Antimicrobial resistance prevalence in bloodstream infection in 29 European countries by age and sex: An observational study.

BACKGROUND: Antibiotic usage, contact with high transmission healthcare settings as well as changes in immune system function all vary by a patient's age and sex. Yet, most analyses of antimicrobial resistance (AMR) ignore demographic indicators and provide only country-level resistance prevalence values. This study aimed to address this knowledge gap by quantifying how resistance prevalence and incidence of bloodstream infection (BSI) varied by age and sex across bacteria and antibiotics in Europe. METHODS AND FINDINGS: We used patient-level data collected as part of routine surveillance between 2015 and 2019 on BSIs in 29 European countries from the European Antimicrobial Resistance Surveillance Network (EARS-Net). A total of 6,862,577 susceptibility results from isolates with age, sex, and spatial information from 944,520 individuals were used to characterise resistance prevalence patterns for 38 different bacterial species and antibiotic combinations, and 47% of these susceptibility results were from females, with a similar age distribution in both sexes (mean of 66 years old). A total of 349,448 isolates from 2019 with age and sex metadata were used to calculate incidence. We fit Bayesian multilevel regression models by country, laboratory code, sex, age, and year of sample to quantify resistant prevalence and provide estimates of country-, bacteria-, and drug-family effect variation. We explore our results in greater depths for 2 of the most clinically important bacteria-antibiotic combinations (aminopenicillin resistance in Escherichia coli and methicillin resistance in Staphylococcus aureus) and present a simplifying indicative index of the difference in predicted resistance between old (aged 100) and young (aged 1). At the European level, we find distinct patterns in resistance prevalence by age. Trends often vary more within an antibiotic family, such as fluroquinolones, than within a bacterial species, such as Pseudomonas aeruginosa. Clear resistance increases by age for methicillin-resistant Staphylococcus aureus (MRSA) contrast with a peak in resistance to several antibiotics at approximately 30 years of age for P. aeruginosa. For most bacterial species, there was a u-shaped pattern of infection incidence with age, which was higher in males. An important exception was E. coli, for which there was an elevated incidence in females between the ages of 15 and 40. At the country-level, subnational differences account for a large amount of resistance variation (approximately 38%), and there are a range of functional forms for the associations between age and resistance prevalence. For MRSA, age trends were mostly positive, with 72% (n = 21) of countries seeing an increased resistance between males aged 1 and 100 years and a greater change in resistance in males. This compares to age trends for aminopenicillin resistance in E. coli which were mostly negative (males: 93% (n = 27) of countries see decreased resistance between those aged 1 and 100 years) with a smaller change in resistance in females. A change in resistance prevalence between those aged 1 and 100 years ranged up to 0.51 (median, 95% quantile of model simulated prevalence using posterior parameter ranges 0.48, 0.55 in males) for MRSA in one country but varied between 0.16 (95% quantile 0.12, 0.21 in females) to -0.27 (95% quantile -0.4, -0.15 in males) across individual countries for aminopenicillin resistance in E. coli. Limitations include potential bias due to the nature of routine surveillance and dependency of results on model structure. CONCLUSIONS: In this study, we found that the prevalence of resistance in BSIs in Europe varies substantially by bacteria and antibiotic over the age and sex of the patient shedding new light on gaps in our understanding of AMR epidemiology. Future work is needed to determine the drivers of these associations in order to more effectively target transmission and antibiotic stewardship interventions.

Individualised, short-course antibiotic treatment versus usual long-course treatment for ventilator-associated pneumonia (REGARD-VAP): a multicentre, individually randomised, open-label, non-inferiority trial.

