. Leung, Ranawaka A.P.M. Perera, Benjamin J. Cowling, Malik Peiris, Tim K. Tsang, Dennis K. M. Ip, Simon Cauchemez, Jessica Y. Wong, Hau Chi So, Eunice Shiu, The University of Hong Kong (HKU), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This study was supported by the Research Fund for the Control of Infectious Diseases of the Health, Welfare and Food Bureau of the Hong Kong SAR Government (grant CHP-CE-03), the Theme-based Research Scheme project no. T11-712/19N from the Hong Kong Government to B.J.C., the Health and Medical Research Fund, Food and Health Bureau, Government of the Hong Kong Special Administrative Region (grant no. 20190542) to T.K.T., and the Laboratory of Excellence Integrative Biology of Emerging Infectious Diseases (research funding to S.C.), AXA Research Fund and the European Union’s Horizon 2020 research and innovation program under VEO grant agreement No. 874735 to S.C., and European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020)
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Adult ,Multidisciplinary ,biology ,[SDV]Life Sciences [q-bio] ,Dynamics (mechanics) ,General Physics and Astronomy ,Bayes Theorem ,General Chemistry ,Hemagglutination Inhibition Tests ,Antibodies, Viral ,Orthomyxoviridae ,Virology ,Communicable Diseases ,Virus ,General Biochemistry, Genetics and Molecular Biology ,Influenza Vaccines ,Influenza, Human ,biology.protein ,Humans ,Disease Susceptibility ,Antibody ,Child - Abstract
For >70 years, a 4-fold or greater rise in antibody titer has been used to confirm influenza virus infections in paired sera, despite recognition that this heuristic can lack sensitivity. Here we analyze with a novel Bayesian model a large cohort of 2,353 individuals followed for up to 5 years in Hong Kong to characterize influenza antibody dynamics and develop an algorithm to improve the identification of influenza virus infections. After infection, we estimate that hemagglutination-inhibiting (HAI) titers were boosted by 16-fold on average and subsequently decrease by 14% per year. Greater boosting in HAI titer is observed in epidemics with a circulating strain that is different from the previous epidemic. In six epidemics, the infection risks for adults were 3%-19% while the infection risks for children were 1.6-4.4 times higher than that of younger adults. Every two-fold increase in pre-epidemic HAI titer was associated with 19%-58% protection against infection. Among the 1731 infections inferred by our model, around half were missed by the 4-fold rise criteria, suggesting that this criteria underestimates infection risks by 23-70%. The sensitivity and specificity of identifying infections for our approach are 87% (95% CrI: 85%, 89%) and 98% (95% CrI: 97%, 98%) respectively, which are higher than 82% (95% CrI: 80%, 84%) and 96% (95% CrI: 96%, 97%) for using 4-fold rise criteria. Our inferential framework clarifies the contributions of age and pre-epidemic HAI titers to characterize individual infection risk and offers an improved algorithm to identify influenza virus infections.
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- 2021
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46. SARS-CoV-2 transmission across age groups in France and implications for control
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Tran Kiem, Cécile, Bosetti, Paolo, Paireau, Juliette, Crepey, Pascal, Salje, Henrik, Lefrancq, Noémie, Fontanet, Arnaud, Benamouzig, Daniel, Boëlle, Pierre-Yves, Desenclos, Jean-Claude, Opatowski, Lulla, Cauchemez, Simon, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Sorbonne Université (SU), Santé publique France - French National Public Health Agency [Saint-Maurice, France], Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), École des Hautes Études en Santé Publique [EHESP] (EHESP), Département Méthodes quantitatives en santé publique (METIS), University of Cambridge [UK] (CAM), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Université Paris Cité (UPCité)-Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité), Centre de sociologie des organisations (Sciences Po, CNRS) (CSO), Sciences Po (Sciences Po)-Centre National de la Recherche Scientifique (CNRS), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Epidémiologie et modélisation de la résistance aux antimicrobiens - Epidemiology and modelling of bacterial escape to antimicrobials (EMAE), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), Santé Publique France, the 101003589 project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grant 101003589 (RECOVER), AXA and Institut Pasteur., ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), Université Paris Cité (UPCité), Université de Versailles Saint-Quentin-en-Yvelines - UFR Sciences de la santé Simone Veil (UVSQ Santé), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), Santé Publique France, the INCEPTION project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grant 101003589 (RECOVER) and 874735 (VEO), AXA, and Groupama., Tran Kiem, Cécile [0000-0003-0563-8428], Paireau, Juliette [0000-0002-5143-6256], Crépey, Pascal [0000-0003-1852-0752], Salje, Henrik [0000-0003-3626-4254], Lefrancq, Noemie [0000-0001-5991-6169], Desenclos, Jean-Claude [0000-0003-0892-8252], Cauchemez, Simon [0000-0001-9186-4549], Apollo - University of Cambridge Repository, Lassailly-Bondaz, Anne, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Rapid European COVID-19 Emergency Response research - RECOVER - - H2020-SC1-PHE-CORONAVIRUS-20202020-02-14 - 2022-02-13 - 101003589 - VALID, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Collège doctoral [Sorbonne universités], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Centre de sociologie des organisations (CSO), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pasteur [Paris], Sorbonne Université, Pasteur-Cnam risques infectieux et émergents (PACRI), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris], Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris], Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay-Hôpital Paul Brousse, Jonchère, Laurent, and Lefrancq, Noémie [0000-0001-5991-6169]
