Using contact network dynamics to implement efficient interventions against pathogen spread in hospital settings: A modelling study.

BACKGROUND: Long-term care facilities (LTCFs) are hotspots for pathogen transmission. Infection control interventions are essential, but the high density and heterogeneity of interindividual contacts within LTCF may hinder their efficacy. Here, we explore how the patient-staff contact structure may inform effective intervention implementation. METHODS AND FINDINGS: Using an individual-based model (IBM), we reproduced methicillin-resistant Staphylococcus aureus colonisation transmission dynamics over a detailed contact network recorded within a French LTCF of 327 patients and 263 staff over 3 months. Simulated baseline cumulative colonisation incidence was 21 patients (prediction interval: 11, 31) and 35 staff (prediction interval: 19, 54). We examined the potential impact of 3 types of interventions against transmission (reallocation reducing the number of unique contacts per staff, reinforced contact precautions, and hypothetical vaccination protecting against acquisition), targeted towards specific populations. All 3 interventions were effective when applied to all nurses or healthcare assistants (median reduction in MRSA colonisation incidence up to 35%), but the benefit did not exceed 8% when targeting any other single staff category. We identified "supercontactor" individuals with most contacts ("frequency-based," overrepresented among nurses, porters, and rehabilitation staff) or with the longest cumulative time spent in contact ("duration-based," overrepresented among healthcare assistants and patients in elderly care or persistent vegetative state (PVS)). Targeting supercontactors enhanced interventions against pathogen spread in the LTCF. With contact precautions, targeting frequency-based staff supercontactors led to the highest incidence reduction (20%, 95% CI: 19, 21). Vaccinating a mix of frequency- and duration-based staff supercontactors led to a higher reduction (23%, 95% CI: 22, 24) than all other approaches. Although based on data from a single LTCF, when varying epidemiological parameters to extend to other pathogens, our results suggest that targeting supercontactors is always the most effective strategy, indicating this approach could be applied to prevent transmission of other nosocomial pathogens. CONCLUSIONS: By characterising the contact structure in hospital settings and identifying the categories of staff and patients more likely to be supercontactors, with either more or longer contacts than others, interventions against nosocomial spread could be more effective. We find that the most efficient implementation strategy depends on the intervention (reallocation, contact precautions, vaccination) and target population (staff, patients, supercontactors). Importantly, both staff and patients may be supercontactors, highlighting the importance of including patients in measures to prevent pathogen transmission in LTCF.

Paris 2024 Olympic Games: A risk enhancer for autochthonous arboviral diseases epidemics?

OBJECTIVES: The anticipated increase in international tourist flows and the first locally acquired dengue cases in the Paris region in October 2023 have raised concerns about potential arbovirus outbreaks during the 2024 Olympics. Unlike previous mass sporting events at risk of arbovirus outbreaks, Paris is a nonendemic arbovirus area, requiring a unique investigation. METHODS: Therefore, we analyzed factors conducive to possible arbovirus epidemics in temperate regions: vector distribution in the Paris area, seasonal global arboviral disease patterns, projected visitor demographics, and international flight bookings. RESULTS AND CONCLUSION: Our results suggest that the expected visitors' profile for the summer of 2024 should not increase the risk of arbovirus importation into the Paris region compared to a typical year. Conversely, the primary risk of arbovirus outbreaks is likely to come from within France, particularly from the French West Indies, where a notable, albeit declining, dengue outbreak is underway. Vigilant surveillance by French health authorities will ensure that this trend continues.

An algorithm to build synthetic temporal contact networks based on close-proximity interactions data.

