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Background Workplace absenteeism increases significantly during influenza epidemics. Sick leave records may facilitate more timely detection of influenza outbreaks, as trends in increased sick leave may precede alerts issued by sentinel surveillance systems by days or weeks. Sick leave data have not been comprehensively evaluated in comparison to traditional surveillance methods. The aim of this paper is to study the performance and the feasibility of using a detection system based on sick leave data to detect influenza outbreaks. Methods Sick leave records were extracted from private French health insurance data, covering on average 209,932 companies per year across a wide range of sizes and sectors. We used linear regression to estimate the weekly number of new sick leave spells between 2016 and 2017 in 12 French regions, adjusting for trend, seasonality and worker leaves on historical data from 2010 to 2015. Outbreaks were detected using a 95%-prediction interval. This method was compared to results from the French Sentinelles network, a gold-standard primary care surveillance system currently in place. Results Using sick leave data, we detected 92% of reported influenza outbreaks between 2016 and 2017, on average 5.88 weeks prior to outbreak peaks. Compared to the existing Sentinelles model, our method had high sensitivity (89%) and positive predictive value (86%), and detected outbreaks on average 2.5 weeks earlier. Conclusion Sick leave surveillance could be a sensitive, specific and timely tool for detection of influenza outbreaks.

BACKGROUND: Plasmodium vivax malaria is challenging to control and eliminate. Treatment with radical cure drugs fails to target the hidden asymptomatic and hypnozoite reservoirs in populations. PvSeroTAT, a novel serological test-and-treat intervention using a serological diagnostic to screen hypnozoite carriers for radical cure eligibility and treatment, could accelerate P. vivax elimination. METHODS: Using a previously developed mathematical model of P. vivax transmission adapted to the Brazilian context as a case study for implementation, we evaluate the public health impact of various deployment strategies of PvSeroTAT as a mass campaign. We compare relative reductions in prevalence, cases averted, glucose-6-phosphate dehydrogenase (G6PD) tests, and treatment doses of PvSeroTAT campaigns to strengthened case management alone or mass drug administration (MDA) campaigns across different settings. FINDINGS: Deploying a single round of PvSeroTAT with 80% coverage to treat cases with a high efficacy radical cure regimen with primaquine is predicted to reduce point population prevalence by 22.5% [95% UI: 20.2%-24.8%] in a peri-urban setting with high transmission and by 25.2% [95% UI: 9.6%-42.2%] in an occupational setting with moderate transmission. In the latter example, while a single PvSeroTAT achieves 9.2% less impact on prevalence and averts 300 less cases per 100,000 than a single MDA (25.2% [95% UI: 9.6%-42.2%] point prevalence reduction versus 34.4% [95% UI: 24.9%-44%]), PvSeroTAT requires 4.6 times less radical cure treatments and G6PD tests. Layering strengthened case management and deploying four rounds of PvSeroTAT six months apart is predicted to reduce point prevalence by a mean of 74.1% [95% UI: 61.3%-86.3%] or more in low transmission settings with less than 10 cases per 1000 population. INTERPRETATION: Modelling predicts that mass campaigns with PvSeroTAT are predicted to reduce P. vivax parasite prevalence across a range of transmission settings and require fewer resources than MDA. In combination with strengthened case management, mass campaigns of serological test-and-treat interventions can accelerate towards P. vivax elimination. FUNDING: This project was funded in part by the Bill and Melinda Gates Foundation and the National Health and Medical Research Council.

Serological markers are a promising tool for surveillance and targeted interventions for Plasmodium vivax malaria. P. vivax is closely related to the zoonotic parasite P. knowlesi, which also infects humans. P. vivax and P. knowlesi are co-endemic across much of South East Asia, making it important to design serological markers that minimize cross-reactivity in this region. To determine the degree of IgG cross-reactivity against a panel of P. vivax serological markers, we assayed samples from human patients with P. knowlesi malaria. IgG antibody reactivity is high against P. vivax proteins with high sequence identity with their P. knowlesi ortholog. IgG reactivity peaks at 7 days post-P. knowlesi infection and is short-lived, with minimal responses 1 year post-infection. We designed a panel of eight P. vivax proteins with low levels of cross-reactivity with P. knowlesi. This panel can accurately classify recent P. vivax infections while reducing misclassification of recent P. knowlesi infections.

