Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England (preprint)

Mathematical modelling has played an important role in offering informed advice during the COVID-19 pandemic. In England, a cross government and academia collaboration generated Medium-Term Projections (MTPs) of possible epidemic trajectories over the future 4-6 weeks from a collection of epidemiological models.In this paper we outline this collaborative modelling approach and evaluate the accuracy of the combined and individual model projections against the data over the period November 2021-December 2022 when various Omicron subvariants were spreading across England. Using a number of statistical methods, we quantify the predictive performance of the model projections for both the combined and individual MTPs, by evaluating the point and probabilistic accuracy. Our results illustrate that the combined MTPs, produced from an ensemble of heterogeneous epidemiological models, were a closer fit to the data than the individual models during the periods of epidemic growth or decline, with the 90% confidence intervals widest around the epidemic peaks. We also show that the combined MTPs increase the robustness and reduce the biases associated with a single model projection. Learning from our experience of ensemble modelling during the COVID-19 epidemic, our findings highlight the importance of developing cross-institutional multi-model infectious disease hubs for future outbreak control.

Protection of second booster vaccinations and prior infection against SARS-CoV-2 in the UK SIREN healthcare worker cohort (preprint)

Background The protection of fourth dose mRNA vaccination against SARS-CoV-2 is relevant to current global policy decisions regarding ongoing booster roll-out. We estimate the effect of fourth dose vaccination, prior infection, and duration of PCR positivity in a highly-vaccinated and largely prior-COVID-19 infected cohort of UK healthcare workers. Methods Participants underwent fortnightly PCR and regular antibody testing for SARS-CoV-2 and completed symptoms questionnaires. A multi-state model was used to estimate vaccine effectiveness (VE) against infection from a fourth dose compared to a waned third dose, with protection from prior infection and duration of PCR positivity jointly estimated. Results 1,298 infections were detected among 9,560 individuals under active follow-up between September 2022 and March 2023. Compared to a waned third dose, fourth dose VE was 13.1% (95%CI 0.9 to 23.8) overall; 24.0% (95%CI 8.5 to 36.8) in the first two months post-vaccination, reducing to 10.3% (95%CI -11.4 to 27.8) and 1.7% (95%CI -17.0 to 17.4) at 2-4 and 4-6 months, respectively. Relative to an infection >2 years ago and controlling for vaccination, 63.6% (95%CI 46.9 to 75.0) and 29.1% (95%CI 3.8 to 43.1) greater protection against infection was estimated for an infection within the past 0-6, and 6-12 months, respectively. A fourth dose was associated with greater protection against asymptomatic infection than symptomatic infection, whilst prior infection independently provided more protection against symptomatic infection, particularly if the infection had occurred within the previous 6 months. Duration of PCR positivity was significantly lower for asymptomatic compared to symptomatic infection. Conclusions Despite rapid waning of protection, vaccine boosters remain an important tool in responding to the dynamic COVID-19 landscape; boosting population immunity in advance of periods of anticipated pressure, such as surging infection rates or emerging variants of concern. Funding UK Health Security Agency, Medical Research Council, NIHR HPRU Oxford, and others.

Effectiveness of BNT162b2 mRNA vaccine third doses and previous infection in protecting against SARS-CoV-2 infections during the Delta and Omicron variant waves; the UK SIREN cohort study September 2021 to February 2022 (preprint)

