Underdetection of cases of COVID-19 in France threatens epidemic control.

As countries in Europe gradually relaxed lockdown restrictions after the first wave, test-trace-isolate strategies became critical to maintain the incidence of coronavirus disease 2019 (COVID-19) at low levels1,2. Reviewing their shortcomings can provide elements to consider in light of the second wave that is currently underway in Europe. Here we estimate the rate of detection of symptomatic cases of COVID-19 in France after lockdown through the use of virological3 and participatory syndromic4 surveillance data coupled with mathematical transmission models calibrated to regional hospitalizations2. Our findings indicate that around 90,000 symptomatic infections, corresponding to 9 out 10 cases, were not ascertained by the surveillance system in the first 7 weeks after lockdown from 11 May to 28 June 2020, although the test positivity rate did not exceed the 5% recommendation of the World Health Organization (WHO)5. The median detection rate increased from 7% (95% confidence interval, 6-8%) to 38% (35-44%) over time, with large regional variations, owing to a strengthening of the system as well as a decrease in epidemic activity. According to participatory surveillance data, only 31% of individuals with COVID-19-like symptoms consulted a doctor in the study period. This suggests that large numbers of symptomatic cases of COVID-19 did not seek medical advice despite recommendations, as confirmed by serological studies6,7. Encouraging awareness and same-day healthcare-seeking behaviour of suspected cases of COVID-19 is critical to improve detection. However, the capacity of the system remained insufficient even at the low epidemic activity achieved after lockdown, and was predicted to deteriorate rapidly with increasing incidence of COVID-19 cases. Substantially more aggressive, targeted and efficient testing with easier access is required to act as a tool to control the COVID-19 pandemic. The testing strategy will be critical to enable partial lifting of the current restrictive measures in Europe and to avoid a third wave.

An ensemble model based on early predictors to forecast COVID-19 health care demand in France.

Short-term forecasting of the COVID-19 pandemic is required to facilitate the planning of COVID-19 health care demand in hospitals. Here, we evaluate the performance of 12 individual models and 19 predictors to anticipate French COVID-19-related health care needs from September 7, 2020, to March 6, 2021. We then build an ensemble model by combining the individual forecasts and retrospectively test this model from March 7, 2021, to July 6, 2021. We find that the inclusion of early predictors (epidemiological, mobility, and meteorological predictors) can halve the rms error for 14-d­ahead forecasts, with epidemiological and mobility predictors contributing the most to the improvement. On average, the ensemble model is the best or second-best model, depending on the evaluation metric. Our approach facilitates the comparison and benchmarking of competing models through their integration in a coherent analytical framework, ensuring that avenues for future improvements can be identified.

Genome-Wide Association Study of Susceptibility to Pseudomonas aeruginosa Infection in Cystic Fibrosis.

QUESTION: Pseudomonas aeruginosa (Pa) is a common pathogen that contributes to progressive lung disease in Cystic Fibrosis (CF). Genetic factors other than CF-causing CFTR variations contribute approximately 85% of the variation in chronic Pa infection age in CF according to twin studies, but the susceptibility loci remain unknown. Our objective is to advance understanding of the genetic basis of host susceptibility to Pa infection. MATERIALS AND METHODS: We conducted a genome-wide association study (GWAS) of chronic Pa infection age in 1037 Canadians with CF. We subsequently assessed the genetic correlation between chronic Pa infection age and lung function through polygenic risk score (PRS) analysis and inferred their causal relationship through bi-directional Mendelian Randomization analysis. RESULTS: Two novel genome-wide significant loci with lead SNPs rs62369766 (chr5p12; p-value= 1.98 ×10-8) and rs927553 (chr13q12.12; p-value= 1.91 × 10-8) were associated with chronic Pa infection age. The rs62369766 locus was validated using an independent French cohort (N=501). Furthermore, PRS constructed from CF lung function-associated SNPs was significantly associated with chronic Pa infection age (p-value=0.002). Finally, our analysis presented evidence for a causal effect of lung function on the chronic Pa infection age (Beta=0.782 years, p-value= 4.24 × 10-4). In the reverse direction, we observed a moderate effect (Beta=0.002, p-value=0.012). CONCLUSIONS: We identified two novel loci that are associated with chronic Pa infection age in individuals with CF. Additionally, we provided evidence of common genetic contributors and a potential causal relationship between Pa infection susceptibility and lung function in CF. Therapeutics targeting these genetic factors may delay the onset of chronic infections which accounts for significant remaining morbidity in CF.