Background Carbapenemase-producing Enterobacteriaceae (CPE) cause resistant healthcare-associated infections that jeopardize healthcare systems and patient safety worldwide. The number of CPE episodes has been increasing in France since 2009, but the dynamics are still poorly understood. Objectives To use time-series modelling to describe the dynamics of CPE episodes from August 2010 to December 2016 and to forecast the evolution of CPE episodes for the 2017–20 period. Methods We used time series to analyse CPE episodes from August 2010 to November 2016 reported to the French national surveillance system. The impact of seasonality was quantified using seasonal-to-irregular ratios. Seven time-series models and three ensemble stacking models (average, convex and linear stacking) were assessed and compared with forecast CPE episodes during 2017–20. Results During 2010–16, 3559 CPE episodes were observed in France. Compared with the average yearly trend, we observed a 30% increase in the number of CPE episodes in the autumn. We noticed a 1 month lagged seasonality of non-imported episodes compared with imported episodes. Average stacking gave the best forecasts and predicted an increase during 2017–20 with a peak up to 345 CPE episodes (95% prediction interval = 124–1158, 80% prediction interval = 171–742) in September 2020. Conclusions The observed seasonality of CPE episodes sheds light on potential factors associated with the increased frequency of episodes, which need further investigation. Our model predicts that the number of CPE episodes will continue to rise in the coming years in France, mainly due to local dissemination, associated with bacterial carriage by patients in the community, which is becoming an immediate challenge with regard to outbreak control.

L9LS, a potent and safe antimalarial monoclonal antibody, demonstrated 88% protective efficacy against infection in a phase 1 trial in healthy adults.(1) These promising results are the first of many to usher in a potential new era of malaria prevention.

SummarySerological exposure markers are a promising tool for surveillance and targeted interventions for Plasmodium vivax malaria. P. vivax is closely related to the zoonotic parasite P. knowlesi, which also infects humans. P. vivax and P. knowlesi are co-endemic across much of South East Asia, making it important to design P. vivax serological markers that minimise cross-reactivity in this region. Our objective was to determine the degree of IgG antibody cross-reactivity against a panel of P. vivax serological markers in samples from human participants with P. knowlesi malaria. We observed higher levels of IgG antibody reactivity against P. vivax proteins that had high levels of sequence identity with their P. knowlesi ortholog. IgG reactivity peaked at 7 days post P. knowlesi infection and was short-lived, with minimal responses detected at 1-year post-infection. Using these data, we designed a panel of 8 P. vivax proteins with low-levels of cross-reactivity with P. knowlesi. This panel was able to accurately classify recent P. vivax infections whilst reducing misclassification of recent P. knowlesi infections.

ObjectiveTo identify the role of Staphylococcus aureus (SA) or its intracellular small-colony variant phenotype (SCV) with co-trimoxazole (CTX) or ANCA-associated vasculitis (AAV) activity.MethodsAll consecutive AAV patients with granulomatosis with polyangiitis (GPA), eosinophilic GPA or microscopic polyangiitis, followed at the French National Vasculitis Referral Center (09/2012–05/2013), and hospitalized non-AAV controls, exclusively for SA/SCV carriage comparisons, were enrolled. All had bilateral anterior nasal swab cultures. Nasal SA or SCV carriage was determined and associations with relapse(s), BVAS, ANCA-positivity, anti-staphylococcal and immunosuppressant use, were analysed ⩾4 years post-inclusion.ResultsNasal SA carriage rates did not differ among AAVs (P = 0.53): GPA (24/80; 30%), EGPA (7/28; 25%) and microscopic polyangiitis (3/11; 27.3%); and the rate was less frequent in controls than in GPA patients not taking CTX (P = 0.04). AAV patients taking CTX prophylaxis had less nasal SA carriage (8.7% vs 36.2%; P = 0.02). Nasal SA carriage or CTX use did not modify relapse rates, BVAS or ANCA-positivity at inclusion or during follow-up. Nasal SCV carriage, found in 15/207 (7.2%) patients, was similar for GPA (10/24; 41.7%), microscopic polyangiitis (2/7; 28.6%) and eosinophilic GPA (2/3; 66.7%), but higher (P = 0.02) than controls (1/14; 7.1%). SCV carriage by AAV groups did not modify relapse rates or ANCA positivity at inclusion or during follow-up; a trend towards higher BVAS was observed only for anti-PR3 ANCA patients.ConclusionNasal SA or SCV carriage was comparable among AAVs but more frequent than in controls. Nasal SA or SCV carriage and CTX use did not modify AAV relapse rates.