BACKGROUND: Ventilator-associated pneumonia (VAP) is associated with increased mortality, prolonged hospitalisation, excessive antibiotic use and, consequently, increased antimicrobial resistance. In this phase 4, randomised trial, we aimed to establish whether a pragmatic, individualised, short-course antibiotic treatment strategy for VAP was non-inferior to usual care. METHODS: We did an individually randomised, open-label, hierarchical non-inferiority-superiority trial in 39 intensive care units in six hospitals in Nepal, Singapore, and Thailand. We enrolled adults (age ≥18 years) who met the US Centers for Disease Control and Prevention National Healthcare Safety Network criteria for VAP, had been mechanically ventilated for 48 h or longer, and were administered culture-directed antibiotics. In culture-negative cases, empirical antibiotic choices were made depending on local hospital antibiograms reported by the respective microbiology laboratories or prevailing local guidelines. Participants were assessed until fever resolution for 48 h and haemodynamic stability, then randomly assigned (1:1) to individualised short-course treatment (≤7 days and as short as 3-5 days) or usual care (≥8 days, with precise durations determined by the primary clinicians) via permuted blocks of variable sizes (8, 10, and 12), stratified by study site. Independent assessors for recurrent pneumonia and participants were masked to treatment allocation, but clinicians were not. The primary outcome was a 60-day composite endpoint of death or pneumonia recurrence. The non-inferiority margin was prespecified at 12% and had to be met by analyses based on both intention-to-treat (all study participants who were randomised) and per-protocol populations (all randomised study participants who fulfilled the eligibility criteria, met fitness criteria for antibiotic discontinuation, and who received antibiotics for the duration specified by their allocation group). This study is registered with ClinicalTrials.gov, number NCT03382548. FINDINGS: Between May 25, 2018, and Dec 16, 2022, 461 patients were enrolled and randomly assigned to the short-course treatment group (n=232) or the usual care group (n=229). Median age was 64 years (IQR 51-74) and 181 (39%) participants were female. 460 were included in the intention-to-treat analysis after excluding one withdrawal (231 in the short-course group and 229 in the usual care group); 435 participants received the allocated treatment and fulfilled eligibility criteria, and were included in the per-protocol population. Median antibiotic treatment duration for the index episodes of VAP was 6 days (IQR 5-7) in the short-course group and 14 days (10-21) in the usual care group. 95 (41%) of 231 participants in the short-course group met the primary outcome, compared with 100 (44%) of 229 in the usual care group (risk difference -3% [one-sided 95% CI -∞ to 5%]). Results were similar in the per-protocol population. Non-inferiority of short-course antibiotic treatment was met in the analyses, although superiority compared with usual care was not established. In the per-protocol population, antibiotic side-effects occurred in 86 (38%) of 224 in the usual care group and 17 (8%) of 211 in the short-course group (risk difference -31% [95% CI -37 to -25%; p<0·0001]). INTERPRETATION: In this study of adults with VAP, individualised shortened antibiotic duration guided by clinical response was non-inferior to longer treatment durations in terms of 60-day mortality and pneumonia recurrence, and associated with substantially reduced antibiotic use and side-effects. Individualised, short-course antibiotic treatment for VAP could help to reduce the burden of side-effects and the risk of antibiotic resistance in high-resource and resource-limited settings. FUNDING: UK Medical Research Council; Singapore National Medical Research Council. TRANSLATIONS: For the Thai and Nepali translations of the abstract see Supplementary Materials section.

A systematic review of neglected tropical diseases (NTDs) in Myanmar.

BACKGROUND: Neglected tropical diseases (NTDs) affect most impoverished communities in developing countries, like Myanmar in Southeast Asia. NTDs have been understudied and underreported in Myanmar. METHODS: A systematic review of published and grey literature (1900-2023) on neglected tropical diseases (NTDs) in Myanmar was conducted. The literature search included five international databases: PubMed, EMBASE, Ovid Global Health, and Web of Science Core Collection and one national database: the Myanmar Central Biomedical Library (locally published papers and grey literature). The selection criteria included articles with all types of study designs of current or previous infections conducted in humans, that reported NTDs, recognised by WHO, US CDC, and listed in PLoS NTDs. We included melioidosis and rickettsioses which we consider also meet the definition of an NTD. RESULTS: A total of 5941 records were retrieved and screened, of which, 672 (11%) met the selection criteria and were included in this review. Of the included articles, 449 (65%) were published after 2000 and 369 (55%) were from two regions (Yangon and Mandalay) of Myanmar. Of the included articles, 238 (35%) reported bacterial NTDs, 212 (32%) viral NTDs, 153 (23%) helminth NTDs, 25 (4%) protozoal NTDs and 39 (6%) reported more than one aetiology. Based on reported frequency in descending order, the bacterial NTDs were leprosy, Escherichia coli enteritis, salmonellosis, cholera, shigellosis, melioidosis, leptospirosis and rickettsioses; the viral NTDs were dengue, chikungunya and Japanese encephalitis virus (JEV) infection; the protozoal NTDs were amoebiasis, giardiasis and leishmaniasis, and the helminth NTDs were ascariasis, trichuriasis, hookworm disease, filariasis and strongyloidiasis. CONCLUSION: This review summarises NTDs reported in Myanmar over the past 100 years. The findings suggest that most NTDs are likely to be under reported, especially from the majority of the country which is far from academic centres. Research capacity building together with strengthening of laboratory systems would lead to better understanding of the true burden of NTDs in Myanmar. TRIAL REGISTRATION: PROSPERO registration ID: CRD42018092627.

