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1. TiPS : Rapidly simulating trajectories and phylogenies from compartmental models

Author

Emma Saulnier, Marc Choisy, Olivier Gascuel, Gonché Danesh, Samuel Alizon, 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), Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), 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), and Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Theoretical computer science, Computer science, Population, Population genetics, computer.software_genre, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Set (abstract data type), Software, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, education, Ecology, Evolution, Behavior and Systematics, [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, education.field_of_study, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], business.industry, Ecological Modeling, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], Ode, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Gillespie algorithm, Simulation software, Viral phylodynamics, Ordinary differential equation, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business, computer, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

We introduce TiPS, an R package to generate trajectories and phylogenetic trees associated with a compartmental model. Trajectories are simulated using Gillespie’s exact or approximate stochastic simulation algorithm, or a newly-proposed mixed version of the two. Phylogenetic trees are simulated from a trajectory under a backwards-in-time approach (i.e. coalescent). TiPS is based on the Rcpp package, allowing to combine the flexibility of R for model definition and the speed of C++ for simulations execution. The model is defined in R with a set of reactions, which allow capturing heterogeneity in life cycles or any sort of population structure. TiPS converts the model into C++ code and compiles it into a simulator that is interfaced in R via a function. Furthermore, the package allows defining time periods in which the model’s parameters can take different values. This package is particularly well suited for population genetics and phylodynamics studies that need to generate a large number of phylogenies used for population dynamics studies. This package is available on the CRAN at https://cran.r-project.org/package=TiPS.

Published
2022
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2. Predicting COVID-19 incidence in French hospitals using human contact network analytics

Author

Christian Selinger, Marc Choisy, Samuel Alizon, 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]), Nuffield Department of Clinical Medicine [Oxford], University of Oxford, Institut de Recherche pour le Développement (IRD), 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), ANR-20-COVI-0098,PHYEPI,Intégration de données de séquences et d'incidence pour analyser et contrôler les épidémies virales(2020), Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford [Oxford], and Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU)

Subjects
Microbiology (medical), medicine.medical_specialty, Time series, Human mobility, Coronavirus disease 2019 (COVID-19), Computer science, Contact network, Infectious and parasitic diseases, RC109-216, 01 natural sciences, Proxy (climate), Article, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Epidemic spread, Statistics, medicine, Humans, 030212 general & internal medicine, 0101 mathematics, Cluster analysis, Epidemics, Infectious disease, business.industry, SARS-CoV-2, Public health, Incidence (epidemiology), Incidence, 010102 general mathematics, COVID-19, General Medicine, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Hospitals, 3. Good health, Infectious Diseases, Geography, Analytics, Mobile phone, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Networks, business
Abstract

Coronavirus disease (COVID-19) was detected in Wuhan, China in 2019 and spread worldwide within few weeks. The COVID-19 epidemic started to gain traction in France in March 2020. Sub-national hospital admissions and deaths were then recorded daily and served as the main policy indicators. Concurrently, mobile phone positioning data have been curated to determine the frequency of users being colocalized within a given distance. Contrarily to individual tracking data, these can provide a proxy of human contact networks between subnational administrative units. Motivated by numerous studies correlating human mobility data and disease incidence, we developed predictive time series models of hospital incidence between July 2020 and April 2021. Adding human contact network analytics such as clustering coefficients, contact network strength, null links or curvature as regressors, we found that predictions can be improved substantially (more than 50%) both at the national and sub-national for up to two weeks. Our sub-national analysis also revealed the importance of spatial structure, as incidence in colocalized administrative units improved predictions. This original application of network analytics from co-localisation data to epidemic spread opens new perspectives for epidemics forecasting and public health.HighlightsWe use novel human contact network analytics based on colocation data of mobile app users to follow the dynamics of disease incidence and interventions of COVID-19 in France.Time series predictions of hospital incidence are greatly improved by adding these analytics as regressors.Sub-national analysis highlights both spatial correlations of incidence and network analytics to obtain high-precision predictions.

Published
2021
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3. Human-vector malaria transmission model structured by age, time since infection and waning immunity

Author

Thierry Lefèvre, Marc Choisy, Ramsès Djidjou-Demasse, Quentin Richard, 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 for Tropical Medicine and Global Health [Oxford, UK], Nuffield Department of Medicine [Oxford, UK] (Big Data Institute), University of Oxford [Oxford]-University of Oxford [Oxford], Institut de Recherche pour le Développement (IRD), Transmission-Interactions-Adaptations hôtes/vecteurs/pathogènes (MIVEGEC-TRIAD), Evolution des Systèmes Vectoriels (ESV), 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]), University of Oxford-University of Oxford, and ANR-16-CE35-0007,STORM,Stratégies de transmission des parasites à vecteur : variation génétique, plasticité phénotypique et conséquences pour les mesures de contrôle(2016)