Thailand is aiming for malaria elimination by the year 2030. However, the high proportion of asymptomatic infections and the presence of the hidden hypnozoite stage of Plasmodium vivax are impeding these efforts. We hypothesized that a validated surveillance tool utilizing serological markers of recent exposure to P. vivax infection could help to identify areas of ongoing transmission. The objective of this exploratory study was to assess the ability of P. vivax serological exposure markers to detect residual transmission ‘hot-spots’ in Western Thailand. Total IgG levels were measured against a panel of 23 candidate P. vivax serological exposure markers using a multiplexed bead-based assay. A total of 4255 plasma samples from a cross-sectional survey conducted in 2012 of endemic areas in the Kanchanaburi and Ratchaburi provinces were assayed. We compared IgG levels with multiple epidemiological factors that are associated with an increased risk of P. vivax infection in Thailand, including age, gender and spatial location, as well as Plasmodium infection status itself. IgG levels to all proteins were significantly higher in the presence of a P. vivax infection (n=144) (t test, p18 years, pP. vivax parasites in the last 9-months, based on their IgG antibody levels to a panel of 8 previously validated P. vivax proteins. Spatial clustering was observed at the village and regional level, with a moderate correlation between PCR prevalence and sero-prevalence as predicted by the algorithm. Our data provides proof-of-concept for application of such surrogate markers as evidence of recent exposure in low transmission areas. These data can be used to better identify geographical areas with asymptomatic infection burdens that can be targeted in elimination campaigns.

Plasmodium vivax relapses caused by reactivating hypnozoites are a major barrier for elimination and control of this form of malaria. Radical cure is a form of therapy capable of addressing this problem. Recent clinical trials of radical cure have yielded efficacy estimates ranging from 65% to 94%, with substantial variation across trial sites. We performed an analysis of simulated trial data using a transmission model to demonstrate that variation in efficacy estimates across trial sites can arise from differences in the conditions under which trials are conducted. Our analysis revealed that differences in transmission intensity, heterogeneous exposure, and relapse rate can yield efficacy estimates ranging as wide as 12-78%, despite simulating trial data under the uniform assumption that treatment had a 75% chance of clearing hypnozoites. A longer duration of prophylaxis leads to a greater measured efficacy, particularly at higher transmission intensities, making the comparison of the protection of different radical cure treatment regimens against relapse more challenging. We show that vector control and parasite genotyping offer two potential means to yield more standardized efficacy estimates that better reflect protection against relapse. We predict that site-specific biases are likely to contribute to variation in efficacy estimates both within and across phase-III clinical trials. Future clinical trials can reduce site-specific biases by conducting trials in low-transmission settings where reinfections from mosquito biting are less common, by preventing reinfections using vector control measures, or by identifying and excluding likely reinfections that occur during follow-up using parasite genotyping methods.AUTHOR SUMMARYRadical cure holds promise as a strategy for Plasmodium vivax malaria control by clearing the parasites known as hypnozoites that latently infect the liver and cause relapsing infections. The efficacy of radical cure treatment regimens is evaluated in phase-III clinical trials. Recent trial results have noted substantial variation in efficacy estimates across trial sites, complicating the interpretation of the benefit of radical cure. However, P. vivax infections identified during the course of the clinical trial could include reinfections from mosquito biting that do not directly reflect the effect of the therapeutic being trialed, potentially biasing efficacy estimates. In this study, we simulated clinical trials to identify the causes and solutions of these site-specific biases. We found that features of both the trial location, such as the transmission intensity, and the trial design, such as the duration of follow-up, lead to an underestimate of the effect of radical cure against hypnozoites. We then demonstrated that vector control and parasite genotyping are two possible strategies to reduce these biases. These insights can be leveraged to aid in the interpretation of past trial results and to help design future clinical trials that minimize site-specific biases.