Small populations (e.g., hospitals, schools or workplaces) are characterised by high contact heterogeneity and stochasticity affecting pathogen transmission dynamics. Empirical individual contact data provide unprecedented information to characterize such heterogeneity and are increasingly available, but are usually collected over a limited period, and can suffer from observation bias. We propose an algorithm to stochastically reconstruct realistic temporal networks from individual contact data in healthcare settings (HCS) and test this approach using real data previously collected in a long-term care facility (LTCF). Our algorithm generates full networks from recorded close-proximity interactions, using hourly inter-individual contact rates and information on individuals' wards, the categories of staff involved in contacts, and the frequency of recurring contacts. It also provides data augmentation by reconstructing contacts for days when some individuals are present in the HCS without having contacts recorded in the empirical data. Recording bias is formalized through an observation model, to allow direct comparison between the augmented and observed networks. We validate our algorithm using data collected during the i-Bird study, and compare the empirical and reconstructed networks. The algorithm was substantially more accurate to reproduce network characteristics than random graphs. The reconstructed networks reproduced well the assortativity by ward (first-third quartiles observed: 0.54-0.64; synthetic: 0.52-0.64) and the hourly staff and patient contact patterns. Importantly, the observed temporal correlation was also well reproduced (0.39-0.50 vs 0.37-0.44), indicating that our algorithm could recreate a realistic temporal structure. The algorithm consistently recreated unobserved contacts to generate full reconstructed networks for the LTCF. To conclude, we propose an approach to generate realistic temporal contact networks and reconstruct unobserved contacts from summary statistics computed using individual-level interaction networks. This could be applied and extended to generate contact networks to other HCS using limited empirical data, to subsequently inform individual-based epidemic models.

Exploring factors shaping antibiotic resistance patterns in Streptococcus pneumoniae during the 2020 COVID-19 pandemic.

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

Preventing iatrogenic HCV infection: A quantitative risk assessment based on observational data in an Egyptian hospital.

When compliance with infection control recommendations is non-optimal, hospitals may play an important role in hepatitis C (HCV) transmission. However, few studies have analyzed the nosocomial HCV acquisition risk based on detailed empirical data. Here, we used data from a prospective cohort study conducted on 500 patients in the Ain Shams hospital (Cairo, Egypt) in 2017 with the objective of identifying (i) high-risk patient profiles and (ii) transmission hotspots within the hospital. Data included information on patient HCV status upon admission, their trajectories between wards and the invasive procedures they underwent. We first performed a sequence analysis to identify different hospitalization profiles. Second, we estimated each patient's individual risk of HCV acquisition based on ward-specific prevalence and procedures undergone, and risk hotspots by computing ward-level risks. Then, using a beta regression model, we evaluated upon-admission factors linked to HCV acquisition risk and built a score estimating the risk of HCV infection during hospitalization based on these factors. Finally, we assessed and compared ward-focused and patient-focused HCV control strategies. The sequence analysis based on patient trajectories allowed us to identify four distinct patient trajectory profiles. The risk of HCV infection was greater in the internal medicine department, compared to the surgery department (0·188% [0·142%-0·235%] vs. 0·043%, CI 95%: [0·036%-0·050%]), with risk hotspots in the geriatric, tropical medicine and intensive-care wards. Upon-admission risk predictors included source of admission, age, reason for hospitalization, and medical history. Interventions focused on the most at-risk patients were most effective to reduce HCV infection risk. Our results might help reduce the risk of HCV acquisition during hospitalization in Egypt by targeting enhanced control measures to ward-level transmission hotspots and to at-risk patients identified upon admission.

Assessing respiratory epidemic potential in French hospitals through collection of close contact data (April-June 2020).

The transmission risk of SARS-CoV-2 within hospitals can exceed that in the general community because of more frequent close proximity interactions (CPIs). However, epidemic risk across wards is still poorly described. We measured CPIs directly using wearable sensors given to all present in a clinical ward over a 36-h period, across 15 wards in three hospitals in April-June 2020. Data were collected from 2114 participants and combined with a simple transmission model describing the arrival of a single index case to the ward to estimate the risk of an outbreak. Estimated epidemic risk ranged four-fold, from 0.12 secondary infections per day in an adult emergency to 0.49 per day in general paediatrics. The risk presented by an index case in a patient varied 20-fold across wards. Using simulation, we assessed the potential impact on outbreak risk of targeting the most connected individuals for prevention. We found that targeting those with the highest cumulative contact hours was most impactful (20% reduction for 5% of the population targeted), and on average resources were better spent targeting patients. This study reveals patterns of interactions between individuals in hospital during a pandemic and opens new routes for research into airborne nosocomial risk.