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Adult ,Male ,141 ,COVID-19 Vaccines ,Adolescent ,Statistical methods ,Epidemiology ,Science ,[SDV]Life Sciences [q-bio] ,Physical Distancing ,Young Adult ,631/114/2397 ,Humans ,Computational models ,Transmission ,Computer Simulation ,692/308/174 ,129 ,Child ,Pandemics ,631/326/596/4130 ,Aged ,Aged, 80 and over ,SARS-CoV-2 ,Age Factors ,Infant, Newborn ,article ,COVID-19 ,Infant ,Middle Aged ,631/114/2415 ,Hospitalization ,[SDV] Life Sciences [q-bio] ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,Child, Preschool ,Female ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,France ,SARS - CoV-2 - Abstract
The shielding of older individuals has been proposed to limit COVID-19 hospitalizations while relaxing general social distancing in the absence of vaccines. Evaluating such approaches requires a deep understanding of transmission dynamics across ages. Here, we use detailed age-specific case and hospitalization data to model the rebound in the French epidemic in summer 2020, characterize age-specific transmission dynamics and critically evaluate different age-targeted intervention measures in the absence of vaccines. We find that while the rebound started in young adults, it reached individuals aged ≥80 y.o. after 4 weeks, despite substantial contact reductions, indicating substantial transmission flows across ages. We derive the contribution of each age group to transmission. While shielding older individuals reduces mortality, it is insufficient to allow major relaxations of social distancing. When the epidemic remains manageable (R close to 1), targeting those most contributing to transmission is better than shielding at-risk individuals. Pandemic control requires an effort from all age groups., In this study, Tran Kiem et al. examine the contribution of different age groups to COVID-19 transmission. Using data from the French epidemic in summer 2020, they report that while individuals aged 80 years and older are more at risk, pandemic control in the absence of vaccines required measures targeted at all age groups.
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- 2021
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47. Transmission dynamics of Q fever in French Guiana: A population-based cross-sectional study
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Sarah Bailly, Nathanaël Hozé, Sylvie Bisser, Aurélien Zhu-Soubise, Camille Fritzell, Sandrine Fernandes-Pellerin, Adija Mbouangoro, Dominique Rousset, Félix Djossou, Simon Cauchemez, Claude Flamand, Institut Pasteur de la Guyane, Réseau International des Instituts Pasteur (RIIP), Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Institut Pasteur [Paris] (IP), Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], and This study was supported by the 'European Regional Development Fund' under EPI-ARBO grant agreement (GY0008695), the 'Regional Health Agency of French Guiana' and the 'National Center of Spatial Studies'.
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[STAT.AP]Statistics [stat]/Applications [stat.AP] ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Health Policy ,Public Health, Environmental and Occupational Health ,Internal Medicine ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie - Abstract
International audience; Background: Q fever is a zoonosis caused by Coxiella burnetii which is among the major agents of community-acquired pneumonia in French Guiana. Despite its relatively high incidence, its epidemiology in French Guiana remains unclear, and all previous studies have considered transmission from livestock unlikely, suggesting that a wild reservoir is responsible for transmission.Methods: A country-wide seroprevalence survey of 2697 participants from French Guiana was conducted. Serum samples were tested for phase II IgG antibodies by ELISA and indirect immunofluorescence assays (IFAs). Factors associated with Q fever were investigated, and a serocatalytic model was used to reconstruct the annual force of infection.Findings: The overall weighted seroprevalence was estimated at 9.6% (95% confidence interval (CI): 8.2%–11.0%). The model revealed constant, low-level circulation across French Guiana, particularly affecting middle-aged males (odds ratio (OR): 3.0, 95% credible interval (CrI): 1.7–5.8) and individuals living close to sheep farms (OR: 4, 95% CrI: 1.5–12). The overall annual number of cases was estimated at 579 (95% CrI: 492–670). In the region around Cayenne, the main urban municipality, the high seroprevalence was explained by an outbreak that may have occurred between 1996 and 2003 and that infected 10% (95% CrI: 6.9%–14%) of the population and males and females alike.Interpretation: This study reveals for the first time Q fever dynamics of transmission and the role of domestic livestock in transmission in French Guiana and highlights the urgent need to reinforce Q fever surveillance in livestocks of the entire Guianese territory.