Subjects
Population, 01 natural sciences, law.invention, 03 medical and health sciences, Mathematics - Analysis of PDEs, Malaria transmission, Bifurcation analysis, law, Statistics, medicine, FOS: Mathematics, Vector-borne diseases, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], Waning immunity, 0101 mathematics, education, 030304 developmental biology, Mathematics, 0303 health sciences, education.field_of_study, Applied Mathematics, 010102 general mathematics, General Engineering, Age-structured model, General Medicine, medicine.disease, Expression (mathematics), Basic reproduction number, 3. Good health, Malaria, Computational Mathematics, Transmission (mechanics), Vector (epidemiology), [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, General Economics, Econometrics and Finance, Analysis, Analysis of PDEs (math.AP)
Abstract

International audience; In contrast to the many theoretical studies on the transmission of human-mosquitoes malaria infection, few studies have considered a multiple structure model formulations including (i) the chronological age of humans and mosquitoes population, (ii) the time since humans and mosquitoes are infected and (iii) humans waning immunity (i.e., the progressive loss of protective antibodies after recovery). Such structural variables are well documented to be fundamental for the transmission of human-mosquitoes malaria infections. Here we formulate an age-structured model accounting for the three structural variables. Using integrated semigroups theory, we first handle the well-posedness of the model proposed. We also investigate the existence of model's steady-states. A disease-free equilibrium always exists while the existence of endemic equilibria is discussed. We derive the threshold R0 (the basic reproduction number). The expression of the R0 obtained here particularly highlight the effect of above structural variables on key important epidemiological traits of the human-vector association. This includes, humans and mosquitoes transmission probability and survival rates. Next, we derive a necessary and sufficient condition that implies the bifurcation of an endemic equilibrium. In some configuration where the age-structure of the human population is neglected, we show that, depending on the sign of some constant Cbif given by the parameters, a bifurcation occurs at R0 = 1 that is either forward or backward. In the former case, it means that there exists a (unique) endemic equilibrium if and only if R0 > 1. In the latter case, no endemic equilibrium exists for R0<< 1 small enough, a unique exists if R0 > 1 while multiple endemic equilibria exist when 0 <

Published
2021
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4. Evolution of virulence in emerging epidemics: inference from an evolution experiment

Author

Thomas W. Berngruber, Sylvain Gandon, François Blanquart, Marc Choisy, 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), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
0106 biological sciences, 0303 health sciences, Experimental evolution, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], Inference, Virulence, Computational biology, Biology, 010603 evolutionary biology, 01 natural sciences, 3. Good health, 03 medical and health sciences, Infectious disease (medical specialty), 030304 developmental biology
Abstract

Inference using mathematical models of infectious disease dynamics is a powerful tool to analyse epidemiological data and elucidate pathogen life cycles. Key epidemiological parameters can be estimated from demographic time series by computing the likelihood of alternative models of pathogen transmission. Here we use this inference approach to analyze data from an evolution experiment in which we monitored both the epidemiology and the evolution of the temperate bacteriophage λ during an epidemic. We estimate parameter values for all the life-history traits of two distinct strains of the virus. In particular, we estimate the ability of the two virus strains to modulate plastically the rate of lysogenization with the multiplicity of infection. Our work illustrates how inference from experimental evolution data can feedback on the development of models aiming to predict the epidemiology and evolution of infectious diseases.

Published
2020

5. Does sunlight drive seasonality of TB in Vietnam? A retrospective environmental ecological study of tuberculosis seasonality in Vietnam from 2010 to 2015

Author

H. Rogier van Doorn, Richard G. White, Behzad Nadjm, Ana Bonell, Lucie Contamin, Marc Choisy, Hoang Thi Thanh Thuy, Pham Quang Thai, London School of Hygiene and Tropical Medicine (LSHTM), Oxford University Clinical Research Unit [Hanoi] (OUCRU), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), and Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])

Subjects
Adult, Male, medicine.medical_specialty, Meteorological, Tuberculosis, Adolescent, Climate, Population, Population density, lcsh:Infectious and parasitic diseases, 03 medical and health sciences, Young Adult, 0302 clinical medicine, medicine, Global health, Prevalence, Humans, lcsh:RC109-216, 030212 general & internal medicine, education, Aged, Retrospective Studies, 2. Zero hunger, 0303 health sciences, education.field_of_study, 030306 microbiology, Public health, Incidence (epidemiology), 1. No poverty, Ecological study, Seasonality, Middle Aged, medicine.disease, Sunshine, 3. Good health, Infectious Diseases, Geography, Socioeconomic Factors, Vietnam, Linear Models, Female, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Seasons, Demography, Research Article
Abstract