Identifying individual and organizational predictors of accidental exposure to blood (AEB) among hospital healthcare workers: A longitudinal study.

BACKGROUND: Accidental exposure to blood (AEB) poses a risk of bloodborne infections for healthcare workers (HCWs) during hospital activities. In this study, we identified individual behavioral and organizational predictors of AEB among HCWs. METHODS: The study was a prospective, 1-year follow-up cohort study conducted in university hospitals in Paris, France. Data were collected from the Stress at Work and Infectious Risk in Patients and Caregivers (STRIPPS) study. Eligible participants included nurses, nursing assistants, midwives, and physicians from 32 randomly selected wards in 4 hospitals. AEB occurrences were reported at baseline, 4 months, 8 months, and 12 months, and descriptive statistical and multilevel risk-factor analyses were performed. RESULTS: The study included 730 HCWs from 32 wards, predominantly nurses (52.6%), nursing assistants (41.1%), physicians (4.8%), and midwives (1.5%). The incidence rate of AEB remained stable across the 4 visits. The multilevel longitudinal analysis identified several significant predictors of AEB occurrence. Individual-level predictors included younger age, occupation as nurses or midwives, irregular work schedule, rotating shifts, and lack of support from supervisors. The use of external nurses was the most significant ward-level predictor associated with AEB occurrence. CONCLUSIONS: AEBs among HCWs are strongly associated with organizational predictors, highlighting the importance of complementing infection control policies with improved staff management and targeted training. This approach can help reduce AEB occurrences and enhance workplace safety for HCWs.

Investigating inequalities in HIV testing in sub-Saharan Africa: spatial analysis of cross-sectional population-based surveys in 25 countries.

OBJECTIVES: We aim to explore spatial variations in socioeconomic inequalities in HIV testing uptake in sub-Saharan Africa (SSA) at different geographical scales to identify potential geographical hotspots of inequalities. Additionally, to evaluate the potential benefits of HIV testing programmes, we assess whether local levels of HIV testing match the local levels of HIV prevalence. DESIGN: A multi-country analysis of population-based cross-sectional surveys in SSA. SETTING: We analysed data from 25 SSA countries with Demographic and Health Surveys between 2011 and 2019. PARTICIPANTS: Country-level analysis included 473 775 participants (312 104 women and 161 671 men) and cluster-level analysis included 328 283 individuals (241 084 women and 87 199 men). Women aged 15-49 years and men aged 15-54/59 years in selected households who were tested for HIV in the last 12 months were eligible. We quantified inequalities in self-reported recent HIV testing with the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII) across geographical scales to capture sex-specific within-country spatial variations. We also conducted local Getis-Ord Gi* statistics to consider the autocorrelation in fine-scale SII and RII across countries. To assess the efficiency of HIV testing programmes, we measured the correlation between recent HIV testing and HIV prevalence through Spearman correlation across geographical scales. RESULTS: We observed varying inequalities in recent HIV testing in magnitude and spatial distribution on both absolute and relative scales in many countries for both sexes at national and subnational levels. Hotspots of absolute and relative inequalities were mostly observed in Western and Central Africa with a few regions in Eastern and Southern Africa. Despite significant sex-specific correlations between testing and prevalence in all countries when assessed at the national level, we report an absence of such a correlation at fine scale in 17 of 50 sex-country combinations. CONCLUSIONS: We highlight the importance of investigating the spatial variability of various HIV indicators and related inequalities across different geographical levels. Results may help inform an equitable distribution of HIV testing services.

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study.