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- 2022
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48. Epidemiology and control of SARS-CoV-2 epidemics in partially vaccinated populations: a modeling study applied to France
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Paolo Bosetti, Cécile Tran Kiem, Alessio Andronico, Vittoria Colizza, Yazdan Yazdanpanah, Arnaud Fontanet, Daniel Benamouzig, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Collège doctoral [Sorbonne universités], Sorbonne Université (SU), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Université Sorbonne Paris Nord, Services de Maladies Infectieuses et Tropicales [CHU Bichat], AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Centre de sociologie des organisations (CSO), Sciences Po (Sciences Po)-Centre National de la Recherche Scientifique (CNRS), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), HAS, Santé Publique France, the INCEPTION project(PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grant 101003589 (RECOVER) and 874735 (VEO), AXA and Groupama., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), European Project: 101003589, H2020-SC1-PHE-CORONAVIRUS-2020,RECOVER(2020), European Project: 874735,VEO, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège Doctoral, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Paris Cité (UPCité)-Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité), Centre de sociologie des organisations (Sciences Po, CNRS) (CSO), We acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (grant ANR-10-LABX-62-IBEID), HAS, Santé Publique France, the EMERGEN project (ANRS0151), the INCEPTION project (PIA/ANR-16-CONV-0005), the European Union’s Horizon 2020 research and innovation program under grant 101003589 (RECOVER) and 874735 (VEO), AXA and Groupama., European Project: 874735,H2020-SC1-2019-Single-Stage-RTD,VEO(2020), Sorbonne Université, Pasteur-Cnam risques infectieux et émergents (PACRI), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris], Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut Pasteur [Paris], ANR-10-LABX-0062,IBEID,Biologie Intégrative des Maladies Infectieuses Emergentes(2011), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Cité (UPCité)-Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Benamouzig, Daniel, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID, Rapid European COVID-19 Emergency Response research - RECOVER - - H2020-SC1-PHE-CORONAVIRUS-20202020-02-14 - 2022-02-13 - 101003589 - VALID, and Versatile Emerging infectious disease Observatory - VEO - - H2020-SC1-2019-Single-Stage-RTD2020-01-01 - 2024-12-31 - 874735 - VALID
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Adult ,COVID-19 Vaccines ,Adolescent ,[SDV]Life Sciences [q-bio] ,[SHS]Humanities and Social Sciences ,03 medical and health sciences ,0302 clinical medicine ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Humans ,030212 general & internal medicine ,Child ,Epidemics ,030304 developmental biology ,0303 health sciences ,SARS-CoV-2 ,Non-pharmaceutical interventions ,Vaccination ,Infant, Newborn ,COVID-19 ,Infant ,General Medicine ,Middle Aged ,3. Good health ,[SDV] Life Sciences [q-bio] ,Child, Preschool ,Medicine ,Epidemiological Models ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,[SHS] Humanities and Social Sciences ,France ,Research Article - Abstract
Background Vaccination is expected to change the epidemiology and management of SARS-CoV-2 epidemics. Methods We used an age-stratified compartmental model calibrated to French data to anticipate these changes and determine implications for the control of an autumn epidemic. We assumed vaccines reduce the risk of hospitalization, infection, and transmission if infected by 95%, 60%, and 50%, respectively. Results In our baseline scenario characterized by basic reproduction number R0=5 and a vaccine coverage of 70–80–90% among 12–17, 18–59, and ≥ 60 years old, important stress on healthcare is expected in the absence of measures. Unvaccinated adults ≥60 years old represent 3% of the population but 43% of hospitalizations. Given limited vaccine coverage, children aged 0–17 years old represent a third of infections and are responsible for almost half of transmissions. Unvaccinated individuals have a disproportionate contribution to transmission so that measures targeting them may help maximize epidemic control while minimizing costs for society compared to non-targeted approaches. Of all the interventions considered including repeated testing and non-pharmaceutical measures, vaccination of the unvaccinated is the most effective. Conclusions With the Delta variant, vaccinated individuals are well protected against hospitalization but remain at risk of infection and should therefore apply protective behaviors (e.g., mask-wearing). Targeting non-vaccinated individuals may maximize epidemic control while minimizing costs for society. Vaccinating children protects them from the deleterious effects of non-pharmaceutical measures. Control strategies should account for the changing SARS-CoV-2 epidemiology.
