Trends in hospitalisations for lower respiratory infections after the COVID-19 pandemic in France.

OBJECTIVES: We aimed to evaluate the impact of the pandemic and post-pandemic periods on hospital admissions for LRTI, with a focus on patients with chronic respiratory disease (CRD). METHODS: From July 2013 to June 2023, monthly numbers of adult hospitalisations for LRTI (excluding SARS-CoV-2) were extracted from the French National Hospital Discharge Database. They were modelled by regressions with autocorrelated errors. Three periods were defined: (1) early pandemic and successive lockdowns; (2) gradual lifting of restrictions and widespread SARS-CoV-2 vaccination; (3) withdrawal of restriction measures. RESULTS: Pre-pandemic incidence was 96 (90.5 to 101.5) per 100,000 population. Compared with the pre-pandemic period, no more seasonality and significant reductions were estimated in the first two periods: -43.64% (-50.11 to -37.17) and -32.97% (-39.88 to -26.05), respectively. A rebound with a positive trend and a seasonal pattern was observed in period 3. Similar results were observed for CRD patients with no significant difference with pre-pandemic levels in the last period (-9.21%; -20.9% to 1.67%), albeit with differential changes according to the type of CRD. CONCLUSIONS: COVID-19 pandemic containment measures contributed to changes in LRTI incidence, with a rapid increase and return to a seasonal pattern after their lifting, particularly in patients with CRD.

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.

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.

Antimicrobial Resistance as Risk Factor for Recurrent Bacteremia after Staphylococcus aureus, Escherichia coli, or Klebsiella spp. Community-Onset Bacteremia.

We investigated links between antimicrobial resistance in community-onset bacteremia and 1-year bacteremia recurrence by using the clinical data warehouse of Europe's largest university hospital group in France. We included adult patients hospitalized with an incident community-onset Staphylococcus aureus, Escherichia coli, or Klebsiella spp. bacteremia during 2017-2019. We assessed risk factors of 1-year recurrence using Fine-Gray regression models. Of the 3,617 patients included, 291 (8.0%) had >1 recurrence episode. Third-generation cephalosporin (3GC)-resistance was significantly associated with increased recurrence risk after incident Klebsiella spp. (hazard ratio 3.91 [95% CI 2.32-6.59]) or E. coli (hazard ratio 2.35 [95% CI 1.50-3.68]) bacteremia. Methicillin resistance in S. aureus bacteremia had no effect on recurrence risk. Although several underlying conditions and infection sources increased recurrence risk, 3GC-resistant Klebsiella spp. was associated with the greatest increase. These results demonstrate a new facet to illness induced by 3GC-resistant Klebsiella spp. and E. coli in the community setting.

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.

Care pathways of sepsis survivors: sequelae, mortality and use of healthcare services in France, 2015-2018.

BACKGROUND: Individuals who survive sepsis are at high risk of chronic sequelae, resulting in significant health-economic costs. Several studies have focused on aspects of healthcare pathways of sepsis survivors but comprehensive, longitudinal overview of their pathways of care are scarce. The aim of this retrospective, longitudinal cohort study is to identify sepsis survivor profiles based on their healthcare pathways and describe their healthcare consumption and costs over the 3 years following their index hospitalization. METHODS: The data were extracted from the French National Hospital Discharge Database. The study population included all patients above 15 years old, with bacterial sepsis, who survived an incident hospitalization in an acute care facility in 2015. To identify survivor profiles, state sequence and clustering analyses were conducted over the year following the index hospitalization. For each profile, patient characteristics and their index hospital stay and sequelae were described, as well as use of care and its associated monetary costs, both pre- and post-sepsis. RESULTS: New medical (79.2%), psychological (26.9%) and cognitive (18.5%) impairments were identified post-sepsis, and 65.3% of survivors were rehospitalized in acute care. Cumulative mortality reached 36.6% by 3 years post-sepsis. The total medical cost increased by 856 million € in the year post-sepsis. Five patient clusters were identified: home (65.6% of patients), early death (12.9%), late death (6.8%), short-term rehabilitation (11.3%) and long-term rehabilitation (3.3%). Survivors with early and late death clusters had high rates of cancer and primary bacteremia and experienced more hospital-at-home care post-sepsis. Survivors in short- or long-term rehabilitation clusters were older, with higher percentage of septic shock than those coming back home, and had high rates of multiple site infections and higher rates of new psychological and cognitive impairment. CONCLUSIONS: Over three years post-sepsis, different profiles of sepsis survivors were identified with different mortality rates, sequels and healthcare services usage and cost. This study confirmed the importance of sepsis burden and suggests that strategies of post-discharge care, in accordance with patient profile, should be further tested in order to reduce sepsis burden.