Epstein-Barr Virus and immune status imprint the immunogenomics of non-Hodgkin lymphomas occurring in immune-suppressed environments.

Non-Hodgkin lymphomas (NHL) commonly occur in immune-deficient (ID) patients, both HIV-infected and transplanted, and are often EBV-driven with cerebral localization, raising the question of tumor immunogenicity, a critical issue for treatment responses. We investigated the immunogenomics of 68 lymphoproliferative disorders from 51 ID (34 posttransplant, 17 HIV+) and 17 immunocompetent patients. Overall, 72% were Large B Cells Lymphoma (LBCL) and 25% were primary central-nervous-system lymphoma (PCNSL) while 40% were EBV-positive. Tumor whole-exome and RNA sequencing, along with a bioinformatics pipeline allowed analysis of tumor mutational burden (TMB), tumor landscape and microenvironment (TME) and prediction of tumor neoepitopes. Both TMB (2.2 vs 3.4/Mb, p=0.001) and neoepitopes numbers (40 vs 200, p=0.00019) were lower in EBVpositive than in EBV-negative NHL, regardless of the immune status. In contrast both EBV and the immune status influenced the tumor mutational profile, with HNRNPF and STAT3 mutations exclusively observed in EBV-positive and ID NHL, respectively. Peripheral blood T-cell responses against tumor neoepitopes were detected in all EBV-negative cases but in only half EBV-positive ones, including responses against IgH-derived MHC-class-II restricted neoepitopes. The TME analysis showed higher CD8 T cell infiltrates in EBVpositive vs EBV-negative NHL, together with a more tolerogenic profile composed of Tregs, type-M2 macrophages and an increased expression of negative immune-regulators. Our results highlight that the immunogenomics of NHL in patients with immunodeficiency primarily relies on the tumor EBV status, while T cell recognition of tumor- and IgH-specific neoepitopes is conserved in EBV-negative patients, offering potential opportunities for future T cell-based immune therapies.

Impact of Chemoprophylaxis on Plasmodium vivax and Plasmodium ovale Infection Among Civilian Travelers: A Nested Case-Control Study With a Counterfactual Approach on 862 Patients.

BACKGROUND: The impact of chemoprophylaxis targeting Plasmodium falciparum on Plasmodium vivax and Plasmodium ovale, which may remain quiescent as hypnozoites in the liver, is debated. METHODS: We conducted a nested case-control analysis of the outcomes of P. vivax and P. ovale infections in imported malaria cases in France among civilian travelers from 1 January 2006, to 31 December 2017. Using adjusted logistic regression, we assessed the effect of chemoprophylaxis on the incubation period, time from symptoms to diagnosis, management, blood results, symptoms, and hospitalization duration. We analyzed the effect of blood-stage drugs (doxycycline, mefloquine, chloroquine, chloroquine-proguanil) or atovaquone-proguanil on the incubation period. We used a counterfactual approach to ascertain the causal effect of chemoprophylaxis on postinfection characteristics. RESULTS: Among 247 P. vivax- and 615 P. ovale-infected travelers, 30% and 47%, respectively, used chemoprophylaxis, and 7 (3%) and 8 (1%) were severe cases. Chemoprophylaxis users had a greater risk of presenting symptoms >2 months after returning for both species (P. vivax odds ratio [OR], 2.91 [95% confidence interval {CI}, 1.22-6.95], P = .02; P. ovale OR, 2.28 [95% CI, 1.47-3.53], P < .001). Using drugs only acting on the blood stage was associated with delayed symptom onset after 60 days, while using atovaquone-proguanil was not. CONCLUSIONS: Civilian travelers infected with P. vivax or P. ovale reporting chemoprophylaxis use, especially of blood-stage agents, had a greater risk of delayed onset of illness. The impact of chemoprophylaxis on the outcomes of infection with relapse-causing species calls for new chemoprophylaxis acting against erythrocytic and liver stages.