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- 2021
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49. Ecology, evolution, and epidemiology of zoonotic and vector-borne infectious diseases in French Guiana: Transdisciplinarity does matter to tackle new emerging threats
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Anne Lavergne, Marine Ginouves, Florian Binetruy, Claude Flamand, Mathieu Nacher, Emmanuel Roux, Roxane Schaub, Sébastien Gourbière, Benoit de Thoisy, Pierre Couppié, Arthur Kocher, Lise Musset, Philippe Quénel, Sourakhata Tirera, Luisiane Carvalho, Jérôme Murienne, Sébastien Briolant, Magalie Demar, Yanouk Epelboin, Ghislaine Prévot, Olivier Duron, Isabelle Dusfour, Benjamin Roche, Maylis Douine, Stéphane Pelleau, Luana Mathieu, Agathe Chavy, Loïc Epelboin, Alain Franc, Paul Le Turnier, Pauline Thill, Jean-François Guégan, Emeline Houël, Dominique Rousset, Stanislas Talaga, Laboratoire des Interactions Virus-Hôtes [Cayenne, Guyane Française], Institut Pasteur de la Guyane, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Réseau International des Instituts Pasteur (RIIP), Centre de Recherche en Ecologie et Evolution de la Santé (CREES), Institut de Recherche pour le Développement (IRD)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Centre National de Référence du Paludisme [Cayenne, Guyane française] (CNR - laboratoire associé), Centre Collaborateur OMS pour la surveillance de la résistance aux antipaludiques [Cayenne, Guyane française] (CCOMS), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), Laboratoire de Parasitologie [Cayenne, Guyane française], Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), École des Hautes Études en Santé Publique [EHESP] (EHESP), Centre de Recherches Ecologiques et Evolutives sur le Cancer (MIVEGEC-CREEC), Processus Écologiques et Évolutifs au sein des Communautés (PEEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Vecteurs - Infections tropicales et méditerranéennes (VITROME), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut de Recherche Biomédicale des Armées [Brétigny-sur-Orge] (IRBA), Institut de Recherche Biomédicale des Armées [Antenne Marseille] (IRBA), Santé publique France Guyane, Santé publique France - French National Public Health Agency [Saint-Maurice, France], Université de Guyane (UG), Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), Centre d'investigation clinique Antilles-Guyane (CIC - Antilles Guyane), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -CHU de la Martinique [Fort de France]-Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Département de Santé Globale - Department Global Health, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Laboratoire Génome et développement des plantes (LGDP), Université de Perpignan Via Domitia (UPVD)-Centre National de la Recherche Scientifique (CNRS), Vectopôle Amazonien Emile Abonnenc [Cayenne, Guyane française], Unité d'Epidémiologie [Cayenne, Guyane française], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), from patterns to models in computational biodiversity and biotechnology (PLEIADE), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biome Tropical et Immuno-Pathophysiologie = Tropical Biome and ImmunoPhysiopathology [Lille] (TBIP), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS)-Université de Guyane (UG), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Max Planck Institute for the Science of Human History (MPI-SHH), Max-Planck-Gesellschaft, Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Centre d’Investigation Clinique de Nantes (CIC Nantes), Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre hospitalier universitaire de Nantes (CHU Nantes), Centre hospitalier universitaire de Nantes (CHU Nantes), Malaria : parasites et hôtes - Malaria : parasites and hosts, Institut Pasteur [Paris] (IP), UMR 228 Espace-Dev, Espace pour le développement, Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Université de Guyane (UG)-Université des Antilles (UA), LMI Sentinela [Rio de Janeiro], Institut de Recherche pour le Développement (IRD)-Universidade de Brasilia [Brasília] (UnB)-Fundação Oswaldo Cruz / Oswaldo Cruz Foundation (FIOCRUZ), Service Universitaire des Maladies Infectieuses et du Voyageur [Tourcoing], Centre Hospitalier Tourcoing, Centre Hospitalier Gustave Dron [Tourcoing], Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), This work has benefited from three 'Investissement d’Avenir' grants managed by Agence Nationale de la Recherche (CEBA: ANR-10-LABX-25-01, TULIP: ANR-10-LABX-0041, DRIIHM: ANR-11-LABX-0010). The two lead coauthors received European funding through the European Regional Development Fund Operational Program FEDER RESERVOIRS Project (BdT) and a US NSF-NIH (NSF#1911457) Ecology of infectious diseases award (J-FG). J-FG is also supported by IRD, INRAE, and Université of Montpellier. OD thanks l’Office français de la biodiversité, le Groupe d'Étude et de Protection des Oiseaux en Guyane (GEPOG), la Direction de l'Alimentation, de l'Agriculture et de la Forêt de Guyane (DAAF). AL acknowledges European funding through the European Regional Development Fund Operational Program FEDER RESERVOIRS, CAROLLIA, EFAG and VIRUSES projects. LM is supported by European funding through the European Regional