ABSTRACT
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.
Subject(s)
COVID-19 , Severe Acute Respiratory Syndrome , InfectionsABSTRACT
Background: Decisions regarding the continued need for control measures to contain the spread of SARS-CoV-2 rely on accurate and up-to-date information about the number of people and risk factors for testing positive. Existing surveillance systems are not based on population samples and are generally not longitudinal in design. Methods: From 26 April to 19 September2020, 514,794 samples from 123,497 individuals were collected from individuals aged 2 years and over from a representative sample of private households from England. Participants completed a questionnaire and nose and throat swab were taken. The percentage of individuals testing positive for SARS-CoV-2 RNA was estimated over time using dynamic multilevel regression and post-stratification, to account for potential residual non-representativeness. Potential changes in risk factors for testing positive over time were also evaluated using multilevel regression models. Findings: Between 26 April and 19 September 2020, in total, results were available from 514,794 samples from 123,497 individuals, of which 489 were positive overall from 398 individuals. The percentage of people testing positive for SARS-CoV-2 changed substantially over time, with an initial decrease between end of April and June, followed by low levels during the summer, before marked increases end of August and September 2020. Having a patient-facing role and working outside your home were important risk factors for testing positive in the first period but not (yet) in the second period of increased positivity rates, and age (young adults) being an important driver of the second period of increased positivity rates. A substantial proportion of infections were in individuals not reporting symptoms (53%-70%, dependent on calendar time). Interpretation: Important risk factors for testing positive varied substantially between the initial and second periods of higher positivity rates, and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the epidemic moving forwards.
ABSTRACT
Background: Information on COVID-19 in representative community surveillance is limited, particularly regarding cycle threshold (Ct) values (a proxy for SARS-CoV-2 viral load) and symptoms. Methods: We included all positive nose and throat swabs between 26 April-11 October 2020 from the UK national COVID-19 Infection Survey, tested by RT-PCR for the N, S and ORF1ab genes. We investigated predictors of median Ct value using quantile regression. Results: 1892(0.22%) of 843,851 results were positive, 1362(72%), 185(10%) and 345(18%) for 3, 2 or 1 genes respectively. Ct for different genes were strongly correlated (rho=0.99) with overall median Ct 26.2 (IQR 19.7-31.1; range 10.3-37.6), corresponding to ~2,500 dC/ml (IQR 80-240,000). Ct values were independently lower in those reporting symptoms, with more genes detected, and in first (vs. subsequent) positives per-participant, with no evidence of independent effects of sex, ethnicity, age, deprivation or other test characteristics (p>0.20). Whilst single-gene positives without reported symptoms almost invariably had Ct>30, triple-gene positives without reported symptoms had widely varying Ct. Incorporating pre-test probability and Ct values, 1547(82%) and 112(6%) positives had higher or lower supporting evidence for genuine infection. Ct values, symptomatic percentages and supporting evidence changed over time. With lower positivity in the summer, there were proportionally more lower evidence positives, and higher evidence positives had higher Ct values (p<0.0001), suggesting lower viral burden. Declines in mean/median Ct values were apparent throughout August and preceded increases in positivity rates. Conclusions: Community SARS-CoV-2 infections show marked variation in viral load. Ct values could be a useful epidemiological early-warning indicator.
Subject(s)
COVID-19 , Sleep Deprivation , Severe Acute Respiratory SyndromeABSTRACT
Objective: To estimate the percentage of individuals infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) over time in the community in England and to quantify risk factors. Design: Repeated cross-sectional surveys of population-representative households with longitudinal follow-up if consent given. Setting: England. Participants: 34,992 Individuals aged 2 years and over from 16,722 private residential households. Data were collected in a pilot phase of the survey between 26 April and 28 June 2020. Main outcome measures: Percentage of individuals in the community testing positive for SARS-CoV-2 RNA using throat and nose swabs. Individuals were asked about any symptoms and potential risk factors. Results: The percentage of people in private-residential households testing positive for SARS-CoV-2 reduced from 0.32% (95% credible interval (CrI) 0.19% to 0.52%) on 26 April to 0.08% (95% CrI 0.05% to 0.12%) on 28 June, although the prevalence stabilised near the end of the pilot. Factors associated with an increased risk of testing positive included having a job with direct patient contact (relative exposure (RE) 4.06, 95% CrI 2.42 to 6.77)), working outside the home (RE 2.49, 95% CrI 1.39 to 4.45), and having had contact with a hospital (RE 2.20, 95% CrI 1.09 to 4.16 for having been to a hospital individually and RE 1.95, 95% CrI 0.81 to 4.09 for a household member having been to a hospital). In 133 visits where individuals tested positive, 82 (61%, 95% CrI 53% to 69%) reported no symptoms, stably over time. Conclusion: The percentage of SARS-CoV-2 positive individuals declined between 26 April and 28 June 2020. Positive tests commonly occurred without symptoms being reported. Working outside your home was an important risk factor, indicating that continued monitoring for SARS-CoV-2 in the community will be essential for early detection of increases in infections following return to work and other relaxations of control measures.
Subject(s)
Coronavirus InfectionsABSTRACT
Nosocomial transmission of SARS-CoV-2 is a key concern and evaluating the effect of testing and infection prevention control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical UK hospital, we predict that approximately 20% of infections in inpatients, and 89% of infections in HCWs were due to nosocomial transmission. Placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 80%. Periodic testing of HCWs has a smaller effect on the patient-burden of COVID-19 but would considerably reduce infection in HCWs by as much as 64% and result in only a small proportion of staff absences (approximately 1% per day). This is considerably fewer than currently observed due to suspected COVID-19 and self-isolation.