Impact of non-pharmaceutical interventions, weather, vaccination, and variants on COVID-19 transmission across departments in France.

BACKGROUND: Multiple factors shape the temporal dynamics of the COVID-19 pandemic. Quantifying their relative contributions is key to guide future control strategies. Our objective was to disentangle the individual effects of non-pharmaceutical interventions (NPIs), weather, vaccination, and variants of concern (VOC) on local SARS-CoV-2 transmission. METHODS: We developed a log-linear model for the weekly reproduction number (R) of hospital admissions in 92 French metropolitan departments. We leveraged (i) the homogeneity in data collection and NPI definitions across departments, (ii) the spatial heterogeneity in the timing of NPIs, and (iii) an extensive observation period (14 months) covering different weather conditions, VOC proportions, and vaccine coverage levels. FINDINGS: Three lockdowns reduced R by 72.7% (95% CI 71.3-74.1), 70.4% (69.2-71.6) and 60.7% (56.4-64.5), respectively. Curfews implemented at 6/7 pm and 8/9 pm reduced R by 34.3% (27.9-40.2) and 18.9% (12.04-25.3), respectively. School closures reduced R by only 4.9% (2.0-7.8). We estimated that vaccination of the entire population would have reduced R by 71.7% (56.4-81.6), whereas the emergence of VOC (mainly Alpha during the study period) increased transmission by 44.6% (36.1-53.6) compared with the historical variant. Winter weather conditions (lower temperature and absolute humidity) increased R by 42.2% (37.3-47.3) compared to summer weather conditions. Additionally, we explored counterfactual scenarios (absence of VOC or vaccination) to assess their impact on hospital admissions. INTERPRETATION: Our study demonstrates the strong effectiveness of NPIs and vaccination and quantifies the role of weather while adjusting for other confounders. It highlights the importance of retrospective evaluation of interventions to inform future decision-making.

Computerized decision support system (CDSS) use for surveillance of antimicrobial resistance in urinary tract infections in primary care.

BACKGROUND: Hospital-based surveillance of antimicrobial resistance may be irrelevant as a guide to antimicrobial use for urinary tract infections (UTIs) in primary care. OBJECTIVES: To highlight the value of online computerized decision support systems (CDSS) in providing information on the surveillance of antimicrobial resistance in community-acquired UTIs. METHODS: We collected the susceptibility profile for key antibiotics by type of UTI involving Escherichia coli from 2017 to 2020, using queries for UTI (Q-UTI) submitted to a French CDSS. We compared these results with those from the MedQual French surveillance system for community-acquired UTI and the European Antimicrobial Resistance Surveillance Network (EARS-NET) for invasive infections. RESULTS: We collected 43 591 Q-UTI, of which 10 192 (23%) involved E. coli: 40% cystitis, 32% male-UTI, and 27% pyelonephritis. Resistance was 41.3% (95% CI, 40.3%-42.2%) for amoxicillin, 16.6% (95% CI, 15.9%-17.3%) for fluoroquinolones, 6.6% (95% CI, 6.1%-7.0%) for third-generation cephalosporins (3GC), and 5.7% (95% CI, 5.2%-6.1%) for aminoglycosides. Resistance to amoxicillin was lower than that reported in MedQual (42.7%, P value = 0.004), and in EARS-NET (55.2%, P value < 0.001). For fluoroquinolones, resistance was higher than in MedQual (12.0%, P value < 0.001) and EARS-NET (15.8%, P value = 0.041). In complicated pyelonephritis and male UTI, fluoroquinolone resistance peaked at ∼20%. For 3GC, all UTI had higher resistance than in MedQual (3.5%, P value < 0.001), but lower than in EARS-NET (9.5%, P value < 0.001). Aminoglycoside resistance was not reported by MedQual, and was lower than in EARS-NET (7.1%, P value < 0.001). CONCLUSIONS: CDSS can inform prescribers in real-time about the ecology and surveillance of E. coli resistance in community-acquired UTI. In complicated upper UTIs, they can underline the risk of empirical use of fluoroquinolones and suggest preferential use of 3GC.

Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19. METHODS: We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk. FINDINGS: Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively. INTERPRETATION: Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission. FUNDING: EU Framework Programme for Research and Innovation Horizon 2020, Agence Nationale de la Recherche.

Benefits and risks associated with different uses of the COVID-19 vaccine Vaxzevria: a modelling study, France, May to September 2021.

Thrombosis with thrombocytopenia (TTS) has been identified as a rare adverse event following COVID-19 vaccination with Vaxzevria. We modelled the benefits and risks of Vaxzevria distribution from May to September 2021 in metropolitan France where other vaccines are available, considering French hospitalisation data and European data on TTS. Across different scenarios, benefits of Vaxzevria distribution in people 55 years and older exceeded the risk of death from COVID-19. In young adults, risks were at least of similar magnitude as benefits.

Lockdown as a last resort option in case of COVID-19 epidemic rebound: a modelling study.

BackgroundGiven its high economic and societal cost, policymakers might be reluctant to implement a large-scale lockdown in case of coronavirus disease (COVID-19) epidemic rebound. They may consider it as a last resort option if alternative control measures fail to reduce transmission.AimWe developed a modelling framework to ascertain the use of lockdown to ensure intensive care unit (ICU) capacity does not exceed a peak target defined by policymakers.MethodsWe used a deterministic compartmental model describing transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the trajectories of COVID-19 patients in healthcare settings, accounting for age-specific mixing patterns and an increasing probability of severe outcomes with age. The framework is illustrated in the context of metropolitan France.ResultsThe daily incidence of ICU admissions and the number of occupied ICU beds are the most robust indicators to decide when a lockdown should be triggered. When the doubling time of hospitalisations estimated before lockdown is between 8 and 20 days, lockdown should be enforced when ICU admissions reach 3.0-3.7 and 7.8-9.5 per million for peak targets of 62 and 154 ICU beds per million (4,000 and 10,000 beds for metropolitan France), respectively. When implemented earlier, the lockdown duration required to get back below a desired level is also shorter.ConclusionsWe provide simple indicators and triggers to decide if and when a last-resort lockdown should be implemented to avoid saturation of ICU. These metrics can support the planning and real-time management of successive COVID-19 pandemic waves.

Lockdown impact on age-specific contact patterns and behaviours, France, April 2020.

BackgroundMany countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity.AimWe aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours.MethodsWe conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020.ResultAmong the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%.ConclusionThe lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.

Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study.

BACKGROUND: In the early months of 2020, a novel coronavirus disease (COVID-19) spread rapidly from China across multiple countries worldwide. As of March 17, 2020, COVID-19 was officially declared a pandemic by the World Health Organization. We collected data on COVID-19 cases outside China during the early phase of the pandemic and used them to predict trends in importations and quantify the proportion of undetected imported cases. METHODS AND FINDINGS: Two hundred and eighty-eight cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized the importation timeline to assess the rapidity of isolation and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, corresponding to a doubling time of 2.8 days, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the successive weeks. Time from travel to detection has considerably decreased since first importation, from 14.5 ± 5.5 days on January 5, 2020, to 6 ± 3.5 days on February 1, 2020. However, we estimated 36% of detection of imported cases. This study is restricted to the early phase of the pandemic, when China was the only large epicenter and foreign countries had not discovered extensive local transmission yet. Missing information in case history was accounted for through modeling and imputation. CONCLUSIONS: Our findings indicate that travel bans and containment strategies adopted in China were effective in reducing the exportation growth rate. However, the risk of importation was estimated to increase again from other sources in South East Asia. Surveillance and management of traveling cases represented a priority in the early phase of the epidemic. With the majority of imported cases going undetected (6 out of 10), countries experienced several undetected clusters of chains of local transmissions, fueling silent epidemics in the community. These findings become again critical to prevent second waves, now that countries have reduced their epidemic activity and progressively phase out lockdown.

Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies.