Additional file 1. Figure S1: Incidence per 100,000 per week of influenza-like illness and sick leave in twelve French regions, 2010–2017. The Christmas and summer school holidays (increased worker leave periods) are shown at the bottom. Figure S2: Incidence of influenza-like illness and sick leave, 2015–2017, and alerts from the Sentinelles and the sick-leave models, in twelve French regions. The Christmas and summer school holidays (increased worker leave periods) are shown at the bottom. Table S1: Performance of the sick-leave model compared to the Sentinelles model.

Additional file 1: Table S1. Notified cases and incidence per 1000 population per year, malaria type, highest transmission state of the Amazon Basin. Figure S1. Monthly P. vivax and P. falciparum cases. Figure S2. P. vivax and P. falciparum 2018 cases stratified by municipality. Figure S3. States reporting cases imported from Venezuela. Figure S4. Proportion of P. vivax and P. falciparum cases by age group per year in each State stratified by gender. Figure S5. Proportion of cases in the top 1% of municipalities and health units. Figure S6. Gini coefficient and population size.

Thailand is aiming for malaria elimination by the year 2030. However, the high proportion of asymptomatic infections and the presence of the hidden hypnozoite stage of Plasmodium vivax are impeding these efforts. We hypothesized that a validated surveillance tool utilizing serological markers of recent exposure to P. vivax infection could help to identify areas of ongoing transmission. The objective of this exploratory study was to assess the ability of P. vivax serological exposure markers to detect residual transmission “hot-spots” in Western Thailand. Total IgG levels were measured against a panel of 23 candidate P. vivax serological exposure markers using a multiplexed bead-based assay. A total of 4,255 plasma samples from a cross-sectional survey conducted in 2012 of endemic areas in the Kanchanaburi and Ratchaburi provinces were assayed. We compared IgG levels with multiple epidemiological factors that are associated with an increased risk of P. vivax infection in Thailand, including age, gender, and spatial location, as well as Plasmodium infection status itself. IgG levels to all proteins were significantly higher in the presence of a P. vivax infection (n = 144) (T-test, p < 0.0001). Overall seropositivity rates varied from 2.5% (PVX_097625, merozoite surface protein 8) to 16.8% (PVX_082670, merozoite surface protein 7), with 43% of individuals seropositive to at least 1 protein. Higher IgG levels were associated with older age (>18 years, p < 0.05) and males (17/23 proteins, p < 0.05), supporting the paradigm that men have a higher risk of infection than females in this setting. We used a Random Forests algorithm to predict which individuals had exposure to P. vivax parasites in the last 9-months, based on their IgG antibody levels to a panel of eight previously validated P. vivax proteins. Spatial clustering was observed at the village and regional level, with a moderate correlation between PCR prevalence and sero-prevalence as predicted by the algorithm. Our data provides proof-of-concept for application of such surrogate markers as evidence of recent exposure in low transmission areas. These data can be used to better identify geographical areas with asymptomatic infection burdens that can be targeted in elimination campaigns.

The spread of carbapenemase-producing Enterobacteriaceae (CPE) in healthcare settings is a major public health threat that has been associated with cross-border and local patient transfers between healthcare facilities. Since the impact of transfers on spread may vary, our study aimed to assess the contribution of a patient transfer network on CPE incidence and spread at a countrywide level, with a case study of France from 2012 to 2015. Our results suggest a transition in 2013 from a CPE epidemic sustained by internationally imported episodes to an epidemic sustained by local transmission events through patient transfers. Incident episodes tend to occur within close spatial distance of their potential infector. We also observe an increasing frequency of multiple spreading events, originating from a limited number of regional hubs. Consequently, coordinated prevention and infection control strategies should focus on transfers of carriers of CPE to reduce regional and inter-regional transmission.