The uncertain role of substandard and falsified medicines in the emergence and spread of antimicrobial resistance.

Approximately 10% of antimicrobials used by humans in low- and middle-income countries are estimated to be substandard or falsified. In addition to their negative impact on morbidity and mortality, they may also be important drivers of antimicrobial resistance. Despite such concerns, our understanding of this relationship remains rudimentary. Substandard and falsified medicines have the potential to either increase or decrease levels of resistance, and here we discuss a range of mechanisms that could drive these changes. Understanding these effects and their relative importance will require an improved understanding of how different drug exposures affect the emergence and spread of resistance and of how the percentage of active pharmaceutical ingredients in substandard and falsified medicines is temporally and spatially distributed.

The burden and dynamics of hospital-acquired SARS-CoV-2 in England.

Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1,2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.

Implications of reducing antibiotic treatment duration for antimicrobial resistance in hospital settings: A modelling study and meta-analysis.

BACKGROUND: Reducing antibiotic treatment duration is a key component of hospital antibiotic stewardship interventions. However, its effectiveness in reducing antimicrobial resistance is uncertain and a clear theoretical rationale for the approach is lacking. In this study, we sought to gain a mechanistic understanding of the relation between antibiotic treatment duration and the prevalence of colonisation with antibiotic-resistant bacteria in hospitalised patients. METHODS AND FINDINGS: We constructed 3 stochastic mechanistic models that considered both between- and within-host dynamics of susceptible and resistant gram-negative bacteria, to identify circumstances under which shortening antibiotic duration would lead to reduced resistance carriage. In addition, we performed a meta-analysis of antibiotic treatment duration trials, which monitored resistant gram-negative bacteria carriage as an outcome. We searched MEDLINE and EMBASE for randomised controlled trials published from 1 January 2000 to 4 October 2022, which allocated participants to varying durations of systemic antibiotic treatments. Quality assessment was performed using the Cochrane risk-of-bias tool for randomised trials. The meta-analysis was performed using logistic regression. Duration of antibiotic treatment and time from administration of antibiotics to surveillance culture were included as independent variables. Both the mathematical modelling and meta-analysis suggested modest reductions in resistance carriage could be achieved by reducing antibiotic treatment duration. The models showed that shortening duration is most effective at reducing resistance carriage in high compared to low transmission settings. For treated individuals, shortening duration is most effective when resistant bacteria grow rapidly under antibiotic selection pressure and decline rapidly when stopping treatment. Importantly, under circumstances whereby administered antibiotics can suppress colonising bacteria, shortening antibiotic treatment may increase the carriage of a particular resistance phenotype. We identified 206 randomised trials, which investigated antibiotic duration. Of these, 5 reported resistant gram-negative bacteria carriage as an outcome and were included in the meta-analysis. The meta-analysis determined that a single additional antibiotic treatment day is associated with a 7% absolute increase in risk of resistance carriage (80% credible interval 3% to 11%). Interpretation of these estimates is limited by the low number of antibiotic duration trials that monitored carriage of resistant gram-negative bacteria, as an outcome, contributing to a large credible interval. CONCLUSIONS: In this study, we found both theoretical and empirical evidence that reducing antibiotic treatment duration can reduce resistance carriage, though the mechanistic models also highlighted circumstances under which reducing treatment duration can, perversely, increase resistance. Future antibiotic duration trials should monitor antibiotic-resistant bacteria colonisation as an outcome to better inform antibiotic stewardship policies.

Estimation of the impact of hospital-onset SARS-CoV-2 infections on length of stay in English hospitals using causal inference.