Background Tuberculosis (TB) is a major global health burden, with an estimated quarter of the world’s population being infected. The World Health Organization (WHO) launched the “End TB Strategy” in 2014 emphasising knowing the epidemic. WHO ranks Vietnam 12th in the world of high burden countries. TB spatial and temporal patterns have been observed globally with evidence of Vitamin D playing a role in seasonality. We explored the presence of temporal and spatial clustering of TB in Vietnam and their determinants to aid public health measures. Methods Data were collected by the National TB program of Vietnam from 2010 to 2015 and linked to the following datasets: socio-demographic characteristics; climatic variables; influenza-like-illness (ILI) incidence; geospatial data. The TB dataset was aggregated by province and quarter. Descriptive time series analyses using LOESS regression were completed per province to determine seasonality and trend. Harmonic regression was used to determine the amplitude of seasonality by province. A mixed-effect linear model was used with province and year as random effects and all other variables as fixed effects. Results There were 610,676 cases of TB notified between 2010 and 2015 in Vietnam. Heat maps of TB incidence per quarter per province showed substantial temporal and geospatial variation. Time series analysis demonstrated seasonality throughout the country, with peaks in spring/summer and troughs in autumn/winter. Incidence was consistently higher in the south, the three provinces with the highest incidence per 100,000 population were Tay Ninh, An Giang and Ho Chi Minh City. However, relative seasonal amplitude was more pronounced in the north. Mixed-effect linear model confirmed that TB incidence was associated with time and latitude. Of the demographic, socio-economic and health related variables, population density, percentage of those under 15 years of age, and HIV infection prevalence per province were associated with TB incidence. Of the climate variables, absolute humidity, average temperature and sunlight were associated with TB incidence. Conclusion Preventative public health measures should be focused in the south of Viet Nam where incidence is highest. Vitamin D is unlikely to be a strong driver of seasonality but supplementation may play a role in a package of interventions.

Published
2020
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6. An estimation of total antimicrobial usage in humans and animals in Vietnam

Author

Nguyen Van Cuong, Juan Carrique-Mas, Stephen Baker, Marc Choisy, Guy E. Thwaites, Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), 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]), Carrique-Mas, Juan J [0000-0001-9161-8890], and Apollo - University of Cambridge Repository

Subjects
Microbiology (medical), Swine, Veterinary medicine, 030231 tropical medicine, Population, Short Report, Aquaculture, lcsh:Infectious and parasitic diseases, Toxicology, 03 medical and health sciences, Drug Utilization Review, 0302 clinical medicine, Anti-Infective Agents, Surveys and Questionnaires, Human medicine, Animals, Humans, media_common.cataloged_instance, Medicine, lcsh:RC109-216, Pharmacology (medical), European Union Main text, 14. Life underwater, European Union, European union, education, Animal species, media_common, Animal use, 2. Zero hunger, Estimation, 0303 health sciences, education.field_of_study, Surveillance, 030306 microbiology, business.industry, Public Health, Environmental and Occupational Health, Antimicrobial, Antimicrobial use, Infectious Diseases, Vietnam, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, Chickens
Abstract

The accurate assessment of antimicrobial use (AMU) requires relating quantities of active ingredients (AAIs) with population denominators. These data can be used to prioritize potential sources of selective pressure for antimicrobial resistance and to establish reduction targets. Here, we estimated AMU in Vietnam (human population 93.4 M in 2015), and compared it with European Union (EU) data (population 511.5 M in 2014). We extrapolated AMU data on each key animal species and humans from different published sources to calculate overall AMU (in tonnes) in Vietnam. We then compared these data with published statistics on AMU in the European Union (EU). A total of 3838 t of antimicrobials were used in Vietnam, of which 2751 (71.7%) corresponded to animal use, and the remainder (1086 t; 28.3%) to human AMU. This equates to 261.7 mg and 247.3 mg per kg of human and animal biomass, compared with 122.0 mg and 151.5 mg in the EU. The greatest quantities of antimicrobials (in decreasing order) were used in pigs (41.7% of total use), humans (28.3%), aquaculture (21.9%) and chickens (4.8%). Combined AMU in other species accounted for

Published
2020
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7. Economic factors influencing zoonotic disease dynamics : demand for poultry meat and seasonal transmission of avian influenza in Vietnam

Author

Nicolas Antoine-Moussiaux, Dirk U. Pfeiffer, Thang D. Phan, Guillaume Fournié, Alexis Delabouglise, Ton Dinh Vu, Marc Choisy, Marie-Isabelle Peyre, Animal et gestion intégrée des risques (UPR AGIRs), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), 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]), Vietnam National University of Agriculture (VNUA), Institut Vétérinaire Tropical [Liège], Faculté de Médecine Vétérinaire [Liège], Royal Veterinary College [London], and University of London [London]

Subjects
0301 basic medicine, Time Factors, Climate, medicine.disease_cause, L73 - Maladies des animaux, Poultry, Disease Outbreaks, 0403 veterinary science, Zoonoses, Cluster Analysis, Socioeconomics, 2. Zero hunger, education.field_of_study, Multidisciplinary, grippe aviaire hautement pathogène, Geography, Ecology, U10 - Informatique, mathématiques et statistiques, Incidence, Incidence (epidemiology), Commerce agricole, 04 agricultural and veterinary sciences, Épidémiologie, Vietnam, Medicine, Livestock, Seasons, zoonose, Meat, 040301 veterinary sciences, Science, Population, E70 - Commerce, commercialisation et distribution, Wavelet Analysis, Article, 03 medical and health sciences, medicine, Animals, education, Consumption (economics), E21 - Agro-industrie, [SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, business.industry, Outbreak, Seasonality, medicine.disease, Influenza A virus subtype H5N1, 030104 developmental biology, Influenza in Birds, Poultry meat, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business
Abstract