Development Fund Operational Program FEDER ELIMALAR project and Santé publique France as the National Reference Center for Malaria. PQ thanks Publique France/Cire Guyane, CNR sur les arboviroses, CNR du paludisme. EH and ID acknowledge European funding through the European Regional Development Fund Operational Program FEDER CONTROLE Projet, the French Guiana Regional Council and the Air Liquide Foundation. SB is supported by the French Army (Grant LR607e). ER is grateful for European funding through the European Regional Development Fund Operational Program FEDER OSE-Guyamapa project, the French Embassy in Brazil, the Guyamazon program ('GAPAM-Sentinela' project), CNES, and the Bill and Melinda Gates Foundation., ANR-10-LABX-0025,CEBA,CEnter of the study of Biodiversity in Amazonia(2010), ANR-10-LABX-0041,TULIP,Towards a Unified theory of biotic Interactions: the roLe of environmental(2010), ANR-11-LABX-0010,DRIIHM / IRDHEI,Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux(2011), Génétique et évolution des maladies infectieuses (GEMI), Centre National de Référence du Paludisme [Cayenne, Guyane française] (CNR), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Génétique et évolution des maladies infectieuses (GEMI), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut de Recherche Biomédicale des Armées (IRBA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Universidade de Brasilia [Brasília] (UnB)-Fundação Oswaldo Cruz (FIOCRUZ), Dusfour, Isabelle, Laboratoires d'excellence - CEnter of the study of Biodiversity in Amazonia - - CEBA2010 - ANR-10-LABX-0025 - LABX - VALID, Towards a Unified theory of biotic Interactions: the roLe of environmental - - TULIP2010 - ANR-10-LABX-0041 - LABX - VALID, Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux - - DRIIHM / IRDHEI2011 - ANR-11-LABX-0010 - LABX - VALID, Université d'Angers (UA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Centre National de la Recherche Scientifique (CNRS)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU de la Martinique [Fort de France]-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Institut Pasteur [Paris], Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Centre National de la Recherche Scientifique (CNRS)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Guyane (UG), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Santé et de la Recherche Médicale (INSERM)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université d'Angers (UA)
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0301 basic medicine ,Microbiology (medical) ,Emerging and reemerging infectious diseases ,Ecology (disciplines) ,media_common.quotation_subject ,[SDV]Life Sciences [q-bio] ,[SDE.MCG]Environmental Sciences/Global Changes ,030106 microbiology ,Immigration ,Interdisciplinary Research ,Wildlife ,Vector Borne Diseases ,Animals, Wild ,Anthropogenic pressures ,Biology ,Microbiology ,03 medical and health sciences ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Zoonoses ,Genetics ,Prevalence ,Animals ,Humans ,Human Activities ,Molecular Biology ,Epidemiologic transition ,Global change ,Ecology, Evolution, Behavior and Systematics ,Ecosystem ,media_common ,Demography ,[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases ,Resistance (ecology) ,Ecology ,Incidence ,Outbreak ,15. Life on land ,French Guiana ,[SDV] Life Sciences [q-bio] ,Epidemiological transition ,[SDE.MCG] Environmental Sciences/Global Changes ,030104 developmental biology ,Infectious Diseases ,Promiscuity ,Vector (epidemiology) ,[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases - Abstract
International audience; French Guiana is a European ultraperipheric region located on the northern Atlantic coast of South America. It constitutes an important forested region for biological conservation in the Neotropics. Although very sparsely populated, with its inhabitants mainly concentrated on the Atlantic coastal strip and along the two main rivers, it is marked by the presence and development of old and new epidemic disease outbreaks, both research and health priorities. In this review paper, we synthetize 15 years of multidisciplinary and integrative research at the interface between wildlife, ecosystem modification, human activities and sociodemographic development, and human health. This study reveals a complex epidemiological landscape marked by important transitional changes, facilitated by increased interconnections between wildlife, land-use change and human occupation and activity, human and trade transportation, demography with substantial immigration, and identified vector and parasite pharmacological resistance. Among other French Guianese characteristics, we demonstrate herein the existence of more complex multi-host disease life cycles than previously described for several disease systems in Central and South America, which clearly indicates that today the greater promiscuity between wildlife and humans due to demographic and economic pressures may offer novel settings for microbes and their hosts to circulate and spread. French Guiana is a microcosm that crystallizes all the current global environmental, demographic and socioeconomic change conditions, which may favor the development of ancient and future infectious diseases.