BACKGROUND: From March 2020 through August 2021, 97,762 hospital-onset SARS-CoV-2 infections were detected in English hospitals. Resulting excess length of stay (LoS) created a potentially substantial health and economic burden for patients and the NHS, but we are currently unaware of any published studies estimating this excess. METHODS: We implemented appropriate causal inference methods to determine the extent to which observed additional hospital stay is attributable to the infection rather than the characteristics of the patients. Hospital admissions records were linked to SARS-CoV-2 test data to establish the study population (7.5 million) of all non-COVID-19 admissions to English hospitals from 1st March 2020 to 31st August 2021 with a stay of at least two days. The excess LoS due to hospital-onset SARS-CoV-2 infection was estimated as the difference between the mean LoS observed and in the counterfactual where infections do not occur. We used inverse probability weighted Kaplan-Meier curves to estimate the mean survival time if all hospital-onset SARS-CoV-2 infections were to be prevented, the weights being based on the daily probability of acquiring an infection. The analysis was carried out for four time periods, reflecting phases of the pandemic differing with respect to overall case numbers, testing policies, vaccine rollout and prevalence of variants. RESULTS: The observed mean LoS of hospital-onset cases was higher than for non-COVID-19 hospital patients by 16, 20, 13 and 19 days over the four phases, respectively. However, when the causal inference approach was used to appropriately adjust for time to infection and confounding, the estimated mean excess LoS caused by hospital-onset SARS-CoV-2 was: 2.0 [95% confidence interval 1.8-2.2] days (Mar-Jun 2020), 1.4 [1.2-1.6] days (Sep-Dec 2020); 0.9 [0.7-1.1] days (Jan-Apr 2021); 1.5 [1.1-1.9] days (May-Aug 2021). CONCLUSIONS: Hospital-onset SARS-CoV-2 is associated with a small but notable excess LoS, equivalent to 130,000 bed days. The comparatively high LoS observed for hospital-onset COVID-19 patients is mostly explained by the timing of their infections relative to admission. Failing to account for confounding and time to infection leads to overestimates of additional length of stay and therefore overestimates costs of infections, leading to inaccurate evaluations of control strategies.

A scoping review of antibiotic use practices and drivers of inappropriate antibiotic use in animal farms in WHO Southeast Asia region.

Antibiotic use (ABU) plays an important role in the proliferation of antimicrobial resistance (AMR). Global antimicrobial consumption in food production is projected to rise by 67% from 2010 to 2030, but available estimates are limited by the scarcity of ABU data and absence of global surveillance systems. The WHO South-East Asia (WHO SEA) region is at high risk of emergence of AMR, likely driven by intensifying farm operations and worsening ABU hotspots. However, little is known about farm-level ABU practices in the region. To summarize emerging evidence and research gaps, we conducted a scoping review of ABU practices following the Arksey and O'Malley methodological framework. We included studies published between 2010 and 2021 on farm-level ABU/AMR in the 11 WHO SEA member states, and databases were last searched on 31 October 2021. Our search strategy identified 184 unique articles, and 25 publications underwent full-text eligibility assessment. Seventeen studies, reported in 18 publications, were included in the scoping review. We found heterogeneity in the categorizations, definitions, and ABU characterization methods used across studies and farm types. Most studies involved poultry, pig, and cattle farms, and only one study examined aquaculture. Most studies evaluated ABU prevalence by asking respondents about the presence or absence of ABU in the farm. Only two studies quantified antibiotic consumption, and sampling bias and lack of standardized data collection methods were identified as key limitations. Emerging evidence that farm workers had difficulty differentiating antibiotics from other substances contributed to the uncertainty about the reliability of self-reported data without other validation techniques. ABU for growth promotion and treatment were prevalent. We found a large overlap in the critically important antibiotics used in farm animals and humans. The ease of access to antibiotics compounded by the difficulties in accessing quality veterinary care and preventive services likely drive inappropriate ABU in complex ways.

Excess Mortality Attributable to Hospital-Acquired Antimicrobial-Resistant Infections: A 2-Year Prospective Surveillance Study in Northeast Thailand.

