ABSTRACT
Objective In September 2020, records of 15,861 SARS-CoV-2 cases failed to upload from the Second Generation Laboratory Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, resulting in a delay in the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on health outcomes: transmission events, hospitalisations, and mortality. Previously, a modelling study had suggested a substantial impact. Design Observational study Setting England. Population Individuals testing positive for SARS-CoV-2 and their reported contacts. Main outcome measures Secondary attack rates (SARs), hospitalisations, and deaths amongst primary and secondary contacts were calculated, compared to all other concurrent, unaffected cases. SGSS records affected by the event were matched to CTAS records and successive contacts and cases were identified. Results The initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared to the control group (3 days). This was associated with lower completion of contact tracing of primary cases in the delay group: 80% (95%CI: 79-81%) in the delay group and 83% (95%CI: 83-84%) in the control group. There was some evidence to suggest an increase in transmission to non-household contacts amongst those affected by the delay. The SAR for non-household contacts was higher amongst secondary contacts in the delay group than the control group (delay group: 7.9%, 95%CI:6.4% to 9.2%; control group: 5.9%, 95%CI: 5.3% to 6.6%). There was no evidence of a difference between the delay and control groups in the odds of hospitalisation (crude odds ratio: 1.1 (95%CI: 0.9 to 1.2) or death (crude odds ratio: 0.7 (0.1 to 4.0)) amongst secondary contacts. Conclusions The delay in contact tracing had a limited impact on population health outcomes. Strengths and limitations of the study Shows empirical data on the health impact of an event leading to a delay in contact tracing so can test hypotheses generated by models of the potential impact of a delay in contact tracing Estimates the extent of further transmission and odds of increased mortality or hospitalisation in up to the third generation of cases affected by the event The event acts as a natural experiment to describe the possible impact of contact tracing, comparing a group affected by chance by delayed contact tracing to a control group who experienced no delay Contact tracing was not completed for all individuals, so the study might not capture all affected contacts or transmissions
Subject(s)
COVID-19ABSTRACT
Background The SARS-CoV-2 Omicron variant (B.1.1.529) has rapidly replaced the Delta variant (B.1.617.2) to become dominant in England. This epidemiological study assessed differences in transmissibility between the Omicron and Delta using two methods and data sources. Methods Omicron and Delta cases were identified through genomic sequencing, genotyping and S-gene target failure in England from 5-11 December 2021. Secondary attack rates for Omicron and Delta using named contacts and household clustering were calculated using national surveillance and contact tracing data. Logistic regression was used to control for factors associated with transmission. Findings Analysis of contact tracing data identified elevated secondary attack rates for Omicron vs Delta in household (15.0% vs 10.8%) and non-household (8.2% vs 3.7%) settings. The proportion of index cases resulting in residential clustering was twice as high for Omicron (16.1%) compared to Delta (7.3%). Transmission was significantly less likely from cases, or in named contacts, in receipt of three compared to two vaccine doses in household settings, but less pronounced for Omicron (aRR 0.78 and 0.88) compared to Delta (aRR 0.62 and 0.68). In non-household settings, a similar reduction was observed for Delta cases and contacts (aRR 0.84 and 0.51) but only for Omicron contacts (aRR 0.76, 95% CI: 0.58-0.93) and not cases in receipt of three vs two doses (aRR 0.95, 0.77-1.16). Interpretation Our study identified increased risk of onward transmission of Omicron, consistent with its successful global displacement of Delta. We identified a reduced effectiveness of vaccination in lowering risk of transmission, a likely contributor for the rapid propagation of Omicron.
ABSTRACT
Background: Universities in England returned to in–person teaching in September 2020, requiring a large migration of students across the country. To understand the impact this had on COVID–19 transmission, we identified and described student cases during the 2020 autumn term. Methods: Student COVID–19 cases were identified from two sources: contact tracing records identifying attendance at university prior to onset and residence in student accommodation identified from matching cases’ residential addresses against national property databases. Residential outbreaks were defined as ≥2 cases with specimen dates within 14 days residing in the same property. A matched analysis of COVID–19 rates and trends in towns/cities with and without a university campus was undertaken. Findings: We identified 53,430 student cases between 1 September and 31 December 2020, constituting 2·7% of all cases (n=1,999,180) in this time period; 39,032 reported attendance at a university during contact tracing; 19,901 resided in student accommodation premises. Cases increased rapidly following the start of term driven initially by cases in student accommodation. Over two thirds (72·2% n=14,375) of cases in student accommodation were part of a residential outbreak.Towns/cities with universities saw a threefold increase in rates amongst 18–23 year olds compared to non–university towns. Interpretation: This study suggests that the return to university teaching and associated movement of students in England was linked to large increases in SARS–CoV–2 transmission amongst this population and potentially contributing to subsequent large increases in the wider population surrounding a campus. Funding Information: No funding was received for this work. Declaration of Interests: None of the authors declare any conflicts of interest.Ethics Approval Statement: UKHSA has legal permission, provided by Regulation 3 of The Health Service (Control of Patient Information) Regulations 2002, to process patient confidential information for national surveillance of communicable diseases and as such, individual patient consent is not required.