BACKGROUND: Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. We sought to evaluate how such collateral impacts of COVID-19 impacted the nosocomial spread of MRB in an early pandemic context. METHODS AND FINDINGS: We developed a mathematical model in which Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and MRB cocirculate among patients and staff in a theoretical hospital population. Responses to COVID-19 were captured mechanistically via a range of parameters that reflect impacts of SARS-CoV-2 outbreaks on factors relevant for pathogen transmission. COVID-19 responses include both "policy responses" willingly enacted to limit SARS-CoV-2 transmission (e.g., universal masking, patient lockdown, and reinforced hand hygiene) and "caseload responses" unwillingly resulting from surges in COVID-19 caseloads (e.g., abandonment of antibiotic stewardship, disorganization of infection control programmes, and extended length of stay for COVID-19 patients). We conducted 2 main sets of model simulations, in which we quantified impacts of SARS-CoV-2 outbreaks on MRB colonization incidence and antibiotic resistance rates (the share of colonization due to antibiotic-resistant versus antibiotic-sensitive strains). The first set of simulations represents diverse MRB and nosocomial environments, accounting for high levels of heterogeneity across bacterial parameters (e.g., rates of transmission, antibiotic sensitivity, and colonization prevalence among newly admitted patients) and hospital parameters (e.g., rates of interindividual contact, antibiotic exposure, and patient admission/discharge). On average, COVID-19 control policies coincided with MRB prevention, including 28.2% [95% uncertainty interval: 2.5%, 60.2%] fewer incident cases of patient MRB colonization. Conversely, surges in COVID-19 caseloads favoured MRB transmission, resulting in a 13.8% [-3.5%, 77.0%] increase in colonization incidence and a 10.4% [0.2%, 46.9%] increase in antibiotic resistance rates in the absence of concomitant COVID-19 control policies. When COVID-19 policy responses and caseload responses were combined, MRB colonization incidence decreased by 24.2% [-7.8%, 59.3%], while resistance rates increased by 2.9% [-5.4%, 23.2%]. Impacts of COVID-19 responses varied across patients and staff and their respective routes of pathogen acquisition. The second set of simulations was tailored to specific hospital wards and nosocomial bacteria (methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase producing Escherichia coli). Consequences of nosocomial SARS-CoV-2 outbreaks were found to be highly context specific, with impacts depending on the specific ward and bacteria evaluated. In particular, SARS-CoV-2 outbreaks significantly impacted patient MRB colonization only in settings with high underlying risk of bacterial transmission. Yet across settings and species, antibiotic resistance burden was reduced in facilities with timelier implementation of effective COVID-19 control policies. CONCLUSIONS: Our model suggests that surges in nosocomial SARS-CoV-2 transmission generate selection for the spread of antibiotic-resistant bacteria. Timely implementation of efficient COVID-19 control measures thus has 2-fold benefits, preventing the transmission of both SARS-CoV-2 and MRB, and highlighting antibiotic resistance control as a collateral benefit of pandemic preparedness.

Sick leave due to COVID-19 during the first pandemic wave in France, 2020.

OBJECTIVES: To quantify the burden of COVID-19-related sick leave during the first pandemic wave in France, accounting for sick leaves due to symptomatic COVID-19 ('symptomatic sick leaves') and those due to close contact with COVID-19 cases ('contact sick leaves'). METHODS: We combined data from a national demographic database, an occupational health survey, a social behaviour survey and a dynamic SARS-CoV-2 transmission model. Sick leave incidence from 1 March 2020 to 31 May 2020 was estimated by summing daily probabilities of symptomatic and contact sick leaves, stratified by age and administrative region. RESULTS: There were an estimated 1.70M COVID-19-related sick leaves among France's 40M working-age adults during the first pandemic wave, including 0.42M due to COVID-19 symptoms and 1.28M due to COVID-19 contacts. There was great geographical variation, with peak daily sick leave incidence ranging from 230 in Corse (Corsica) to 33 000 in Île-de-France (the greater Paris region), and greatest overall burden in regions of north-eastern France. Regional sick leave burden was generally proportional to local COVID-19 prevalence, but age-adjusted employment rates and contact behaviours also contributed. For instance, 37% of symptomatic infections occurred in Île-de-France, but 45% of sick leaves. Middle-aged workers bore disproportionately high sick leave burden, owing predominantly to greater incidence of contact sick leaves. CONCLUSIONS: France was heavily impacted by sick leave during the first pandemic wave, with COVID-19 contacts accounting for approximately three-quarters of COVID-19-related sick leaves. In the absence of representative sick leave registry data, local demography, employment patterns, epidemiological trends and contact behaviours can be synthesised to quantify sick leave burden and, in turn, predict economic consequences of infectious disease epidemics.