Background: Quantifying the excess mortality attributable to antimicrobial-resistant (AMR) bacterial infections is important for assessing the potential benefit of preventive interventions and for prioritization of resources. However, there are few data from low- and middle-income countries. Methods: We conducted a 2-year prospective surveillance study to estimate the excess mortality attributable to AMR infections for all types of hospital-acquired infection (HAI), and included bacterial species that were both locally relevant and included in the World Health Organization priority list. Twenty-eight-day mortality was measured. Excess mortality and population attributable fraction (PAF) of mortality caused by AMR infections compared to antimicrobial-susceptible (AMS) infections, adjusted for predefined confounders, were calculated. Results: We enrolled 2043 patients with HAIs. The crude 28-day mortality of patients with AMR and AMS infections was 35.5% (491/1385) and 23.1% (152/658), respectively. After adjusting for prespecified confounders, the estimated excess mortality attributable to AMR infections was 7.7 (95% confidence interval [CI], 2.2-13.2) percentage points. This suggests that 106 (95% CI, 30-182) deaths among 1385 patients with AMR infections might have been prevented if all of the AMR infections in this study were AMS infections. The overall PAF was 16.3% (95% CI, 1.2%-29.1%). Among the bacteria under evaluation, carbapenem-resistant Acinetobacter baumannii was responsible for the largest number of excess deaths. Among all types of infection, urinary tract infections were associated with the highest number of excess deaths, followed by lower respiratory tract infections and bloodstream infections. Conclusions: Estimating and monitoring excess mortality attributable to AMR infections should be included in national action plans to prioritize targets of preventive interventions. Clinical Trials Registration: NCT03411538.

Attributable mortality and excess length of stay associated with third-generation cephalosporin-resistant Enterobacterales bloodstream infections: a prospective cohort study in Suva, Fiji.

OBJECTIVES: There are scant primary clinical data on antimicrobial resistance (AMR) burden from low- and middle-income countries (LMICs). We adapted recent World Health Organization methodology to measure the effect of third-generation cephalosporin resistance (3GC-R) on mortality and excess length of hospital stay in Fiji. METHODS: We conducted a prospective cohort study of inpatients with Enterobacterales bloodstream infections (BSIs) at Colonial War Memorial Hospital, Suva. We used cause-specific Cox proportional hazards models to estimate the effect of 3GC-R on the daily risk (hazard) of in-hospital mortality and being discharged alive (competing risks), and we used multistate modelling to estimate the excess length of hospital stay. RESULTS: From July 2020 to February 2021 we identified 162 consecutive Enterobacterales BSIs; 3GC-R was present in 66 (40.7%). Crude mortality for patients with 3GC-susceptible and 3GC-R BSIs was 16.7% (16/96) and 30.3% (20/66), respectively. 3GC-R was not associated with the in-hospital mortality hazard rate (adjusted hazard ratio [aHR] 1.13, 95% confidence interval [CI] 0.51-2.53) or being discharged alive (aHR 0.99, 95% CI 0.65-1.50), whereas Charlson comorbidity index score (aHR 1.62, 95% CI 1.36-1.93) and Pitt bacteraemia score (aHR 3.57, 95% CI 1.31-9.71) were both associated with an increased hazard rate of in-hospital mortality. 3GC-R was associated with an increased length of stay of 2.6 days (95% CI 2.5-2.8). 3GC-R was more common among hospital-associated infections, but genomics did not identify clonal transmission. CONCLUSION: Patients with Enterobacterales BSIs in Fiji had high mortality. There were high rates of 3GC-R, which was associated with increased hospital length of stay but not with in-hospital mortality.

The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020.

BACKGROUND: SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. METHODS: We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020. RESULTS: In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2-20.7%) of all identified hospitalised COVID-19 cases. CONCLUSIONS: Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections.

The potential impact of intensified community hand hygiene interventions on respiratory tract infections: a modelling study.

Hand hygiene is among the most fundamental and widely used behavioural measures to reduce the person-to-person spread of human pathogens and its effectiveness as a community intervention is supported by evidence from randomized trials. However, a theoretical understanding of the relationship between hand hygiene frequency and change in risk of infection is lacking. Using a simple model-based framework for understanding the determinants of hand hygiene effectiveness in preventing viral respiratory tract infections, we show that a crucial, but overlooked, determinant of the relationship between hand hygiene frequency and risk of infection via indirect transmission is persistence of viable virus on hands. If persistence is short, as has been reported for influenza, hand-washing needs to be performed very frequently or immediately after hand contamination to substantially reduce the probability of infection. When viable virus survival is longer (e.g. in the presence of mucus or for some enveloped viruses) less frequent hand washing can substantially reduce the infection probability. Immediate hand washing after contamination is consistently more effective than at fixed-time intervals. Our study highlights that recommendations on hand hygiene should be tailored to persistence of viable virus on hands and that more detailed empirical investigations are needed to help optimize this key intervention.