While climate is often presented as a key factor influencing the seasonality of diseases, the importance of anthropogenic factors is less commonly evaluated. Using a combination of methods – wavelet analysis, economic analysis, statistical and disease transmission modelling – we aimed to explore the influence of climatic and economic factors on the seasonality of H5N1 Highly Pathogenic Avian Influenza in the domestic poultry population of Vietnam. We found that while climatic variables are associated with seasonal variation in the incidence of avian influenza outbreaks in the North of the country, this is not the case in the Centre and the South. In contrast, temporal patterns of H5N1 incidence are similar across these 3 regions: periods of high H5N1 incidence coincide with Lunar New Year festival, occurring in January-February, in the 3 climatic regions for 5 out of the 8 study years. Yet, daily poultry meat consumption drastically increases during Lunar New Year festival throughout the country. To meet this rise in demand, poultry production and trade are expected to peak around the festival period, promoting viral spread, which we demonstrated using a stochastic disease transmission model. This study illustrates the way in which economic factors may influence the dynamics of livestock pathogens.

Published
2017
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8. Hydrological Regime and Water Shortage as Drivers of the Seasonal Incidence of Diarrheal Diseases in a Tropical Montane Environment

Author

Laurie Boithias, Emma Rochelle-Newall, Sylvia Becerra, Chanthamousone Thammahacksa, Marc Choisy, Olivier Ribolzi, Norbert Silvera, Keooudone Latsachack, Fabrice Quet, Noy Souliyaseng, Alain Pierret, Oloth Sengtaheuanghoung, Yves Buisson, Marine Jourdren, Géosciences Environnement Toulouse (GET), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), Institut de la Francophonie pour la Médecine Tropicale (IFMT), Centre de Montpellier [IRSTEA], Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Department of Agricultural Land Management (DALaM), Institut d'écologie et des sciences de l'environnement de Paris (IEES), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Recherche Agronomique (INRA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Institut d'écologie et des sciences de l'environnement de Paris (iEES), Institut National de la Recherche Agronomique (INRA)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Lao Department of Agricultural Land Management (DALaM), Multi-Scale Environmental Changes project (MSEC), Consultative Group on International Agricultural Research (CGIAR) research program 'Humidtropics', GIS-Climat, French National Research Agency [ANR-13-AGRO-0007], Research Institute for Development (IRD), Institut de Recherche pour le Developpement, Wellcome Trust of Great Britain [106680/Z/14/Z], Joseph M. Vinetz, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)

Subjects
Male, Atmospheric Science, Rain, Marine and Aquatic Sciences, Water supply, 010501 environmental sciences, Pathology and Laboratory Medicine, 01 natural sciences, Geographical Locations, Feces, 0302 clinical medicine, Natural Resources, Tropical climate, Dry season, Medicine and Health Sciences, LAOS, Public and Occupational Health, 030212 general & internal medicine, Sanitation, 2. Zero hunger, Ecology, lcsh:Public aspects of medicine, Hygiene, 6. Clean water, Infectious Diseases, Water Resources, Female, Seasons, Water Microbiology, Environmental Health, Research Article, Freshwater Environments, Diarrhea, Wet season, lcsh:Arctic medicine. Tropical medicine, Asia, lcsh:RC955-962, Indicator bacteria, Gastroenterology and Hepatology, 03 medical and health sciences, Signs and Symptoms, Meteorology, Rivers, Diagnostic Medicine, Surface Water, Water Supply, Environmental health, Escherichia coli, Humans, Epidemics, Demography, Retrospective Studies, 0105 earth and related environmental sciences, Tropical Climate, business.industry, Ecology and Environmental Sciences, Public Health, Environmental and Occupational Health, Aquatic Environments, Water, lcsh:RA1-1270, Community Health Centers, Bodies of Water, 15. Life on land, Health Care, Water resources, 13. Climate action, People and Places, Earth Sciences, Hydrology, business, Surface runoff, Surface water, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