Incidence and risk factors of neonatal bacterial infections: a community-based cohort from Madagascar (2018-2021).

BACKGROUND: Few studies on neonatal severe bacterial infection are available in LMICs. Data are needed in these countries to prioritize interventions and decrease neonatal infections which are a primary cause of neonatal mortality. The BIRDY project (Bacterial Infections and Antimicrobial Drug Resistant among Young Children) was initially conducted in Madagascar, Senegal and Cambodia (BIRDY 1, 2012-2018), and continued in Madagascar only (BIRDY 2, 2018-2021). We present here the BIRDY 2 project whose objectives were (1) to estimate the incidence of neonatal severe bacterial infections and compare these findings with those obtained in BIRDY 1, (2) to identify determinants associated with severe bacterial infection and (3) to specify the antibiotic resistance pattern of bacteria in newborns. METHODS: The BIRDY 2 study was a prospective community-based mother and child cohort, both in urban and semi-rural areas. All pregnant women in the study areas were identified and enrolled. Their newborns were actively and passively followed-up from birth to 3 months. Data on clinical symptoms developed by the children and laboratory results of all clinical samples investigated were collected. A Cox proportional hazards model was performed to identify risk factors associated with possible severe bacterial infection. FINDINGS: A total of 53 possible severe bacterial infection and 6 confirmed severe bacterial infection episodes were identified among the 511 neonates followed-up, with more than half occurring in the first 3 days. For the first month period, the incidence of confirmed severe bacterial infection was 11.7 per 1,000 live births indicating a 1.3 -fold decrease compared to BIRDY 1 in Madagascar (p = 0.50) and the incidence of possible severe bacterial infection was 76.3, indicating a 2.6-fold decrease compared to BIRDY 1 in Madagascar (p < 0.001). The 6 severe bacterial infection confirmed by blood culture included 5 Enterobacterales and one Enterococcus faecium. The 5 Enterobacterales were extended-spectrum ß-lactamases (ESBL) producers and were resistant to quinolones and gentamicin. Enterococcus faecium was sensitive to vancomycin but resistant to amoxicillin and to gentamicin. These pathogns were classified as multidrug-resistant bacteria and were resistant to antibiotics recommended in WHO guidelines for neonatal sepsis. However, they remained susceptible to carbapenem. Fetid amniotic fluid, need for resuscitation at birth and low birth weight were associated with early onset possible severe bacterial infection. CONCLUSION: Our results suggest that the incidence of severe bacterial infection is still high in the community of Madagascar, even if it seems lower when compared to BIRDY 1 estimates, and that existing neonatal sepsis treatment guidelines may no longer be appropriate in Madagascar. These results motivate to further strengthen actions for the prevention, early diagnosis and case management during the first 3 days of life.

Determinants of worldwide antibiotic resistance dynamics across drug-bacterium pairs: a multivariable spatial-temporal analysis using ATLAS.

BACKGROUND: Antibiotic resistance (ABR) is a major concern for global health. However, factors driving its emergence and dissemination are not fully understood. Identification of such factors is crucial to explain heterogeneity in ABR rates observed across space, time, and species and antibiotics. METHODS: We analysed count data of clinical isolates from 51 countries over 2006-19 for thirteen drug-bacterium pairs taken from the ATLAS database. We characterised ABR spatial and temporal patterns and used a mixed-effect negative binomial model, accounting for country-year dependences with random effects, to investigate associations with potential drivers, including antibiotic sales, economic and health indicators, meteorological data, population density, and tourism. FINDINGS: ABR patterns were strongly country and drug-bacterium pair dependent. In 2019, median ABR rates ranged from 6·3% (IQR 19·7% [0·5-20·2]) for carbapenem-resistant Klebsiella pneumoniae to 80·7% (41·8% [50·4-92·2]) for fluoroquinolone-resistant Acinetobacter baumannii, with heterogeneity across countries. From 2006 to 2019, carbapenem resistance increased in more than 60% of investigated countries; no global trend was observed for other resistances. Multivariable analyses identified significant associations of ABR with country-level selecting antibiotic sales, but only in fluoroquinolone-resistant-Escherichia coli, fluoroquinolone-resistant-Pseudomonas aeruginosa, and carbapenem-resistant-A baumannii. We also found a correlation between temperature and resistance in Enterobacteriaceae and with the health system quality for all drug-bacterium pairs except Enterococci and Streptococcus pneumoniae pairs. Despite wide consideration of possible explanatory variables, drug-bacterium pair ABR rates still showed unexplained spatial random effects variance. INTERPRETATION: Our findings reflect the diversity of mechanisms driving global antibiotic resistance across pathogens and stress the need for tailored interventions to tackle bacterial resistance. FUNDING: Independent research Pfizer Global Medical Grant and ANR Labex IBEID.