BackgroundInfection with SARS-CoV-2 induces an antibody response targeting multiple antigens that changes over time. This complexity presents challenges and opportunities for serological diagnostics.MethodsA multiplex serological assay was developed to measure IgG and IgM antibody responses to seven SARS-CoV-2 spike or nucleoprotein antigens, two antigens for the nucleoproteins of the 229E and NL63 seasonal coronaviruses, and three non-coronavirus antigens. Antibodies were measured in serum samples from patients in French hospitals with RT-qPCR confirmed SARS-CoV-2 infection (n= 259), and negative control serum samples collected before the start of the SARS-CoV-2 epidemic (n= 335). A random forests algorithm was trained with the multiplex data to classify individuals with previous SARS-CoV-2 infection. A mathematical model of antibody kinetics informed by prior information from other coronaviruses was used to estimate time-varying antibody responses and assess the potential sensitivity and classification performance of serological diagnostics during the first year following symptom onset. A statistical estimator is presented that can provide estimates of seroprevalence in very low transmission settings.ResultsIgG antibody responses to trimeric Spike protein identified individuals with previous RT-qPCR confirmed SARS-CoV-2 infection with 91.6% sensitivity (95% confidence interval (CI); 87.5%, 94.5%) and 99.1% specificity (95% CI; 97.4%, 99.7%). Using a serological signature of IgG and IgM to multiple antigens, it was possible to identify infected individuals with 98.8% sensitivity (95% CI; 96.5%, 99.6%) and 99.3% specificity (95% CI; 97.6%, 99.8%). Informed by prior data from other coronaviruses, we estimate that one year following infection a monoplex assay with optimal anti-StriIgG cutoff has 88.7% sensitivity (95% CI: 63.4%, 97.4%), and that a multiplex assay can increase sensitivity to 96.4% (95% CI: 80.9%, 100.0%). When applied to population-level serological surveys, statistical analysis of multiplex data allows estimation of seroprevalence levels less than 1%, below the false positivity rate of many other assays.ConclusionSerological signatures based on antibody responses to multiple antigens can provide accurate and robust serological classification of individuals with previous SARS-CoV-2 infection. This provides potential solutions to two pressing challenges for SARS-CoV-2 serological surveillance: classifying individuals who were infected greater than six months ago, and measuring seroprevalence in serological surveys in very low transmission settings.

Background: Carbapenemase-producing Enterobacteriaceae (CPE) cause resistant healthcare-associated infections that jeopardize healthcare systems and patient safety worldwide. The number of CPE episodes has been increasing in France since 2009 but the dynamics are still poorly understood. Methods: We used a time-series approach to analyze CPE episodes from August 2010 to November 2016 reported to the French national surveillance system. The impact of seasonality was quantified using seasonal-to-irregular ratios. Seven time-series models and three ensemble stacking models (average, convex and linear stacking) were assessed and compared to forecast CPE episodes during 2017-2020. Findings: During 2010-2016, 3559 CPE episodes were observed in France. Compared to the average yearly trend, we observed a 30% increase in the number of CPE episodes in Autumn. We noticed a 1-month lagged seasonality of non-imported episodes compared to imported episodes. Average stacking gave the best forecasts and predicted an increase during 2017-2020 with a peak up to 345 CPE episodes (95% PI[124-1158], 80% PI[171-742]) in September 2020. Interpretation: The observed seasonality of CPE episodes sheds light on potential factors associated with the increased frequency of episodes which need further investigations. Our model predicts that the number of CPE episodes will continue to rise in the coming years in France, mainly due to local dissemination, associated with bacterial carriage of patients in the community which is becoming an immediate challenge to help controlling the outbreak. Funding Statement: French national research agency (ANR) through the SPHINx project. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: Ethical and data access approvals for the present study were obtained in accordance with French legislation. The data on CPE episodes used in this study were anonymized and aggregated at the hospital level, which did not permit to identify colonized or infected cases. The study protocol was reviewed and accepted by the French national public health agency, which provided the data.