Background The global burden of diarrhea is a leading cause of morbidity and mortality worldwide. In montane areas of South-East Asia such as northern Laos, recent changes in land use have induced increased runoff, soil erosion and in-stream suspended sediment loads, and potential pathogen dissemination. To our knowledge, few studies have related diarrhea incidences to catchment scale hydrological factors such as river discharge, and loads of suspended sediment and of Fecal Indicator Bacteria (FIB) such as Escherichia coli, together with sociological factors such as hygiene practices. We hypothesized that climate factors combined with human behavior control diarrhea incidence, either because higher rainfall, leading to higher stream discharges, suspended sediment loads and FIB counts, are associated with higher numbers of reported diarrhea cases during the rainy season, or because water shortage leads to the use of less safe water sources during the dry season. Using E. coli as a FIB, the objectives of this study were thus (1) to characterize the epidemiological dynamics of diarrhea in Northern Laos, and (2) to identify which hydro-meteorological and sociological risk factors were associated with diarrhea epidemics. Methods Considering two unconnected river catchments of 22 and 7,448 km2, respectively, we conducted a retrospective time series analysis of meteorological variables (rainfall, air temperature), hydrological variables (discharge, suspended sediments, FIB counts, water temperature), and the number of diarrheal disease cases reported at 6 health centers located in the 5 southern districts of the Luang Prabang Province, Lao PDR. We also examined the socio-demographic factors potentially affecting vulnerability to the effect of the climate factors, such as drinking water sources, hygiene habits, and recreational water exposure. Results Using thus a mixed methods approach, we found E. coli to be present all year long (100–1,000 Most Probable Number or MPN 100 mL-1) indicating that fecal contamination is ubiquitous and constant. We found that populations switch their water supply from wells to surface water during drought periods, the latter of which appear to be at higher risk of bacterial contamination than municipal water fountains. We thus found that water shortage in the Luang Prabang area triggers diarrhea peaks during the dry and hot season and that rainfall and aquifer refill ends the epidemic during the wet season. The temporal trends of reported daily diarrhea cases were generally bimodal with hospital admissions peaking in February-March and later in May-July. Annual incidence rates were higher in more densely populated areas and mostly concerned the 0–4 age group and male patients. Conclusions We found that anthropogenic drivers, such as hygiene practices, were at least as important as environmental drivers in determining the seasonal pattern of a diarrhea epidemic. For diarrheal disease risk monitoring, discharge or groundwater level can be considered as relevant proxies. These variables should be monitored in the framework of an early warning system provided that a tradeoff is found between the size of the monitored catchment and the frequency of the measurement., Author Summary Aiming to identify the most critical drivers of diarrhea epidemics in montane areas of South-East Asia, we conducted a retrospective time series analysis of diarrhea reported cases and of hydro-meteorological variables measured in two contrasted river basins in northern Laos, together with socio-behavioral practices. We found that during drought periods, the population switches its water supply from wells to surface water where we measured numbers of fecal indicator bacteria (E. coli) of 100–1,000 MPN 100 mL-1 (the World Health Organization recommendation is 0 MPN 100 mL-1 in drinking water supply sources). We found that water shortages trigger diarrhea peaks during the dry and hot seasons and that rainfall and subsequent aquifer refill ends the epidemic during the wet season. As E. coli counts in surface water are high all year long, E. coli may not be a relevant indicator of the fecal risk in this area. Conversely, stream discharge and aquifer water level appear to be relevant proxies to predict diarrheal risk. Mitigating both environmental and anthropogenic drivers of fecal bacteria dissemination in developing countries is critical in the context of global change: more intense rainfall combined to the extension of run-off prone land uses (e.g. tree plantation without understorey) may decrease both the aquifer recharge and the contaminant retention ecosystem service, and thus threaten the availability of safe water resource for the population.

Published
2016
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9. Causality Analysis Between Climatic Factors And Dengue Fever Using The Granger Causality

Author

Pham Nguyen Hoang, Ho Tuong Vinh, Marc Choisy, Jean-Daniel Zucker, Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO), Université Cadi Ayyad [Marrakech] (UCA)-Université de Yaoundé I-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Institut de la francophonie pour l'informatique-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut de Recherche pour le Développement (IRD [France-Nord]), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), 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]), Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), PHAM, Nguyen Hoang, and Génétique et évolution des maladies infectieuses (GEMI)

Subjects
EPIDEMIOLOGIE, DENGUE, 030231 tropical medicine, Dengue virus, medicine.disease_cause, Dengue fever, law.invention, 03 medical and health sciences, 0302 clinical medicine, Granger causality, CORRELATION TEMPORELLE, law, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, medicine, [SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health, dengue fever, 030212 general & internal medicine, Socioeconomics, [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, CAUSALITE AU SENS DE GRANGER, Incidence (epidemiology), Tropical disease, medicine.disease, Causality, [STAT] Statistics [stat], 3. Good health, [STAT]Statistics [stat], Geography, Transmission (mechanics), Vietnam, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Close relationship, FACTEUR CLIMATIQUE, Climatology, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, climatic drivers, ANALYSE MULTIVARIABLE
Abstract

International audience; Dengue is a mosquito-borne tropical disease caused by one of the four serotypes of dengue virus. There are about 2,5 billion people living in endemic areas. The potential influence of environmental and climatic factors on the transmission of mosquito-borne diseases are expected in many situations but the exact real influences of climatic variables remain uncertain in most of the cases. In the present study, we applied the Granger causality to analyze the relation between climatic variables and the monthly incidences of dengue syndromes in Vietnam for 64 provinces from 1994 to 2010. The experimental results shows a close relationship between climatic factors and dengue incidence in each province and their neighbourhoods.

