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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.

Hospital-based transmission played a dominant role in MERS-CoV and SARS-CoV epidemics 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 show that hospital transmission is likely to have been a major contributor to the burden of COVID-19 in England. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 patients acquired SARS-CoV-2 in hospitals with nosocomially-infected patients likely to have been the main sources of transmission to other patients. Increased transmission to patients 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 unrecognised 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.

Summary 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.

BackgroundSARS-CoV-2 spreads in hospitals, but the contribution of these settings to the overall COVID-19 burden at a national level is unknown.MethodsWe used comprehensive national English datasets and simulation modelling to determine the total burden (identified and unidentified) of symptomatic hospital-acquired infections. Those unidentified would either be 1) discharged before symptom onset (“missed”), or 2) have symptom onset 7 days or fewer from admission (“misclassified”). We estimated the contribution of “misclassified” cases and transmission from “missed” symptomatic infections to the English epidemic before 31st July 2020.FindingsIn our dataset of hospitalised COVID-19 patients in acute English Trusts with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired (with symptom onset 8 or more days after admission and before discharge). We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified. Misclassified cases and onward transmission from missed infections could account for 15% (mean, 95% range over 200 simulations: 14·1%-15·8%) of cases currently classified as community-acquired COVID-19.From this, 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.ConclusionsTransmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the “first wave”, but fewer than 1% of all SARS-CoV-2 infections in England. Using symptom onset as a detection method for hospital-acquired SARS-CoV-2 likely misses a substantial proportion (>60%) of hospital-acquired infections.FundingNational Institute for Health Research, UK Medical Research Council, Society for Laboratory Automation and Screening, UKRI, Wellcome Trust, Singapore National Medical Research Council.Research in contextEvidence before this studyWe searched PubMed with the terms “((national OR country) AND (contribution OR burden OR estimates) AND (“hospital-acquired” OR “hospital-associated” OR “nosocomial”)) AND Covid-19” for articles published in English up to July 1st 2021. This identified 42 studies, with no studies that had aimed to produce comprehensive national estimates of the contribution of hospital settings to the COVID-19 pandemic. Most studies focused on estimating seroprevalence or levels of infection in healthcare workers only, which were not our focus. Removing the initial national/country terms identified 120 studies, with no country level estimates. Several single hospital setting estimates exist for England and other countries, but the percentage of hospital-associated infections reported relies on identified cases in the absence of universal testing.Added value of this studyThis study provides the first national-level estimates of all symptomatic hospital-acquired infections with SARS-CoV-2 in England up to the 31st July 2020. Using comprehensive data, we calculate how many infections would be unidentified and hence can generate a total burden, impossible from just notification data. Moreover, our burden estimates for onward transmission suggest the contribution of hospitals to the overall infection burden.Implications of all the available evidenceLarge numbers of patients may become infected with SARS-CoV-2 in hospitals though only a small proportion of such infections are identified. Further work is needed to better understand how interventions can reduce such transmission and to better understand the contributions of hospital transmission to mortality.

Background Despite evidence of the nosocomial transmission of novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in hospitals worldwide, the contributions of the pathways of transmission are poorly quantified. Methods We analysed national records of hospital admissions and discharges, linked to data on SARS-CoV-2 testing, using an individual-based model that considers patient-to-patient, patient-to-healthcare worker (HCW), HCW-to-patient and HCW-to-HCW transmission. Results Between 1 March 2020 and 31 December 2020, SARS-CoV-2 infections that were classified as nosocomial were identified in 0.5% (0.34–0.74) of patients admitted to an acute National Health Service trust. We found that the most likely route of nosocomial transmission to patients was indirect transmission from other infected patients, e.g. through HCWs acting as vectors or contaminated fomites, followed by direct transmission between patients in the same bay. The risk of transmission to patients from HCWs over this time period is low, but can contribute significantly when the number of infected inpatients is low. Further, the risk of a HCW acquiring SARS-CoV-2 in hospital is approximately equal to that in the community, thereby doubling their overall risk of infection. The most likely route of transmission to HCWs is transmission from other infected HCWs. Conclusions Current control strategies have successfully reduced the transmission of SARS-CoV-2 between patients and HCWs. In order to reduce the burden of nosocomial COVID-19 infections on health services, stricter measures should be enforced that would inhibit the spread of the virus between bays or wards in the hospital. There should also be a focus on inhibiting the spread of SARS-CoV-2 between HCWs. The findings have important implications for infection-control procedures in hospitals.

The effects of global change on human health have attracted increasing attention in recent years, with anthropogenic influences thought to have significant influences on the Earth’s climate (Intergovernmental Panel on Climate Change [IPCC], 2007). Climate change is thought likely to have important effects on human, animal and plant life. In addition to indirect effects on human behaviour such as shifting migration patterns, direct effects of climate change on human health are potentially severe. Together with implications through changing air quality, increased exposure to UV radiation, changes in food production, increasing water shortages and contamination, and economic instability, climate change is widely expected to also significantly affect the global spread, intensity and distribution of infectious diseases (Hunter, 2003; McMichael et al., 2006). In this chapter, we review current knowledge on the impacts of global change on infectious diseases (Section 1), highlighting how combining global and regional climate models with mathematical (and statistical) models of disease transmission (Section 2) provides valuable tools for better understanding future disease scenarios as environmental conditions change. Such models may be used to address important questions on the current and projected impacts of climate change on disease transmission and we illustrate these issues (and the extent to which they have been addressed in modelling work to date) in Section 3. It should be remembered, however, that despite the power of weather, climate and disease models, considerable uncertainties remain. Identifying the origin of these uncertainties, highlighting where improved data may improve model accuracy, realism and confidence, together with translating uncertainties in model inputs into uncertainties in model outputs, are important benefits of modelling. Highlighting where key uncertainties lie is discussed in Section 4, illustrating where future research priorities may be directed to further our understanding of this emerging field.