Inappropriate antibiotic prescribing and its determinants among outpatient children in 3 low- and middle-income countries: A multicentric community-based cohort study.

BACKGROUND: Antibiotic resistance is a global public health issue, particularly in low- and middle-income countries (LMICs), where antibiotics required to treat resistant infections are not affordable. LMICs also bear a disproportionately high burden of bacterial diseases, particularly among children, and resistance jeopardizes progress made in these areas. Although outpatient antibiotic use is a major driver of antibiotic resistance, data on inappropriate antibiotic prescribing in LMICs are scarce at the community level, where the majority of prescribing occurs. Here, we aimed to characterize inappropriate antibiotic prescribing among young outpatient children and to identify its determinants in 3 LMICs. METHODS AND FINDINGS: We used data from a prospective, community-based mother-and-child cohort (BIRDY, 2012 to 2018) conducted across urban and rural sites in Madagascar, Senegal, and Cambodia. Children were included at birth and followed-up for 3 to 24 months. Data from all outpatient consultations and antibiotics prescriptions were recorded. We defined inappropriate prescriptions as antibiotics prescribed for a health event determined not to require antibiotic therapy (antibiotic duration, dosage, and formulation were not considered). Antibiotic appropriateness was determined a posteriori using a classification algorithm developed according to international clinical guidelines. We used mixed logistic analyses to investigate risk factors for antibiotic prescription during consultations in which children were determined not to require antibiotics. Among the 2,719 children included in this analysis, there were 11,762 outpatient consultations over the follow-up period, of which 3,448 resulted in antibiotic prescription. Overall, 76.5% of consultations resulting in antibiotic prescription were determined not to require antibiotics, ranging from 71.5% in Madagascar to 83.3% in Cambodia. Among the 10,416 consultations (88.6%) determined not to require antibiotic therapy, 25.3% (n = 2,639) nonetheless resulted in antibiotic prescription. This proportion was much lower in Madagascar (15.6%) than in Cambodia (57.0%) or Senegal (57.2%) (p < 0.001). Among the consultations determined not to require antibiotics, in both Cambodia and Madagascar the diagnoses accounting for the greatest absolute share of inappropriate prescribing were rhinopharyngitis (59.0% of associated consultations in Cambodia, 7.9% in Madagascar) and gastroenteritis without evidence of blood in the stool (61.6% and 24.6%, respectively). In Senegal, uncomplicated bronchiolitis accounted for the greatest number of inappropriate prescriptions (84.4% of associated consultations). Across all inappropriate prescriptions, the most frequently prescribed antibiotic was amoxicillin in Cambodia and Madagascar (42.1% and 29.2%, respectively) and cefixime in Senegal (31.2%). Covariates associated with an increased risk of inappropriate prescription include patient age greater than 3 months (adjusted odds ratios (aOR) with 95% confidence interval (95% CI) ranged across countries from 1.91 [1.63, 2.25] to 5.25 [3.85, 7.15], p < 0.001) and living in rural as opposed to urban settings (aOR ranged across countries from 1.83 [1.57, 2.14] to 4.40 [2.34, 8.28], p < 0.001). Diagnosis with a higher severity score was also associated with an increased risk of inappropriate prescription (aOR = 2.00 [1.75, 2.30] for moderately severe, 3.10 [2.47, 3.91] for most severe, p < 0.001), as was consultation during the rainy season (aOR = 1.32 [1.19, 1.47], p < 0.001). The main limitation of our study is the lack of bacteriological documentation, which may have resulted in some diagnosis misclassification and possible overestimation of inappropriate antibiotic prescription. CONCLUSION: In this study, we observed extensive inappropriate antibiotic prescribing among pediatric outpatients in Madagascar, Senegal, and Cambodia. Despite great intercountry heterogeneity in prescribing practices, we identified common risk factors for inappropriate prescription. This underscores the importance of implementing local programs to optimize antibiotic prescribing at the community level in LMICs.