Published
2016
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10. The niche reduction approach: an opportunity for optimal control of infectious diseases in low-income countries?

Author

Marc Choisy, Jean-Daniel Zucker, Bernard Cazelles, Hélène Broutin, Yann Chevaleyre, Sylvain Godreuil, Romulus Breban, Guillaume Constantin de Magny, Benjamin Roche, Frédéric Simard, Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO), Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA), 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]), Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), Pathogénèse et contrôle des infections chroniques (PCCI), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Du gène à l'écosystème (MIVEGEC-GeneSys), Pathogènes, Environnement, Santé Humaine (EPATH), 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]), Laboratoire d'Informatique de Paris-Nord (LIPN), Université Paris 13 (UP13)-Institut Galilée-Université Sorbonne Paris Cité (USPC)-Centre National de la Recherche Scientifique (CNRS), Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology, 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)-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), Laboratoire Ecologie et évolution, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Diversity, ecology, evolution & Adaptation of arthropod vectors (MIVEGEC-DEEVA), Evolution des Systèmes Vectoriels (ESV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Universitaire de Montpellier (CHU Montpellier )-Université de Montpellier (UM), Université Sorbonne Paris Cité (USPC)-Institut Galilée-Université Paris 13 (UP13)-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), École normale supérieure - Paris (ENS Paris), Génétique et évolution des maladies infectieuses (GEMI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre Hospitalier Universitaire de Montpellier (CHU Montpellier ), 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), and BMC, Ed.

Subjects
ECOLOGIE DES PARASITES, medicine.medical_specialty, Debate, Developing country, HIV Infections, Biology, POLITIQUE DE SANTE, ENDEMIE, RELATION HOTE PARASITE, EPIDEMIE, METHODE DE LUTTE, Development economics, Yellow Fever, medicine, Smallpox, Western world, Humans, Temporal scales, Developing Countries, Poverty, 2. Zero hunger, Public health, Vaccination, 1. No poverty, Public Health, Environmental and Occupational Health, medicine.disease, EVOLUTION, 3. Good health, Malaria, NICHE ECOLOGIQUE, ETUDE DE CAS, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Immunology, Communicable Disease Control, Evolutionary ecology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Public Health, AGENT PATHOGENE, Measles
Abstract

International audience; BACKGROUND: During the last century, WHO led public health interventions that resulted in spectacular achievements such as the worldwide eradication of smallpox and the elimination of malaria from the Western world. However, besides major successes achieved worldwide in infectious diseases control, most elimination/control programs remain frustrating in many tropical countries where specific biological and socio-economical features prevented implementation of disease control over broad spatial and temporal scales. Emblematic examples include malaria, yellow fever, measles and HIV. There is consequently an urgent need to develop affordable and sustainable disease control strategies that can target the core of infectious diseases transmission in highly endemic areas. DISCUSSION: Meanwhile, although most pathogens appear so difficult to eradicate, it is surprising to realize that human activities are major drivers of the current high rate of extinction among upper organisms through alteration of their ecology and evolution, i.e., their "niche". During the last decades, the accumulation of ecological and evolutionary studies focused on infectious diseases has shown that the niche of a pathogen holds more dimensions than just the immune system targeted by vaccination and treatment. Indeed, it is situated at various intra- and inter- host levels involved on very different spatial and temporal scales. After developing a precise definition of the niche of a pathogen, we detail how major advances in the field of ecology and evolutionary biology of infectious diseases can enlighten the planning and implementation of infectious diseases control in tropical countries with challenging economic constraints. SUMMARY: We develop how the approach could translate into applied cases, explore its expected benefits and constraints, and we conclude on the necessity of such approach for pathogen control in low-income countries.

Published
2014
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11. Ecologie prédictive & changement planétaire