The effect of hand hygiene frequency on reducing acute respiratory infections in the community: a meta-analysis.

Hand hygiene is a simple, low-cost intervention that may lead to substantial population-level effects in suppressing acute respiratory infection epidemics. However, quantification of the efficacy of hand hygiene on respiratory infection in the community is lacking. We searched PubMed for randomised controlled trials on the effect of hand hygiene for reducing acute respiratory infections in the community published before 11 March 2021. We performed a meta-regression analysis using a Bayesian mixed-effects model. A total of 105 publications were identified, out of which six studies reported hand hygiene frequencies. Four studies were performed in household settings and two were in schools. The average number of handwashing events per day ranged from one to eight in the control arms, and four to 17 in the intervention arms. We estimated that a single hand hygiene event is associated with a 3% (80% credible interval (-1% to 7%)) decrease in the daily probability of an acute respiratory infection. Three of these six studies were potentially at high risk of bias because the primary outcome depended on self-reporting of upper respiratory tract symptoms. Well-designed trials with an emphasis on monitoring hand hygiene adherence are needed to confirm these findings.

The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020.

Background SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. Methods We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset >7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31 st July 2020. Results In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1%-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2%-20.7%) of all identified hospitalised COVID-19 cases. Conclusions Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (>60%) of hospital-acquired infections.

Effectiveness of infection prevention and control interventions, excluding personal protective equipment, to prevent nosocomial transmission of SARS-CoV-2: a systematic review and call for action.

Many infection prevention and control (IPC) interventions have been adopted by hospitals to limit nosocomial transmission of SARS-CoV-2. The aim of this systematic review is to identify evidence on the effectiveness of these interventions. We conducted a literature search of five databases (OVID MEDLINE, Embase, CENTRAL, COVID-19 Portfolio (pre-print), Web of Science). SWIFT ActiveScreener software was used to screen English titles and abstracts published between 1st January 2020 and 6th April 2021. Intervention studies, defined by Cochrane Effective Practice and Organisation of Care, that evaluated IPC interventions with an outcome of SARS-CoV-2 infection in either patients or healthcare workers were included. Personal protective equipment (PPE) was excluded as this intervention had been previously reviewed. Risks of bias were assessed using the Cochrane tool for randomised trials (RoB2) and non-randomized studies of interventions (ROBINS-I). From 23,156 screened articles, we identified seven articles that met the inclusion criteria, all of which evaluated interventions to prevent infections in healthcare workers and the majority of which were focused on effectiveness of prophylaxes. Due to heterogeneity in interventions, we did not conduct a meta-analysis. All agents used for prophylaxes have little to no evidence of effectiveness against SARS-CoV-2 infections. We did not find any studies evaluating the effectiveness of interventions including but not limited to screening, isolation and improved ventilation. There is limited evidence from interventional studies, excluding PPE, evaluating IPC measures for SARS-CoV-2. This review calls for urgent action to implement such studies to inform policies to protect our most vulnerable populations and healthcare workers.

Populations of extended-spectrum ß-lactamase-producing Escherichia coli and Klebsiella pneumoniae are different in human-polluted environment and food items: a multicentre European study.

OBJECTIVES: To assess the extent to which food items are a source of extended-spectrum ß-lactamase (ESBL) -producing Escherichia coli (ESBL-Ec) and ESBL-producing Klebsiella pneumoniae (ESBL-Kp) for humans in five European cities. METHODS: We sampled 122 human polluted (hp)-environments (sewers and polluted rivers, as a proxy of human contamination) and 714 food items in Besançon (France), Geneva (Switzerland), Sevilla (Spain), Tübingen (Germany) and Utrecht (The Netherlands). A total of 254 ESBL-Ec and 39 ESBL-Kp isolates were cultured. All genomes were fully sequenced to compare their sequence types (ST) and core genomes, along with the distribution of blaESBL genes and their genetic supports (i.e. chromosome or plasmid). RESULTS: Sequence data revealed that ESBL-Ec and ESBL-Kp isolates from hp-environments were genetically different from those contaminating food items. ESBL-Ec ST131 was widespread in the hp-environment (21.5% of the isolates) but absent from the food items tested. ESBL-Ec ST10 was in similar proportions in hp-environments and food items (15 and 10 isolates, respectively) but mostly carried reservoir-specific blaESBL. blaCTX-M-1 and blaSHV-12 predominated in food-related E. coli isolates (32% and 34% of the isolates, respectively), whereas blaCTX-M-15 and blaCTX-M-27 predominated in isolates from hp-environments (52% and 15% of the isolates, respectively). CONCLUSIONS: We found a very limited connection between ESBL-Ec and ESBL-Kp populations retrieved in food items and from hp-environments and blaESBL. This suggests that human-to-human contamination, rather than the food chain, is possibly the most frequent route of ESBL-Ec and ESBL-Kp transmission in high-income countries.