A new ranking index to identify the work-related psychosocial factors most impacting mental health: a cross-sectional study.

OBJECTIVES: In modern professional life, mental health prevention and promotion have become a major challenge for decision-makers. Devising appropriate actions requires better understanding the role played by each work-related psychosocial factor (WPSF). The objective of this study was to present a relevant tool to hierarchise WPSFs that jointly takes into account their importance (impact on mental health) and their prevalence (the proportion of the population exposed to WPSF). DESIGN: A cross-sectional study was conducted in March 2018 among 3200 French workers which are representative of the French working population. SETTING: France. PARTICIPANTS: Individuals aged 18-80 years who declared currently having a job (even a part-time job) whatever their occupation or status (employee or self-employed) were eligible. We excluded students, unemployed individuals, housewives/husbands and retired people. The mental health level was assessed using the General Health Questionnaire-28 and 44 items were gathered from theoretical models of WPSFs. We assessed two distinct multivariate methods for calculating WPSF importance: (1) weifila (weighted first last) method in a linear regression context and (2) random forests in a non-linear context. Both methods were adjusted on individual, health and job characteristics. RESULTS: The WPSF rankings obtained with the two methods to calculate importance are strongly consistent with each other (correlation coefficient=0.88). We highlighted nine WPSFs that are ranked high by both methods. In particular, irrespective of the chosen method, lack of communication, lack of social and hierarchy support and personal-professional life imbalance, emotional demands at work and dissatisfaction with the compensation received came out as top-ranking WPSFs. CONCLUSIONS: A total of nine WPSFs were identified as key for decision-making. The easy-to-use tools we propose can help decision-makers identify priority WPSFs and design effective strategies to promote mental health in the workplace.

Estimating the risk of incident SARS-CoV-2 infection among healthcare workers in quarantine hospitals: the Egyptian example.

In response to the COVID-19 epidemic, Egypt established a unique care model based on quarantine hospitals where only externally-referred confirmed COVID-19 patients were admitted, and healthcare workers resided continuously over 1- to 2-week working shifts. Using a mathematical model accounting for the false-negative rates of RT-PCR tests, we computed the incidence rate of SARS-CoV-2 infection among HCWs, while unveiling the proportion of infections remaining undiagnosed despite routine testing. We relied on longitudinal data, including results of routine RT-PCR tests, collected within three Egyptian quarantine hospitals. We estimated an incidence rate (per 100 person-day, PD) of 1.05 (95% CrI 0.58-1.65) at Hospital 1, 1.92 (95% CrI 0.93-3.28) at Hospital 2 and 7.62 (95% CrI 3.47-13.70) at Hospital 3. We found that the risk for an HCW to be infected during a working shift lay within the range of risk levels previously documented in standard healthcare settings for Hospitals 1-2, whereas it was > threefold higher for Hospital 3. This large variation suggests that HCWs from quarantine hospitals may face a high occupational risk of infection, but that, with sufficient infection control measures, this risk can be brought down to levels similar to those observed in standard healthcare settings.

Multilevel approach to individual and organisational predictors of stress and fatigue among healthcare workers of a university hospital: a longitudinal study.