Author

Frédéric Austerlitz, Michael Blum, Sarah Calba, Jérôme Chave, Marc Choisy, Audrey Coreau, Vincent Devictor, Luc Doyen, Stéphane Dray, Anne Duputié, Damien Eveillard, Denis Faure, Charly Favier, Oscar Gaggiotti, Nicolas Galtier, Eric Garnier, Olivier Gimenez, Helene Guis, Vincent Herbreteau, Philippe Huneman, Franck Jabot, Philippe Jarne, Dominique Joly, Romain Julliard, Sonia Kéfi, Gael Kergoat, Gerard Lacroix, Yvan Lagadeuc, Sandra Lavorel, Jean-François Le Gaillard, Line Le Gall, Michel Loreau, Virginie Maris, Serge Morand, Xavier Morin, Hélène Morlon, Nicolas Mouquet, Gilles Pinay, Julien Pottier, Roger Pradel, Ophélie Ronce, Frank Schurr, Pascal Simonet, Céline Teplitsky, Wilfried Thuiller, Anne-Lise Tran, Samuel Venner, Eco-Anthropologie et Ethnobiologie (EAE), Muséum national d'Histoire naturelle (MNHN)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), CNRS, University Joseph Fourier, Centre National de la Recherche Scientifique (CNRS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), 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), 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]), Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), AgroParisTech, Centre Alexandre Koyré - Centre de Recherche en Histoire des Sciences et des Techniques (CAK-CRHST), Muséum national d'Histoire naturelle (MNHN)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS), Conservation des espèces, Restauration et Suivi des Populations (CERSP), Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Ecologie quantitative et évolutive des communautés, Département écologie évolutive [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Hydrobiologie (UR HYAX), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Laboratoire d'Informatique de Nantes Atlantique (LINA), Mines Nantes (Mines Nantes)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS), Inst Sci Vegetal, Laboratoire d'Ecologie Alpine (LECA), Université Joseph Fourier - Grenoble 1 (UJF)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Contrôle des maladies animales exotiques et émergentes (UMR CMAEE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), 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), Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST), Université Paris 1 Panthéon-Sorbonne (UP1)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'ingénierie pour les systèmes complexes (UR LISC), Centre de recherche Croissance et signalisation (UMR_S 845), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Ecologie et des Sciences de la COnservation (CESCO), Centre de Biologie pour la Gestion des Populations (UMR CBGP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Biogéochimie et écologie des milieux continentaux (Bioemco), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Université Pierre et Marie Curie - Paris 6 (UPMC)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), RBPE, Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Systématique, adaptation, évolution (SAE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Expt Ecol Stn, Ctr Biodivers Theory & Modelling, Institut de biologie de l'ENS Paris (IBENS), Département de Biologie - ENS Paris, Université Paris sciences et lettres (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)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (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)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de Mathématiques Appliquées (CMAP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Unité de recherche sur l'Ecosystème Prairial (UREP), Institut National de la Recherche Agronomique (INRA), Agence Française de Sécurité Sanitaire des Aliments (AFSSA), Ampère, Département Bioingénierie (BioIng), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Thiébault, Stéphanie and Hadi, Halima, Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Paul-Valéry - Montpellier 3 (UM3), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Centre National de la Recherche Scientifique (CNRS)-Cité des Sciences et de l'Industrie-École des hautes études en sciences sociales (EHESS), Conservation des espèces, restauration et suivi des populations (CERSP), Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Joseph Fourier - Grenoble 1 (UJF)-Université Grenoble Alpes (UGA), Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Université des Antilles (UA)-Université de Guyane (UG)-Université de Montpellier (UM)-Université de La Réunion (UR)-Avignon Université (AU)-Université de Perpignan Via Domitia (UPVD)-Institut de Recherche pour le Développement (IRD), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Recherche Agronomique (INRA)-École normale supérieure - Paris (ENS Paris), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut de biologie de l'ENS Paris (UMR 8197/1024) (IBENS), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), AFSSA, Ampère, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Université Paris Diderot - Paris 7 (UPD7), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE), 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, Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN), Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-Université de Nantes (UN), Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), 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), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Recherche Agronomique (INRA)-Université Pierre et Marie Curie - Paris 6 (UPMC)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Département de Biologie - ENS Paris, Université Paris sciences et lettres (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)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (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), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Muséum national d'Histoire naturelle (MNHN), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), École des hautes études en sciences sociales (EHESS)-Cité des Sciences et de l'Industrie-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UR226, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
CNRS8, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2013

12. Canine visceral leishmaniasis caused by Leishmania infantum in Senegal: risk of emergence in humans?

Author

Souleymane Diedhiou, Anne-Laure Bañuls, M. Claire, Jean Louis Ndiaye, Malick Faye, S. Mellul, Bruno Bucheton, Mallorie Hide, Michel M. Dione, J. Dereure, I. Sy, Pierre Marty, O. Konate, Jean-François Molez, K. Victoir, Oumar Gaye, O. Bassanganam, R. Knecht, Abdoul Aziz Niang, Massila Wagué Senghor, Marc Choisy, Pascal Delaunay, Babacar Faye, Génétique et évolution des maladies infectieuses (GEMI), and Université Montpellier 1 (UM1)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])

Subjects
Male, Prevalence, Polymerase Chain Reaction, 0302 clinical medicine, Seroepidemiologic Studies, Zoonoses, Canine leishmaniasis, Dog, Dog Diseases, Leishmania infantum, Child, ComputingMilieux_MISCELLANEOUS, Aged, 80 and over, Leishmania, 0303 health sciences, biology, Zoonosis, Middle Aged, Senegal, 3. Good health, Infectious Diseases, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, Child, Preschool, Leishmaniasis, Visceral, Female, Human, Adult, Adolescent, 030231 tropical medicine, Immunology, Microbiology, Risk Assessment, 03 medical and health sciences, Young Adult, Dogs, West Africa, medicine, Seroprevalence, Animals, Humans, Aged, 030306 microbiology, Infant, Leishmaniasis, DNA, Protozoan, biology.organism_classification, medicine.disease, Visceral leishmaniasis
Abstract