Probabilistic modelling of effects of antibiotics and calendar time on transmission of healthcare-associated infection.

Healthcare-associated infection and antimicrobial resistance are major concerns. However, the extent to which antibiotic exposure affects transmission and detection of infections such as MRSA is unclear. Additionally, temporal trends are typically reported in terms of changes in incidence, rather than analysing underling transmission processes. We present a data-augmented Markov chain Monte Carlo approach for inferring changing transmission parameters over time, screening test sensitivity, and the effect of antibiotics on detection and transmission. We expand a basic model to allow use of typing information when inferring sources of infections. Using simulated data, we show that the algorithms are accurate, well-calibrated and able to identify antibiotic effects in sufficiently large datasets. We apply the models to study MRSA transmission in an intensive care unit in Oxford, UK with 7924 admissions over 10 years. We find that falls in MRSA incidence over time were associated with decreases in both the number of patients admitted to the ICU colonised with MRSA and in transmission rates. In our inference model, the data were not informative about the effect of antibiotics on risk of transmission or acquisition of MRSA, a consequence of the limited number of possible transmission events in the data. Our approach has potential to be applied to a range of healthcare-associated infections and settings and could be applied to study the impact of other potential risk factors for transmission. Evidence generated could be used to direct infection control interventions.

Transmission of community- and hospital-acquired SARS-CoV-2 in hospital settings in the UK: A cohort study.

BACKGROUND: Nosocomial spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been widely reported, but the transmission pathways among patients and healthcare workers (HCWs) are unclear. Identifying the risk factors and drivers for these nosocomial transmissions is critical for infection prevention and control interventions. The main aim of our study was to quantify the relative importance of different transmission pathways of SARS-CoV-2 in the hospital setting. METHODS AND FINDINGS: This is an observational cohort study using data from 4 teaching hospitals in Oxfordshire, United Kingdom, from January to October 2020. Associations between infectious SARS-CoV-2 individuals and infection risk were quantified using logistic, generalised additive and linear mixed models. Cases were classified as community- or hospital-acquired using likely incubation periods of 3 to 7 days. Of 66,184 patients who were hospitalised during the study period, 920 had a positive SARS-CoV-2 PCR test within the same period (1.4%). The mean age was 67.9 (±20.7) years, 49.2% were females, and 68.5% were from the white ethnic group. Out of these, 571 patients had their first positive PCR tests while hospitalised (62.1%), and 97 of these occurred at least 7 days after admission (10.5%). Among the 5,596 HCWs, 615 (11.0%) tested positive during the study period using PCR or serological tests. The mean age was 39.5 (±11.1) years, 78.9% were females, and 49.8% were nurses. For susceptible patients, 1 day in the same ward with another patient with hospital-acquired SARS-CoV-2 was associated with an additional 7.5 infections per 1,000 susceptible patients (95% credible interval (CrI) 5.5 to 9.5/1,000 susceptible patients/day) per day. Exposure to an infectious patient with community-acquired Coronavirus Disease 2019 (COVID-19) or to an infectious HCW was associated with substantially lower infection risks (2.0/1,000 susceptible patients/day, 95% CrI 1.6 to 2.2). As for HCW infections, exposure to an infectious patient with hospital-acquired SARS-CoV-2 or to an infectious HCW were both associated with an additional 0.8 infection per 1,000 susceptible HCWs per day (95% CrI 0.3 to 1.6 and 0.6 to 1.0, respectively). Exposure to an infectious patient with community-acquired SARS-CoV-2 was associated with less than half this risk (0.2/1,000 susceptible HCWs/day, 95% CrI 0.2 to 0.2). These assumptions were tested in sensitivity analysis, which showed broadly similar results. The main limitations were that the symptom onset dates and HCW absence days were not available. CONCLUSIONS: In this study, we observed that exposure to patients with hospital-acquired SARS-CoV-2 is associated with a substantial infection risk to both HCWs and other hospitalised patients. Infection control measures to limit nosocomial transmission must be optimised to protect both staff and patients from SARS-CoV-2 infection.