BACKGROUND: More than half of the global population is under strict forms of social distancing. Estimating the expected impact of lockdown and exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis. METHODS: We use a stochastic age-structured transmission model integrating data on age profile and social contacts in Île-de-France to (i) assess the epidemic in the region, (ii) evaluate the impact of lockdown, and (iii) propose possible exit strategies and estimate their effectiveness. The model is calibrated to hospital admission data before lockdown. Interventions are modeled by reconstructing the associated changes in the contact matrices and informed by mobility reductions during lockdown evaluated from mobile phone data. Different types and durations of social distancing are simulated, including progressive and targeted strategies, with large-scale testing. RESULTS: We estimate the reproductive number at 3.18 [3.09, 3.24] (95% confidence interval) prior to lockdown and at 0.68 [0.66, 0.69] during lockdown, thanks to an 81% reduction of the average number of contacts. Model predictions capture the disease dynamics during lockdown, showing the epidemic curve reaching ICU system capacity, largely strengthened during the emergency, and slowly decreasing. Results suggest that physical contacts outside households were largely avoided during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave overwhelming the healthcare system, if conditions return to normal. Extensive case finding and isolation are required for social distancing strategies to gradually relax lockdown constraints. CONCLUSIONS: As France experiences the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.

A computerized decision support system (CDSS) for antibiotic prescription in primary care-Antibioclic: implementation, adoption and sustainable use in the era of extended antimicrobial resistance.

OBJECTIVES: To describe the implementation and use of a computerized decision support system (CDSS) for antibiotic prescription in primary care in France (Antibioclic). The CDSS targets 37 infectious diseases and has been freely available on a website since 2011. METHODS: Description and implementation of the architecture of a CDSS for antibiotic prescription in general practice. Analysis of the queries made between 2012 and 2018 on the CDSS by GPs. Analysis of two cross-sectional studies of users in 2014 and 2019. RESULTS: The number of queries increased from a median of 796/day [IQR, 578-989] in 2012 to 11 125/day [5592-12 505] in 2018. Unique users increased from 414/day [245-494] in 2012 to 5365/day [2891-5769] in 2018. Time taken to make a query was 2 min [1.9-2.1]. Among 3 542 347 queries in 2018, 78% were for adults. Six situations accounted for ≥50% of queries: cystitis; acute otitis media; acute sinusitis; community-acquired pneumonia; sore throat; and pyelonephritis. Queries concerned pathologies for which antibiotic prescription was necessary (64%), was conditional on additional clinical steps (34%) or was not recommended (2%). Most users (81%) were GPs, with median age of 38 years [31-52] and 58% were female. Among the 4016 GPs who responded to the surveys, the vast majority (96%) reported using the CDSS during the consultation, with 24% systematically using Antibioclic to initiate an antibiotic course and 93% having followed the CDSS recommendation for the latest prescription. Most GPs were comfortable using the CDSS in front of a patient. CONCLUSIONS: Antibioclic has been adopted and is widely used in primary care in France. Its interoperability could allow its adaptation and implementation in other countries.

Cystic Fibrosis Liver Disease: Outcomes and Risk Factors in a Large Cohort of French Patients.

Cystic fibrosis (CF)-related liver disease (CFLD) is a common symptom in patients with CF. However, its prevalence, risk factors, and evolution are unclear. We analyzed a large database of patients with CF to investigate the incidence of CFLD, its related risk factors, and the use and effect of ursodeoxycholic acid (UDCA) treatment. We retrospectively analyzed 3,328 CF patients with pancreatic insufficiency born after 1985 and recruited into the French CF Modifier Gene Study since 2004. We determined liver status, age at CFLD and severe CFLD onset, sex, CFTR genotype, history of meconium ileus, treatment with UDCA, and respiratory and nutritional status. The incidence of CFLD increased by approximately 1% every year, reaching 32.2% by age 25. The incidence of severe CFLD increased only after the age of 5, reaching 10% by age 30. Risk factors for CFLD and severe CFLD were male sex, CFTR F508del homozygosity, and history of meconium ileus. Increasingly precocious initiation of UDCA treatment did not change the incidence of severe CFLD. Finally, patients with severe CFLD had worse lung function and nutritional status than other CF patients. Conclusion: CFLD occurs not only during childhood but also later in the lifetime of patients with CF; male sex, CFTR F508del homozygosity, and history of meconium ileus are independent risk factors for CFLD development; earlier use of UDCA over the last 20 years has not changed the incidence of severe CFLD, leading to questions about the use of this treatment in young children given its possible adverse effects.