OBJECTIVE: Healthcare workers (HCWs) are at high risk of experiencing stress and fatigue due to the demands of their work within hospitals. Improving their physical and mental health and, in turn, the quality and safety of care requires considering factors at both individual and organisational/ward levels. Using a multicentre prospective cohort, this study aims to identify the individual and organisational predictors of stress and fatigue of HCWs in several wards from university hospitals. METHODS: Our cohort consists of 695 HCWs from 32 hospital wards drawn at random within four volunteer hospital centres in Paris-area. Three-level longitudinal analyses, accounting for repeated measures (level 1) across participants (level 2) nested within wards (level 3) and adjusted for relevant fixed and time-varying confounders, were performed. RESULTS: At baseline, the sample was composed by 384 registered nurses, 300 auxiliary nurses and 11 midwives. According to the three-level longitudinal models, some predictors were found in common for both stress and fatigue (low social support from supervisors, work overcommitment, sickness presenteeism and number of beds per ward). However, specific predictors for high level of stress (negative life events, low social support from colleagues and breaks frequently cancelled due to work overload) and fatigue (longer commuting duration, frequent use of interim staff in the ward) were also found. CONCLUSION: Our results may help identify at-risk HCWs and wards, where interventions to reduce stress and fatigue should be focused. These interventions could include manager training to favour better staff support and overall safety culture of HCWs.

Understanding the pathways leading to socioeconomic inequalities in HIV testing uptake in 18 sub-Saharan African countries.

OBJECTIVE: To better understand the different pathways linking socioeconomic position and HIV testing uptake in 18 sub-Saharan African countries. DESIGN: We used cross-sectional population-based surveys between 2010 and 2018. METHODS: Using a potential outcomes framework and the product method, we decomposed the total effect linking wealth and recent (<12 months) HIV testing into direct effects, and indirect effects, via internal (related to individual's ability to perceive need for and to seek care) or external (ability to reach, pay for and engage in healthcare) mediators to calculate the proportion mediated (PM) by each mediator. RESULTS: High levels of inequalities were observed in nine and 15 countries among women and men, respectively. The mediator indirect effect varied greatly across countries. The PM tended to be higher for internal than for external mediators. For instance, among women, HIV-related knowledge was estimated to mediate up to 12.1% of inequalities in Côte d'Ivoire; and up to 31.5% for positive attitudes towards people with HIV (PWH) in Senegal. For the four external mediators, the PM was systematically below 7%. Similar findings were found when repeating analyses on men for the internal mediators, with higher PM by attitudes towards PWH (up to 39.9% in Senegal). CONCLUSIONS: Our findings suggest that wealth-related inequalities in HIV testing may be mediated by internal more than external characteristics, with important variability across countries. Overall, the important heterogeneities in the pathways of wealth-related inequalities in HIV testing illustrate that addressing inequalities requires tailored efforts and upstream interventions.

Meta-analysis: risk of hepatitis C virus infection associated with hospital-based invasive procedures.

BACKGROUND: Healthcare settings, where invasive procedures are frequently performed, may play an important role in the transmission dynamics of blood-borne pathogens when compliance with infection control precautions is suboptimal. AIMS: To understand and quantify the role of hospital-based invasive procedures on hepatitis C virus (HCV) transmission. METHODS: We conducted a systematic review and meta-analysis to identify recent studies reporting association measures of HCV infection risk that are linked to iatrogenic procedures. Based on expert opinion, invasive procedures were categorised into 10 groups for which pooled measures were calculated. Finally, the relationship between pooled measures and the country-level HCV prevalence or the Healthcare Access and Quality (HAQ) index was assessed by meta-regression. RESULTS: We included 71 studies in the analysis. The most frequently evaluated procedures were blood transfusion (66 measures) and surgery (43 measures). The pooled odds ratio (OR) of HCV infection varied widely, ranging from 1.46 (95% confidence interval: 1.14-1.88) for dental procedures to 3.22 (1.7-6.11) for transplantation. The OR for blood transfusion was higher for transfusions performed before 1998 (3.77, 2.42-5.88) than for those without a specified/recent date (2.20, 1.77-2.75). In procedure-specific analyses, the HCV infection risk was significantly negatively associated with the HAQ for endoscopy and positively associated with HCV prevalence for endoscopy and surgery. CONCLUSIONS: Various invasive procedures were significantly associated with HCV infection. Our results provide a ranking of procedures in terms of HCV risk that may be used for prioritisation of infection control interventions, especially in high HCV prevalence settings.