Vaccination Coverage and Risk Factors Associated With Incomplete Vaccination Among Children in Cambodia, Madagascar, and Senegal.

Background: Vaccination reduces mortality from infectious disease, which is the leading cause of death in children under 5 and bears a particularly high burden in low- and middle-income countries. The Global Vaccine Action Plan (2011-2020) has set a target of 90% vaccine coverage for all vaccines included in national immunization programs by 2020. The objectives of this study were to estimate vaccine coverage among children in Madagascar, Cambodia, and Senegal and to identify the risk factors associated with incomplete vaccination. Methods: Using data from a community-based prospective cohort that included all newborn of some areas from 2012 to 2018 in these 3 countries, vaccine coverage was estimated for BCG, hepatitis B, oral polio, pentavalent (targeting diphtheria, tetanus, pertussis, hepatitis B, and Haemophilus influenzae type b), and measles vaccines. Risk factor analysis was performed with logistic regression models to identify correlates of incomplete vaccination. Results: A total of 3606 children were followed up, and vaccine coverage was below the 90% threshold for most vaccines in all countries. Coverage was higher for vaccines recommended at birth and at 6 weeks, while a decrease in coverage for subsequent doses was observed for vaccines requiring several doses (23-47 points). Low birth weight (<2500 g) was an important risk factor for nonvaccination for vaccines recommended at birth in all 3 countries (adjusted odds ratio [95% confidence interval] ranging from 1.93 [1.11-3.38] to 4.28 [1.85-9.37]). Conclusions: Vaccine coverage for common childhood vaccines was lower than World Health Organization recommendations, and multidisciplinary approaches may help to improve vaccine coverage and timeliness.

Stillbirths and neonatal mortality in LMICs: A community-based mother-infant cohort study.

Background: The exact timing, causes, and circumstances of stillbirth and neonatal mortality in low- and middle-income countries (LMICs) remain poorly described, especially for antenatal stillbirths and deaths occurring at home. We aimed to provide reliable estimates of the incidence of stillbirth and neonatal death in three LMICs (Madagascar, Cambodia and Senegal) and to identify their main causes and associated risk factors. Methods: This study is based on data from an international, multicentric, prospective, longitudinal, community-based mother-infant cohort. We included pregnant mothers and prospectively followed up their children in the community. Stillbirths and deaths were systematically reported; information across healthcare settings was collected and verbal autopsies were performed to document the circumstances and timing of death. Results: Among the 4436 pregnancies and 4334 live births, the peripartum period and the first day of life were the key periods of mortality. The estimated incidence of stillbirth was 11 per 1000 total births in Cambodia, 15 per 1000 in Madagascar, and 12 per 1000 in Senegal. We estimated neonatal mortality at 18 per 1000 live births in Cambodia, 24 per 1000 in Madagascar, and 23 per 1000 in Senegal. Based on ultrasound biometric data, 16.1% of infants in Madagascar were born prematurely, where 42% of deliveries and 33% of deaths occurred outside healthcare facilities. Risk factors associated with neonatal death were mainly related to delivery or to events that newborns faced during the first week of life. Conclusions: These findings underscore the immediate need to improve care for and monitoring of children at birth and during early life to decrease infant mortality. Surveillance of stillbirth and neonatal mortality and their causes should be improved to mitigate this burden in LMICs.

Ability of epidemiological studies to monitor HPV post-vaccination dynamics: a simulation study.

Genital human papillomavirus (HPV) infections are caused by a broad diversity of genotypes. As available vaccines target a subgroup of these genotypes, monitoring transmission dynamics of nonvaccine genotypes is essential. After reviewing the epidemiological literature on study designs aiming to monitor those dynamics, we evaluated their abilities to detect HPV-prevalence changes following vaccine introduction. We developed an agent-based model to simulate HPV transmission in a heterosexual population under various scenarios of vaccine coverage and genotypic interaction, and reproduced two study designs: post-vs.-prevaccine and vaccinated-vs.-unvaccinated comparisons. We calculated the total sample size required to detect statistically significant prevalence differences at the 5% significance level and 80% power. Although a decrease in vaccine-genotype prevalence was detectable as early as 1 year after vaccine introduction, simulations indicated that the indirect impact on nonvaccine-genotype prevalence (a decrease under synergistic interaction or an increase under competitive interaction) would only be measurable after >10 years whatever the vaccine coverage. Sample sizes required for nonvaccine genotypes were >5 times greater than for vaccine genotypes and tended to be smaller in the post-vs.-prevaccine than in the vaccinated-vs.-unvaccinated design. These results highlight that previously published epidemiological studies were not powerful enough to efficiently detect changes in nonvaccine-genotype prevalence.