Population-level faecal metagenomic profiling as a tool to predict antimicrobial resistance in Enterobacterales isolates causing invasive infections: An exploratory study across Cambodia, Kenya, and the UK.

BACKGROUND: Antimicrobial resistance (AMR) in Enterobacterales is a global health threat. Capacity for individual-level surveillance remains limited in many countries, whilst population-level surveillance approaches could inform empiric antibiotic treatment guidelines. METHODS: In this exploratory study, a novel approach to population-level prediction of AMR in Enterobacterales clinical isolates using metagenomic (Illumina) profiling of pooled DNA extracts from human faecal samples was developed and tested. Taxonomic and AMR gene profiles were used to derive taxonomy-adjusted population-level AMR metrics. Bayesian modelling, and model comparison based on cross-validation, were used to evaluate the capacity of each metric to predict the number of resistant Enterobacterales invasive infections at a population-level, using available bloodstream/cerebrospinal fluid infection data. FINDINGS: Population metagenomes comprised samples from 177, 157, and 156 individuals in Kenya, the UK, and Cambodia, respectively, collected between September 2014 and April 2016. Clinical data from independent populations included 910, 3356 and 197 bacterial isolates from blood/cerebrospinal fluid infections in Kenya, the UK and Cambodia, respectively (samples collected between January 2010 and May 2017). Enterobacterales were common colonisers and pathogens, and faecal taxonomic/AMR gene distributions and proportions of antimicrobial-resistant Enterobacterales infections differed by setting. A model including terms reflecting the metagenomic abundance of the commonest clinical Enterobacterales species, and of AMR genes known to either increase the minimum inhibitory concentration (MIC) or confer clinically-relevant resistance, had a higher predictive performance in determining population-level resistance in clinical Enterobacterales isolates compared to models considering only AMR gene information, only taxonomic information, or an intercept-only baseline model (difference in expected log predictive density compared to best model, estimated using leave-one-out cross-validation: intercept-only model = -223 [95% credible interval (CI): -330,-116]; model considering only AMR gene information = -186 [95% CI: -281,-91]; model considering only taxonomic information = -151 [95% CI: -232,-69]). INTERPRETATION: Whilst our findings are exploratory and require validation, intermittent metagenomics of pooled samples could represent an effective approach for AMR surveillance and to predict population-level AMR in clinical isolates, complementary to ongoing development of laboratory infrastructures processing individual samples.

Effect of Delays in Concordant Antibiotic Treatment on Mortality in Patients With Hospital-Acquired Acinetobacter Species Bacteremia: Emulating a Target Randomized Trial With a 13-Year Retrospective Cohort.

Delays in treating bacteremias with antibiotics to which the causative organism is susceptible are expected to adversely affect patient outcomes. Quantifying the impact of such delays to concordant treatment is important for decision-making about interventions to reduce the delays and for quantifying the burden of disease due to antimicrobial resistance. There are, however, potentially important biases to be addressed, including immortal time bias. We aimed to estimate the impact of delays in appropriate antibiotic treatment of patients with Acinetobacter species hospital-acquired bacteremia in Thailand on 30-day mortality by emulating a target trial using retrospective cohort data from Sunpasitthiprasong Hospital in 2003-2015. For each day, we defined treatment as concordant if the isolated organism was susceptible to at least 1 antibiotic given. Among 1,203 patients with Acinetobacter species hospital-acquired bacteremia, 682 had 1 or more days of delays to concordant treatment. Surprisingly, crude 30-day mortality was lower in patients with delays of ≥3 days compared with those who had 1-2 days of delays. Accounting for confounders and immortal time bias resolved this paradox. Emulating a target trial, we found that these delays were associated with an absolute increase in expected 30-day mortality of 6.6% (95% confidence interval: 0.2, 13.0), from 33.8% to 40.4%.