Measuring Basic Reproduction Number to Assess Effects of Nonpharmaceutical Interventions on Nosocomial SARS-CoV-2 Transmission.

Outbreaks of SARS-CoV-2 infection frequently occur in hospitals. Preventing nosocomial infection requires insight into hospital transmission. However, estimates of the basic reproduction number (R0) in care facilities are lacking. Analyzing a closely monitored SARS-CoV-2 outbreak in a hospital in early 2020, we estimated the patient-to-patient transmission rate and R0. We developed a model for SARS-CoV-2 nosocomial transmission that accounts for stochastic effects and undetected infections and fit it to patient test results. The model formalizes changes in testing capacity over time, and accounts for evolving PCR sensitivity at different stages of infection. R0 estimates varied considerably across wards, ranging from 3 to 15 in different wards. During the outbreak, the hospital introduced a contact precautions policy. Our results strongly support a reduction in the hospital-level R0 after this policy was implemented, from 8.7 to 1.3, corresponding to a policy efficacy of 85% and demonstrating the effectiveness of nonpharmaceutical interventions.

Modelling the impact of antimicrobial use and external introductions on commensal E. coli colistin resistance in small-scale chicken farms of the Mekong delta of Vietnam.

Colistin is a critically important antimicrobial for human medicine, and colistin-resistant Escherichia coli are commonly found in poultry and poultry products in Southeast Asia. Here, we aim at disentangling the within-farm and outside-farm drivers of colistin resistance in small-scale chicken farms of the Mekong delta of Vietnam. Nineteen Vietnamese chicken farms were followed up along a whole production cycle, during which weekly antimicrobial use data were recorded. At the beginning, middle and end of each production cycle, commensal E. coli samples from birds were collected, pooled and tested for colistin resistance. Twelve models were fitted to the data using an expectation-maximization algorithm and compared. We further tested the spatial clustering of the occurrence of resistance importations from external sources using the local Moran's I statistic. In the best model, colistin resistance in E. coli from chickens was found to be mostly affected by importations of resistance, and, to a lesser extent, by the use of antimicrobials in the last 1.73 weeks [0.00; 2.90], but not by the use of antimicrobials in day-olds, nor their colistin resistance carriage from hatchery. The occurrence of external source importations proved to be sometimes spatially clustered, suggesting a role of local environmental sources of colistin resistance.

[Dual-use research on modified pathogens in the laboratory: What framework for what issue?] / Recherche à usage dual sur les pathogènes modifiés en laboratoire - Quel encadrement pour quels enjeux ?

Technological advances in synthetic biology have made in vitro modification, or even creation, of viruses easier and more affordable. Several research studies using synthesis of potential pandemic pathogens led to controversies in the 2010's. More recently, the hypothesis that Covid-19 pandemics could originate from a lab escape is still under debate. In France, a legislative vacuum remains concerning the synthesis of modified pathogens. Initiating a collective reflection process towards setting of a legal framework on this type of work is timely so that research continues to provide profit to society rather than hazard.

Title: Recherche à usage dual sur les pathogènes modifiés en laboratoire - Quel encadrement pour quels enjeux ? Abstract: Les avancées techniques en biologie de synthèse rendent de plus en plus accessibles la modification ou même la fabrication de virus en laboratoire. Plusieurs travaux de recherche fondés sur la synthèse de pathogènes à potentiel pandémique ont créé la polémique au cours des années 2010 et, aujourd'hui encore, l'éventualité qu'une fuite de laboratoire soit à l'origine de la pandémie de Covid-19 fait débat. En France, un vide juridique subsiste concernant la synthèse de pathogènes modifiés. Une réflexion concertée vers un encadrement légal de ce type de recherche apparaît donc nécessaire et urgent pour que la recherche continue de représenter un bénéfice, plutôt qu'un risque, pour la société.