In the context of global warming and the risk of spreading arthropod-borne diseases, the emergence and reemergence of leishmaniasis should not be neglected. In Senegal, over the past few years, cases of canine leishmaniasis have been observed. We aim to improve the understanding of the transmission cycle of this zoonosis, to determine the responsible species and to evaluate the risk for human health. An epidemiological and serological study on canine and human populations in the community of Mont Rolland (Thies area) was conducted. The data showed a high seroprevalence of canine leishmaniasis (>40%) and more than 30% seropositive people. The dogs' seroprevalence was confirmed by PCR data (concordance > 0.85, Kappa > 0.7). The statistical analysis showed strong statistical associations between the health status of dogs and seropositivity, the number of positive PCRs, clinical signs and the number of Leishmania isolates. For the first time, the discriminative PCRs performed on canine Leishmania strains clearly evidenced that the pathogenic agent is Leishmania infantum. The results obtained show that transmission of this species is well established in this area. That the high incidence of seropositivity in humans may be a consequence of infection with this species is discussed. Published by Elsevier Masson SAS on behalf of the Institut Pasteur.

Published
2010
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13. Cultural Diversity, Economic Development and Societal Instability

Author

Howard V. Cornell, James B. Grace, Daniel Nettle, Jean-François Guégan, Marc Choisy, Michael E. Hochberg, Centre for Behaviour and Evolution, Newcastle University [Newcastle], US Geological Survey [Lafayette], United States Geological Survey [Reston] (USGS), Génétique et évolution des maladies infectieuses (GEMI), Centre National de la Recherche Scientifique (CNRS)-Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD [France-Sud]), Department of Environmental Science and Policy [Davis], University of California [Davis] (UC Davis), University of California-University of California, Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UR226, National Center for Ecological Analysis and Synthesis (NCEAS), Santa Fe Institute, Université Montpellier 1 (UM1)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Department of Environmental Science and Policy [Univ California Davis] (DESP - UC Davis), University of California (UC)-University of California (UC), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cross-Cultural Comparison, Religion and Psychology, 0106 biological sciences, Social Values, Economics, media_common.quotation_subject, Ethnic group, Beta diversity, lcsh:Medicine, Social value orientations, Biology, 010603 evolutionary biology, 01 natural sciences, 03 medical and health sciences, Diversity index, Cultural diversity, Ecology/Behavioral Ecology, Humans, Economic geography, Economic impact analysis, 10. No inequality, lcsh:Science, 030304 developmental biology, media_common, 0303 health sciences, Multidisciplinary, lcsh:R, 1. No poverty, Cultural Diversity, Models, Theoretical, respiratory system, [SDE.ES]Environmental Sciences/Environmental and Society, Alpha diversity, lcsh:Q, Societies, human activities, Research Article, Diversity (politics)
Abstract

International audience; Background. Social scientists have suggested that cultural diversity in a nation leads to societal instability. However, societal instability may be affected not only by within-nation or alpha diversity, but also diversity between a nation and its neighbours or beta diversity. It is also necessary to distinguish different domains of diversity, namely linguistic, ethnic and religious, and to distinguish between the direct effects of diversity on societal instability, and effects that are mediated by economic conditions. Methodology/Principal Findings. We assembled a large cross-national dataset with information on alpha and beta cultural diversity, economic conditions, and indices of societal instability. Structural equation modeling was used to evaluate the direct and indirect effects of cultural diversity on economics and societal stability. Results show that different types and domains of diversity have interacting effects. As previously documented, linguistic alpha diversity has a negative effect on economic performance, and we show that it is largely through this economic mechanism that it affects societal instability. For beta diversity, the higher the linguistic diversity among nations in a region, the less stable the nation. But, religious beta diversity has the opposite effect, reducing instability, particularly in the presence of high linguistic diversity. Conclusions. Within-nation linguistic diversity is associated with reduced economic performance, which, in turn, increases societal instability. Nations which differ linguistically from their neighbors are also less stable. However, religious diversity between neighboring nations has the opposite effect, decreasing societal instability.

Published
2007
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14. Phylodynamique de la grippe

Author

Vergu, Elisabeta, Flahault, Antoine, Viboud, Cécile, Unité de biométrie et intelligence artificielle de jouy, Institut National de la Recherche Agronomique (INRA), École des Hautes Études en Santé Publique [EHESP] (EHESP), Fogarty International Center, National Institutes of Health [Bethesda] (NIH), Jean-François Guégan, Marc Choisy, and Jean-François Girard (Préfacier)

Subjects
epidemiologie humaine, dynamique de population, modélisation mathématique, [INFO]Computer Science [cs], [MATH]Mathematics [math], évolution virale
Abstract

Chapitre n° 11; National audience

Published
2008

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