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

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{middle dot}1%-15{middle dot}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 contextO_ST_ABSEvidence before this studyC_ST_ABSWe 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.

Transmission dynamics of SARS-CoV-2 in the hospital setting

BackgroundSARS-CoV-2 can spread efficiently in hospitals, but the transmission pathways amongst patients and healthcare workers are unclear. MethodsWe analysed data from four teaching hospitals in Oxfordshire, UK, 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. ResultsNine-hundred and twenty of 66184 patients who were hospitalised during the study period had a positive SARS-CoV-2 PCR test within the same period (1%). Out of these, 571 patients had their first positive PCR tests while hospitalised (62%), and 97 of these occurred at least seven days after admission (11%). Amongst the 5596 healthcare workers, 615 (11%) tested positive during the study period using PCR or serological tests. For susceptible patients, one day in the same ward with another patient with hospital-acquired SARS-CoV-2 was associated with an additional eight infections per 1000 susceptible patients (95%CrI 6-10). Exposure to an infectious patient with community-acquired COVID-19 or to an infectious healthcare worker was associated with substantially lower infection risks (2/1000 susceptible patients/day, 95%CrI 1-2). As for healthcare worker infections, exposure to an infectious patient with hospital-acquired SARS-CoV-2 or to an infectious healthcare worker were both associated with an additional one infection per 1000 susceptible healthcare workers per day (95%CrI 1-2). Exposure to an infectious patient with community-acquired SARS-CoV-2 was associated with half this risk (0.5/1000 susceptible healthcare workers/day, 95%CrI 0.3-0.7). InterpretationExposure to patients with hospital-acquired SARS-CoV-2 poses a substantial infection risk. Infection control measures to limit nosocomial transmission must be optimised to protect both staff and patients from SARS-CoV-2 infection. FundingNational Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University in partnership with Public Health England (PHE) (NIHR200915). Medical Research Council, Nosocomial transmission of SARS-CoV-2 (MR/V028456/1). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched the PubMed database using the search terms ("COVID-19" OR "SARS-CoV-2") AND ("nosocomial" OR "hospital") AND ("transmission") in either the abstracts or titles, for English-language articles published up to March 31, 2021. This returned 748 results, out of which ten reported transmission events in the hospital setting quantitatively. These publications can be broadly categorised to epidemiological descriptions of isolated outbreaks (5) or contact tracing of patients exposed to infected healthcare workers (1), retrospective cohort studies involving a particular group of patients, e.g., patients who underwent surgical procedures (2), and using genomic sequencing to identify transmission clusters (2). None of the studies reported the comparative transmission rates of SARS-CoV-2 amongst patients and staff. Added value of this studyThis study reports the analysis of a large observational dataset collected from a group of hospitals in the UK over eight months, consisting of both hospitalised patients and healthcare workers. Based on these detailed individual-level data, we quantified the associations between patient and healthcare worker characteristics and risks for acquiring nosocomial SARS-CoV-2 infection after adjusting for their exposures to SARS-CoV-2. Over the study period, we describe how risk of acquisition changes both with calendar time and over a patients hospital stay. By linking the presence of infected and susceptible patients and healthcare workers by time and ward locations, we quantify the relative importance of the transmission pathways for both the susceptible patients and healthcare workers. Implications of all the available evidenceNosocomial transmission of SARS-CoV-2 is common. Identifying the drivers of SARS-CoV-2 transmissions in the hospital setting is essential for designing infection prevention and control policies to minimise the added pressure from such events on our health systems. We found that newly infected patients who acquired SARS-CoV-2 in the hospital pose the highest risk of onward transmission to other patients and healthcare workers. Infection control and prevention efforts need to be enhanced around these patients to prevent further transmissions and studies assessing the effectiveness of these policies are needed.

Quantifying HIV-1 transmission due to contaminated injections.

Assessments of the importance of different routes of HIV-1 (HIV) transmission are vital for prioritization of control efforts. Lack of consistent direct data and large uncertainty in the risk of HIV transmission from HIV-contaminated injections has made quantifying the proportion of transmission caused by contaminated injections in sub-Saharan Africa difficult and unavoidably subjective. Depending on the risk assumed, estimates have ranged from 2.5% to 30% or more. We present a method based on an age-structured transmission model that allows the relative contribution of HIV-contaminated injections, and other routes of HIV transmission, to be robustly estimated, both fully quantifying and substantially reducing the associated uncertainty. To do this, we adopt a Bayesian perspective, and show how prior beliefs regarding the safety of injections and the proportion of HIV incidence due to contaminated injections should, in many cases, be substantially modified in light of age-stratified incidence and injection data, resulting in improved (posterior) estimates. Applying the method to data from rural southwest Uganda, we show that the highest estimates of the proportion of incidence due to injections are reduced from 15.5% (95% credible interval) (0.7%, 44.9%) to 5.2% (0.5%, 17.0%) if random mixing is assumed, and from 14.6% (0.7%, 42.5%) to 11.8% (1.2%, 32.5%) under assortative mixing. Lower, and more widely accepted, estimates remain largely unchanged, between 1% and 3% (0.1-6.3%). Although important uncertainty remains, our analysis shows that in rural Uganda, contaminated injections are unlikely to account for a large proportion of HIV incidence. This result is likely to be generalizable to many other populations in sub-Saharan Africa.