Subject(s)
COVID-19ABSTRACT
Assessing the impact of an intervention using time-series observational data on multiple units and outcomes is a frequent problem in many fields of scientific research. In this paper, we present a novel method to estimate intervention effects in such a setting by generalising existing approaches based on the factor analysis model and developing a Bayesian algorithm for inference. Our method is one of the few that can simultaneously: deal with outcomes of mixed type (continuous, binomial, count); increase efficiency in the estimates of the causal effects by jointly modelling multiple outcomes affected by the intervention; easily provide uncertainty quantification for all causal estimands of interest. We use the proposed approach to evaluate the impact that local tracing partnerships (LTP) had on the effectiveness of England's Test and Trace (TT) programme for COVID-19. Our analyses suggest that, overall, LTPs had a small positive impact on TT. However, there is considerable heterogeneity in the estimates of the causal effects over units and time.
Subject(s)
COVID-19ABSTRACT
Background How SARS-CoV-2 infectivity varies with viral load is incompletely understood. Whether rapid point-of-care antigen lateral flow devices (LFDs) detect most potential transmission sources despite imperfect sensitivity is unknown. Methods We combined SARS-CoV-2 testing and contact tracing data from England between 01-September-2020 and 28-February-2021. We used multivariable logistic regression to investigate relationships between PCR-confirmed infection in contacts of community-diagnosed cases and index case viral load, S gene target failure (proxy for B.1.1.7 infection), demographics, SARS-CoV-2 incidence, social deprivation, and contact event type. We used LFD performance to simulate the proportion of cases with a PCR-positive contact expected to be detected using one of four LFDs. Results 231,498/2,474,066 (9%) contacts of 1,064,004 index cases tested PCR-positive. PCR-positive results in contacts independently increased with higher case viral loads (lower Ct values) e.g., 11.7%(95%CI 11.5-12.0%) at Ct=15 and 4.5%(4.4-4.6%) at Ct=30. B.1.1.7 infection increased PCR-positive results by ∼50%, (e.g. 1.55-fold, 95%CI 1.49-1.61, at Ct=20). PCR-positive results were most common in household contacts (at Ct=20.1, 8.7%[95%CI 8.6-8.9%]), followed by household visitors (7.1%[6.8-7.3%]), contacts at events/activities (5.2%[4.9-5.4%]), work/education (4.6%[4.4-4.8%]), and least common after outdoor contact (2.9%[2.3-3.8%]). Contacts of children were the least likely to test positive, particularly following contact outdoors or at work/education. The most and least sensitive LFDs would detect 89.5%(89.4-89.6%) and 83.0%(82.8-83.1%) of cases with PCR-positive contacts respectively. Conclusions SARS-CoV-2 infectivity varies by case viral load, contact event type, and age. Those with high viral loads are the most infectious. B.1.1.7 increased transmission by ∼50%. The best performing LFDs detect most infectious cases. Key points In 2,474,066 contacts of 1,064,004 SARS-CoV-2 cases, PCR-positive tests in contacts increased with higher index case viral loads, the B.1.1.7 variant and household contact. Children were less infectious. Lateral flow devices can detect 83.0-89.5% of infections leading to onward transmission.
ABSTRACT
Background: Households appear to be the highest risk setting for transmission of COVID-19. Large household transmission studies were reported in the early stages of the pandemic in Asia with secondary attack rates ranging from 5-30% but few large scale household transmission studies have been conducted outside of Asia. Methods: A prospective case ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. Household secondary attack rates and serial intervals were estimated. Individual and household basic reproduction numbers were also estimated. The incubation period was estimated using known point source exposures that resulted in secondary cases. Results: A total of 233 households with two or more people were included with a total of 472 contacts. The overall household SAR was 37% (95% CI 31-43%) with a mean serial interval of 4.67 days, an R0 of 1.85 and a household reproduction number of 2.33. We find lower secondary attack rates in larger households. SARs were highest when the primary case was a child. We estimate a mean incubation period of around 4.5 days. Conclusions: High rates of household transmission of COVID-19 were found in the UK emphasising the need for preventative measures in this setting. Careful monitoring of schools reopening is needed to monitor transmission from children.