Short treatment duration for community-acquired pneumonia.

PURPOSE OF REVIEW: Lower respiratory tract infections are one of the most common indications for antibiotic use in community and hospital settings. Usual guidelines for adults with community-acquired pneumonia (CAP) recommend 5-7 days of antibiotic treatment. In daily practice, physicians often prescribe 9-10 days of antibiotic treatment. Among available strategies to decrease antibiotic use, possibly preventing the emergence of bacterial resistance, reducing treatment durations is the safest and the most acceptable to clinicians. We aim to review data evaluating the efficacy of short antibiotic duration in adult CAP and which criteria can help clinicians to reduce antibiotic treatment. RECENT FINDINGS: Several studies and meta-analyses demonstrated that the treatment duration of 7 days or less was sufficient for CAP. Two trials found that 3-day treatments were effective, even in hospitalized CAP.To customize and shorten duration, clinical and biological criteria have been studied and reflect patient's response. Indeed, stability criteria were recently shown to be effective to discontinue antibiotic treatment. Procalcitonin was also studied but never compared with clinical criteria. SUMMARY: Treatment duration for CAP is still under debate, but several studies support short durations. Clinical criteria could be possibly used to discontinue antibiotic treatment.

Antimicrobial Resistance and Mortality in Hospitalized Patients with Bacteremia in the Greater Paris Area from 2016 to 2019.

Purpose: Antibiotic-resistant bacteremia is a leading global cause of infectious disease morbidity and mortality. Clinical data warehouses (CDWs) allow for the secure, real-time coupling of diverse data sources from real-world clinical settings, including care-based medical-administrative data and laboratory-based microbiological data. The main purpose of this study was to assess the contribution of CDWs in the epidemiological study of antibiotic resistance by constructing a database of bacteremia patients, BactHub, and describing their main clinico-microbiological features and outcomes. Patients and Methods: Adult patients with bacteremia hospitalized between January 1, 2016 and December 31, 2019 in 14 acute care university hospitals from the Greater Paris area were identified; their first bacteremia episode was included. Data describing patients, episodes of bacteremia, bacterial isolates, and antimicrobial resistance were structured. Results: Among 29,228 patients with bacteremia, 41% of episodes were community-onset (CO) and 59% were hospital-acquired (HA). Thirty-day and ninety-day mortality rates were 15% and 20% in CO episodes, and 18% and 36% in HA episodes. Overall resistance rates were high, including third-generation cephalosporin resistance among Klebsiella pneumoniae (CO 21%, HA 37%) and Escherichia coli (CO 13%, HA 17%), and methicillin resistance among Staphylococcus aureus (CO 11%, HA 14%). Annual incidence rates increased significantly from 2017 to 2019, from 20.0 to 20.9 to 22.1 stays with bacteremia per 1000 stays (p < 0.0001). Conclusion: The Bacthub database provides accurate clinico-microbiological data describing bacteremia across France's largest hospital group. Data from Bacthub may inform surveillance and the clinical decision-making process for bacteremia patients, including choice of antimicrobial therapy. The database also offers opportunities for research, including analysis of hospital care pathways and significant patient outcomes such as mortality and recurrence of infection.

One-year hospital readmission for recurrent sepsis: associated risk factors and impact on 1-year mortality-a French nationwide study.