Host contact dynamics shapes richness and dominance of pathogen strains.

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains.

Close proximity interactions support transmission of ESBL-K. pneumoniae but not ESBL-E. coli in healthcare settings.

Antibiotic-resistance of hospital-acquired infections is a major public health issue. The worldwide emergence and diffusion of extended-spectrum ß-lactamase (ESBL)-producing Enterobacteriaceae, including Escherichia coli (ESBL-EC) and Klebsiella pneumoniae (ESBL-KP), is of particular concern. Preventing their nosocomial spread requires understanding their transmission. Using Close Proximity Interactions (CPIs), measured by wearable sensors, and weekly ESBL-EC-and ESBL-KP-carriage data, we traced their possible transmission paths among 329 patients in a 200-bed long-term care facility over 4 months. Based on phenotypically defined resistance profiles to 12 antibiotics only, new bacterial acquisitions were tracked. Extending a previously proposed statistical method, the CPI network's ability to support observed incident-colonization episodes of ESBL-EC and ESBL-KP was tested. Finally, mathematical modeling based on our findings assessed the effect of several infection-control measures. A potential infector was identified in the CPI network for 80% (16/20) of ESBL-KP acquisition episodes. The lengths of CPI paths between ESBL-KP incident cases and their potential infectors were shorter than predicted by chance (P = 0.02), indicating that CPI-network relationships were consistent with dissemination. Potential ESBL-EC infectors were identified for 54% (19/35) of the acquisitions, with longer-than-expected lengths of CPI paths. These contrasting results yielded differing impacts of infection control scenarios, with contact reduction interventions proving less effective for ESBL-EC than for ESBL-KP. These results highlight the widely variable transmission patterns among ESBL-producing Enterobacteriaceae species. CPI networks supported ESBL-KP, but not ESBL-EC spread. These outcomes could help design more specific surveillance and control strategies to prevent in-hospital Enterobacteriaceae dissemination.

Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020.

As at 27 January 2020, 42 novel coronavirus (2019-nCoV) cases were confirmed outside China. We estimate the risk of case importation to Europe from affected areas in China via air travel. We consider travel restrictions in place, three reported cases in France, one in Germany. Estimated risk in Europe remains high. The United Kingdom, Germany and France are at highest risk. Importation from Beijing and Shanghai would lead to higher and widespread risk for Europe.

Excess cases of influenza-like illnesses synchronous with coronavirus disease (COVID-19) epidemic, France, March 2020.

Several French regions where coronavirus disease (COVID-19) has been reported currently show a renewed increase in ILI cases in the general practice-based Sentinelles network. We computed the number of excess cases by region from 24 February to 8 March 2020 and found a correlation with the number of reported COVID-19 cases so far. The data suggest larger circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the French population than apparent from confirmed cases.

Classification of Spatiotemporal Data for Epidemic Alert Systems: Monitoring Influenza-Like Illness in France.

Surveillance data used by epidemic alert systems are typically fully aggregated in space at the national level. However, epidemics may be spatially heterogeneous, undergoing distinct dynamics in distinct regions of the surveillance area. We unveiled this in retrospective analyses by classifying incidence time series. We used Pearson correlation to quantify the similarity between local time series and then classified them using modularity maximization. The surveillance area was thus divided into regions with different incidence patterns. We analyzed 31 years (1985-2016) of data on influenza-like illness from the French Sentinelles system and found spatial heterogeneity in 19 of 31 influenza seasons. However, distinct epidemic regions could be identified only 4-5 weeks after a nationwide alert. The impact of spatial heterogeneity on influenza epidemiology was complex. First, when a nationwide alert was triggered, 32%-41% of the administrative regions of France were experiencing an epidemic, while the others were not. Second, the nationwide alert was timely for the whole surveillance area, but subsequently regions experienced distinct epidemic dynamics. Third, the epidemic dynamics were homogeneous in space. Spatial heterogeneity analyses can provide information on the timing of the peak and end of the epidemic, in various regions, for use in tailoring disease monitoring and control.