Background Incidence of Carbapenemase-Producing Enterobacteriaceae (CPE) episodes within hospitals is rising at an alarming rate and threaten health systems and patient safety worldwide. Their number is growing in France since 2009 associated with inter-regional dissemination and importation of international cases. This study aimed at describing the dynamics of CPE episodes in France over 2010-2016 and forecasting their evolution for 2017-2020. Methods Surveillance data of CPE episodes (imported and non-imported) from August 2010 to November 2016 were issued from the French national Healthcare-Associated Infections Early Warning and Response System. Impact of seasonality on the number of CPE episodes was analyzed using seasonal-to-irregular ratios. Seven models issued from time series analysis and three ensemble stacking models (average, convex and linear stacking) were used to describe and forecast CPE episodes. The model with the best forecasting’s quality was then trained on all available data (2010-2016) and used to predict CPE episodes over 2017-2020. Results Over 2010-2016, 3,559 CPE episodes were observed in France. Compared to the average yearly trend, we observed a 30% increase in the number of CPE episodes in September and October. On the opposite, a decrease of 20% was noticed in February compared to other months. We also noticed a 1-month lagged seasonality of non-imported episodes compared to imported ones. The number of non-imported episodes appeared to grow faster than imported ones starting from 2014. Average stacking gave the best forecasts and predicted an increase over 2017-2020 with a peak up to 345 CPE episodes (95% PI [124-1,158], 80% PI [171-742]) in September 2020. Conclusions The number of CPE episodes is predicted to rise in the next years in France because of non-imported episodes. These results could help public health authorities in the definition and evaluation of new containment strategies. Key messages Time series modeling predicts an increase in the number of CPE episodes in France in the next few years with a quicker rise of non-imported episodes. An increase of 30% in the number of CPE episodes was observed in September and October with a 1-month lagged seasonality impact of non-imported episodes compared to imported one.

International audience; IntroductionThe spread of carbapenemase-producing Enterobacteriaceae (CPE) is a major public health threat that has been associated with cross-border and local transfer of patients between healthcare facilities. However, the impact of healthcare transfer networks on CPE spread dynamics may vary in time and between countries. In this context, our study aimed to assess the contribution of the patient transfer network on CPE spread in France from 2012 to 2015.MethodsUsing the French healthcare network of 2.3 million patients, we extended a previously proposed statistical method and tested the ability of this network to support observed CPE incidence episodes. First, using 2237 CPE episodes that occurred from 2012 to 2015, we identified the most likely infector for the 1251 non-imported episodes using network-supported paths (NSPs). We then compared the observed NSP distances to those expected by chance, using random permutations of the CPE data. The impact of the assumed time window between infector episode and CPE episode was investigated in a sensitivity analysis.ResultsMore than half of all CPE episodes were linked, either as infectors or incident episodes. The percentage of episodes with identified potential infectors over the network increased with time, from 57% in 2012 to 66% in 2015. NSP distances from 2013 to 2015 were significantly shorter in the observed data than expected by chance, indicating a role of the transfer network in CPE spread dynamics in France. In 2012 however, this result was not found. Over the entire study period, linked episodes tended to occur in the same administrative department or within close geographic distances. The 3-to-4 weeks baseline window between infector and episode was supported by the sensitivity analysis, where the strongest evidence for network-supported CPE transmission was observed for 2014 and 2015 episodes.ConclusionsWe observed a transition in 2013 from an epidemic sustained by importation to local transmission events sustaining the epidemic. As a result of a growing contribution of transfers in CPE spread over time, coordinated prevention and infection control strategies in France should focus on at-risk patient transfers to reduce regional and inter-regional transmission of CPE.

Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network); patients with suspected HAI (suspected-HAI network); and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies., Author summary Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the scale of potential HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. We construct and compare the characteristics of three different patient transfer networks based on data on transfers of patients with diagnosed HAIs, suspected HAIs, or of all patients. Our analyses show that these healthcare networks, the patient populations that comprise them and the patient movement patterns are heterogeneous and centralized. Despite the differences in patient populations, the HAI-specific and suspected-HAI healthcare networks have the same underlying structure as that of the general healthcare network. We identify key hospital centers, patient flow trajectories, at both the regional and department (county) level that may serve as a basis for proposing novel wide-scale infection control strategies.

International audience; PURPOSE OF REVIEW: Mathematical modeling approaches have brought important contributions to the study of pathogen spread in healthcare settings over the last 20 years. Here, we conduct a comprehensive systematic review of mathematical models of disease transmission in healthcare settings and assess the application of contact and patient transfer network data over time and their impact on our understanding of transmission dynamics of infections.RECENT FINDINGS: Recently, with the increasing availability of data on the structure of interindividual and interinstitution networks, models incorporating this type of information have been proposed, with the aim of providing more realistic predictions of disease transmission in healthcare settings. Models incorporating realistic data on individual or facility networks often remain limited to a few settings and a few pathogens (mostly methicillin-resistant Staphylococcus aureus).SUMMARY: To respond to the objectives of creating improved infection prevention and control measures and better understanding of healthcare-associated infections transmission dynamics, further innovations in data collection and parameter estimation in modeling is required.

International audience; BackgroundInfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces an antibody response targeting multiple antigens that changes over time. This study aims to take advantage of this complexity to develop more accurate serological diagnostics.MethodsA multiplex serological assay was developed to measure IgG and IgM antibody responses to seven SARS-CoV-2 spike or nucleoprotein antigens, two antigens for the nucleoproteins of the 229E and NL63 seasonal coronaviruses, and three non-coronavirus antigens. Antibodies were measured in serum samples collected up to 39 days after symptom onset from 215 adults in four French hospitals (53 patients and 162 health-care workers) with quantitative RT-PCR-confirmed SARS-CoV-2 infection, and negative control serum samples collected from healthy adult blood donors before the start of the SARS-CoV-2 epidemic (335 samples from France, Thailand, and Peru). Machine learning classifiers were trained with the multiplex data to classify individuals with previous SARS-CoV-2 infection, with the best classification performance displayed by a random forests algorithm. A Bayesian mathematical model of antibody kinetics informed by prior information from other coronaviruses was used to estimate time-varying antibody responses and assess the sensitivity and classification performance of serological diagnostics during the first year following symptom onset. A statistical estimator is presented that can provide estimates of seroprevalence in very low-transmission settings.FindingsIgG antibody responses to trimeric spike protein (Stri) identified individuals with previous SARS-CoV-2 infection with 91·6% (95% CI 87·5–94·5) sensitivity and 99·1% (97·4–99·7) specificity. Using a serological signature of IgG and IgM to multiple antigens, it was possible to identify infected individuals with 98·8% (96·5–99·6) sensitivity and 99·3% (97·6–99·8) specificity. Informed by existing data from other coronaviruses, we estimate that 1 year after infection, a monoplex assay with optimal anti-Stri IgG cutoff has 88·7% (95% credible interval 63·4–97·4) sensitivity and that a four-antigen multiplex assay can increase sensitivity to 96·4% (80·9–100·0). When applied to population-level serological surveys, statistical analysis of multiplex data allows estimation of seroprevalence levels less than 2%, below the false-positivity rate of many other assays.InterpretationSerological signatures based on antibody responses to multiple antigens can provide accurate and robust serological classification of individuals with previous SARS-CoV-2 infection. This provides potential solutions to two pressing challenges for SARS-CoV-2 serological surveillance: classifying individuals who were infected more than 6 months ago and measuring seroprevalence in serological surveys in very low-transmission settings.FundingEuropean Research Council. Fondation pour la Recherche Médicale. Institut Pasteur Task Force COVID-19.