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- 2021
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- View/download PDF
50. Assessing the feasibility of Nipah vaccine efficacy trials based on previous outbreaks in Bangladesh
- Author
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Marc Lipsitch, Stephen P. Luby, Gabriel Ribeiro Dos Santos, Henrik Salje, Mahmudur Rahman, Emily S. Gurley, Birgit Nikolay, Simon Cauchemez, Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of Cambridge [UK] (CAM), Harvard T.H. Chan School of Public Health, Stanford University, Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), B. N. and S. C. acknowledge the support of the Laboratory of Excellence Integrative Biology of Emerging Infectious Diseases (Grant ANR-10-LABX-62-IBEID), the National Institute of General Medical Sciences Models of Infectious Disease Agent Study Initiative, the AXA Research Fund and the INCEPTION project (PIA/ANR-16-CONV-0005). B. N., E. G. and H. S. acknowledge the support of the Defense Advanced Research Projects Agency (Grant D18AC00031)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), and Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)
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medicine.medical_specialty ,030231 tropical medicine ,Context (language use) ,Nipah virus ,Disease cluster ,Disease Outbreaks ,03 medical and health sciences ,0302 clinical medicine ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,Epidemiology ,medicine ,Animals ,Humans ,030212 general & internal medicine ,030304 developmental biology ,0303 health sciences ,Bangladesh ,Vaccines ,General Veterinary ,General Immunology and Microbiology ,business.industry ,vaccine trial ,Clinical study design ,Public Health, Environmental and Occupational Health ,Vaccine trial ,Vaccine efficacy ,3. Good health ,Vaccination ,Infectious Diseases ,Case-Control Studies ,Emergency medicine ,Molecular Medicine ,Feasibility Studies ,Observational study ,Emerging pathogens ,business - Abstract
BackgroundNipah virus (NiV) is an emerging, bat-borne pathogen that can be transmitted from person-to-person. Vaccines are currently being developed for NiV, and studies funded to evaluate their safety and immunogenicity, so that they could possibly be used to contain outbreaks. An important unanswered question is whether it will be possible to evaluate the efficacy of vaccine candidates in phase III clinical trials in a context where spillovers from the zoonotic reservoir are infrequent and associated with small outbreaks. The objective of this study was to investigate the feasibility of conducting a phase III vaccine trial in Bangladesh, the only country reporting regularly NiV cases.MethodsWe used simulations based on previously observed NiV cases from Bangladesh, an assumed vaccine efficacy of 90% and other NiV vaccine target characteristics, to compare three vaccination study designs: (i) cluster randomized ring vaccination, (ii) cluster randomized mass vaccination, and (iii) an observational case-control study design.ResultsThe simulations showed that, assuming a ramp-up period of 10 days and a mean hospitalization delay of 4 days, it would take 516 years and over 163,000 vaccine doses to run a ring vaccination trial under current epidemic conditions. A cluster-randomized trial in the two most affected districts would take 81 years and 2.3 million vaccine doses. An observational case-control design in these two districts would require seven years and 2.5 million vaccine doses.DiscussionWithout a change in the epidemiology of NiV, ring vaccination or cluster-randomized trials are unlikely to be completed within a reasonable time window. In this light, the remaining options are: (i) not conducting a phase III trial until the epidemiology of NiV changes, (ii) identifying alternative ways to licensure such as observational studies or controlled studies in animals such as in the US Food and Drug Administration’s (FDA) Animal Rule.
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- 2021
- Full Text
- View/download PDF
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