BACKGROUND: Sepsis is a complex health condition, leading to long-term morbidity and mortality. Understanding the risk factors for recurrent sepsis, as well as its impact on mid- and long-term mortality among other risk factors, is essential to improve patient survival. METHODS: A risk factor analysis, based on French nationwide medico-administrative data, was conducted on a cohort of patients above 15 years old, hospitalized with an incident sepsis in metropolitan France between 1st January 2018 and 31st December 2018 and who survived their index hospitalization. Two main analyses, focusing on outcomes occurring 1-year post-discharge, were conducted: a first one to assess risk factors for recurrent sepsis and a second to assess risk factors for mortality. RESULTS: Of the 178017 patients surviving an incident sepsis episode in 2018 and included in this study, 22.3% died during the 1-year period from discharge and 73.8% had at least one hospital readmission in acute care, among which 18.1% were associated with recurrent sepsis. Patients aged between 56 and 75, patients with cancer and renal disease, with a long index hospital stay or with mediastinal or cardiac infection had the highest odds of recurrent sepsis. One-year mortality was higher for patients with hospital readmission for recurrent sepsis (aOR 2.93; 99% CI 2.78-3.09). Among all comorbidities, patients with cancer (aOR 4.35; 99% CI 4.19-4.52) and dementia (aOR 2.02; 99% CI 1.90-2.15) had the highest odds of 1-year mortality. CONCLUSION: Hospital readmission for recurrent sepsis is one of the most important risk factors for 1-year mortality of septic patients, along with age and comorbidities. Our study suggests that recurrent sepsis, as well as modifiable or non-modifiable other risk factors identified, should be considered in order to improve patient care pathway and survival.

Prevalence and factors associated with faecal carriage of extended-spectrum ß-lactamase-producing Enterobacterales among peripartum women in the community in Cambodia.

BACKGROUND: In Southeast-Asia, where many conditions associated with dissemination of ESBL-producing Enterobacterales (ESBL-E) in the community are met, data from the community are scarce but show high ESBL-E carriage prevalence. Maternal ESBL-E colonization is considered a risk factor for neonatal colonization, which is the first step towards developing neonatal sepsis. Despite this, ESBL-E carriage prevalence and its risk factors during pregnancy or postpartum remain undefined in Southeast-Asia. OBJECTIVES: To estimate the prevalence of ESBL-E faecal colonization among peripartum women in the community of an urban and a rural area in Cambodia, to investigate ESBL-E genomic characteristics and to identify associated risk factors. METHODS: Epidemiological data and faecal samples from 423 peripartum women were collected in an urban and rural areas in Cambodia (2015-16). Bacterial cultures, antibiotic susceptibility tests and ESBL gene sequencing were performed. Risk factor analysis was conducted using logistic regression. RESULTS: The prevalence of ESBL-E faecal carriage was 79.2% (95% CI 75.0%-82.8%) among which Escherichia coli (n = 315/335, 94.0%) were most frequent. All isolates were multidrug resistant. Among 318 ESBL-E, the genes most frequently detected were blaCTX-M-15 (41.5%), blaCTX-M-55 (24.8%), and blaCTX-M-27 (15.1%). Low income, undernutrition, multiparity, regular consumption of pork, dried meat, and raw vegetables, were associated with ESBL-E faecal carriage. CONCLUSIONS: The high prevalence of ESBL-E carriage observed among peripartum women in Southeast-Asia and the identified associated factors underline the urgent need for public health measures to address antimicrobial resistance, including a 'One Health' approach.

Trends in bacterial sepsis incidence and mortality in France between 2015 and 2019 based on National Health Data System (Système National des données de Santé (SNDS)): a retrospective observational study.

OBJECTIVE: This study aims to provide a case definition of sepsis of presumed bacterial aetiology based on 10th revision of the International Classification of Diseases (ICD-10) codes, to assess trends in sepsis incidence and mortality between 2015 and 2019 in France, and to describe the characteristics of affected patients and hospital stays. DESIGN: Nationwide, population-based, retrospective observational study. SETTING: Metropolitan France between 2015 and 2019. PARTICIPANTS: Between 2015 and 2019, 1 224 433 patients with sepsis of presumed bacterial aetiology were selected from the French National Hospital Discharge Database (Programme de Médicalisation des Systèmes d'Information) and were identified from corresponding ICD-10 codes for explicit sepsis or implicit sepsis. MAIN OUTCOMES MEASURES: Annual overall and age-specific and gender-specific incidence and 95% CI, as well as trends in sepsis incidence and mortality, were estimated. Comorbidities, length of hospital stay and outcomes were described. RESULTS: The sex-standardised and age-standardised incidence per 100 000 (95% CI) increased from 357 (356.0 to 359.0) in 2015 to 403 (401.9 to 405.0) in 2019 and remained higher for males compared with females. Children under 1 year and patients over 75 years consistently had the highest incidence. The most common comorbidities were cancer and chronic heart failure. The median hospital length of stay was 12 days. Most patients came from home, but only half returned home after their hospital stay and approximately 15% were discharged to long-term care. In-hospital mortality was about 25% and declined along the study period. CONCLUSIONS: Medico-administrative databases can be used to provide nationwide estimates of the in-hospital burden of bacterial sepsis. The results confirm the high burden of sepsis in France. These data should be complemented by estimating the additional burden associated with fungal and viral infections during the COVID-19 pandemic.

Contact patterns and HPV-genotype interactions yield heterogeneous HPV-vaccine impacts depending on sexual behaviors: An individual-based model.

Human papillomaviruses are common sexually transmitted infections, caused by a large diversity of genotypes. In the context of vaccination against a subgroup of genotypes, better understanding the role of genotype interactions and human sexual behavior on genotype dynamics is essential. Herein, we present an individual-based model that integrates realistic heterosexual partnership behaviors and simulates interactions between vaccine and non-vaccine genotypes. Genotype interactions were considered, assuming a previous vaccine-genotype infection shortened (competition) or extended (synergy) the duration of a secondary non-vaccine-genotype infection. Sexual behavior determined papillomavirus acquisition and transmission: only 19.5% of active individuals at most 1 partner r during the year, but > 80% of those with ≥ 2 partners, were infected before vaccine introduction. The pre-vaccination situation was consistent with all genotype interaction scenarios. These genotype interactions, despite being undetectable during the pre-vaccination era, markedly impacted genotype prevalence after vaccination started, with a significant increase/decrease of non-vaccine genotypes prevalence for respectively competitive/synergistic interactions. These prevalence changes were more pronounced in individuals with ≤ 3 partners per year (up to 30% of prevalence modification assuming 65% vaccine coverage) but barely visible for individuals with > 3 partners per year (at most 0.30%). Results suggest the presence of genotype interaction, which is consistent with the pre-vaccine situation, may impact the dynamics of non-vaccine genotypes, particularly in less active individuals.

Excess risk of subsequent infection in hospitalized children from a community cohort study in Cambodia and Madagascar.

BACKGROUND: Children in low- and middle-income countries are particularly vulnerable in the months following an initial health event (IHE), with increased risk of mortality caused mostly by infectious diseases. Due to exposure to a wide range of environmental stressors, hospitalization in itself might increase child vulnerability at discharge. The goal of this study was to disentangle the role of hospitalization on the risk of subsequent infection. METHODS: Data from a prospective, longitudinal, international, multicenter mother-and-child cohort were analysed. The main outcome assessed was the risk of subsequent infection within 3 months of initial care at hospital or primary healthcare facilities. First, risk factors for being hospitalized for the IHE (Step 1) and for having a subsequent infection (Step 2) were identified. Then, inpatients were matched with outpatients using propensity scores, considering the risk factors identified in Step 1. Finally, adjusted on the risk factors identified in Step 2, Cox regression models were performed on the matched data set to estimate the effect of hospitalization at the IHE on the risk of subsequent infection. RESULTS: Among the 1312 children presenting an IHE, 210 (16%) had a subsequent infection, mainly lower-respiratory infections. Although hospitalization did not increase the risk of subsequent diarrhoea or unspecified sepsis, inpatients were 1.7 (95% Confidence Intervals [1.0-2.8]) times more likely to develop a subsequent lower-respiratory infection than comparable outpatients. CONCLUSION: For the first time, our findings suggest that hospitalization might increase the risk of subsequent lower-respiratory infection adjusted on severity and symptoms at IHE. This highlights the need for robust longitudinal follow-up of at-risk children and the importance of investigating underlying mechanisms driving vulnerability to infection.

From Pathophysiological Hypotheses to Case-Control Study Design: Resistance from Antibiotic Exposure in Community-Onset Infections.

Antimicrobial resistance is a global public health concern, at least partly due to the misuse of antibiotics. The increasing prevalence of antibiotic-resistant infections in the community has shifted at-risk populations into the general population. Numerous case-control studies attempt to better understand the link between antibiotic use and antibiotic-resistant community-onset infections. We review the designs of such studies, focusing on community-onset bloodstream and urinary tract infections. We highlight their methodological heterogeneity in the key points related to the antibiotic exposure, the population and design. We show the impact of this heterogeneity on study results, through the example of extended-spectrum ß-lactamases producing Enterobacteriaceae. Finally, we emphasize the need for the greater standardization of such studies and discuss how the definition of a pathophysiological hypothesis specific to the bacteria-resistance pair studied is an important prerequisite to clarify the design of future studies.