Third doses of COVID-19 vaccines were widely deployed following primary vaccine course waning and emergence of the Omicron-variant. We investigated protection from third-dose vaccines and previous infection against SARS-CoV-2 infection during Delta-variant and Omicron-variant (BA.1 & BA.2) waves in our frequently PCR-tested cohort of healthcare-workers. Relative effectiveness of BNT162b2 third doses and infection-acquired immunity was assessed by comparing the time to PCR-confirmed infection in boosted participants with those with waned dose-2 protection ([≥]254 days after dose-2). Follow-up time was divided by dominant circulating variant: Delta 07 September 2021 to 30 November 2021, Omicron 13 December 2021 to 28 February 2022. We used a Cox regression model with adjustment/stratification for demographic characteristics and staff-type. We explored protection associated with vaccination, infection and both. We included 19,614 participants, 29% previously infected. There were 278 primary infections (4 per 10,000 person-days of follow-up) and 85 reinfections (0.8/10,000 person-days) during the Delta period and 2467 primary infections (43/10,000 person-days) and 881 reinfections (33/10,000) during the Omicron period. Relative Vaccine Effectiveness (VE) 0-2 months post-3rd dose (V3) (3-doses BNT162b2) in the previously uninfected cohort against Delta infections was 63% (95% Confidence Interval (CI) 40%-77%) and was lower (35%) against Omicron infection (95% CI 21%-47%). For primary course ChAdOX1 recipients, BNT162b2 heterologous third doses were especially effective, with VE 0-2 months post-V3 over [≥]68% higher for both variants. Third-dose protection waned rapidly against Omicron, with no significant difference between two and three BNT162b2 doses observed after 4-months. Previous infection continued to provide additional protection against Omicron (67% (CI 56%-75%) 3-6 months post-infection), but this waned to about 25% after 9-months, approximately three times lower than against Delta. Infection rates surged with Omicron emergence. Third doses of BNT162b2 vaccine provided short-term protection, with rapid waning against Omicron infections. Protection associated with infections incurred before Omicron was markedly diminished against the Omicron wave. Our findings demonstrate the complexity of an evolving pandemic with potential emergence of immune-escape variants and the importance of continued monitoring.

Global surveillance of novel SARS-CoV-2 variants (preprint)

Earlier global detection of novel SARS-CoV-2 variants gives governments more time to respond. However, few countries can implement timely national surveillance resulting in gaps in monitoring. The UK implemented large-scale community and hospital surveillance, but experience suggests it may be faster to detect new variants through testing UK arrivals for surveillance. We developed simulations of the emergence and importation of novel variants with a range of infection hospitalisation rates (IHR) to the UK. We compared time taken to detect the variant though testing arrivals at UK borders, hospital admissions, and the general community. We found that sampling 10 to 50% of arrivals at UK borders could confer a speed advantage of 3.5 to 6 weeks over existing community surveillance, and 1.5 to 5 weeks (depending on IHR) over hospital testing. We conclude that directing limited global capacity for surveillance to highly connected ports could speed up global detection of novel SARS-CoV-2 variants.

Combining models to generate a consensus effective reproduction number R for the COVID-19 epidemic status in England (preprint)

The effective reproduction number R was widely accepted as a key indicator during the early stages of the COVID-19 pandemic. In the UK, the R value published on the UK Government Dashboard has been generated as a combined value from an ensemble of fourteen epidemiological models via a collaborative initiative between academia and government. In this paper we outline this collaborative modelling approach and illustrate how, by using an established combination method, a combined R estimate can be generated from an ensemble of epidemiological models. We show that this R is robust to different model weighting methods and ensemble size and that using heterogeneous data sources for validation increases its robustness and reduces the biases and limitations associated with a single source of data. We discuss how R can be generated from different data sources and is therefore a good summary indicator of the current dynamics in an epidemic.

The interplay between pre-season population susceptibility and the effectiveness of the rolled out vaccination control the timing and size of an emerging seasonal influenza wave in England (preprint)

Relaxing social distancing measures and reduced level of influenza over the last two seasons may lead to a winter 2022 influenza wave in England. We used an established model for influenza transmission and vaccination to evaluate the rolled out influenza immunisation programme over October to December 2022. Specifically, we explored how the interplay between pre-season population susceptibility and influenza vaccine efficacy control the timing and the size of a possible winter influenza wave. Our findings suggest that susceptibility affects the timing and the height of a potential influenza wave, with higher susceptibility leading to an earlier and larger influenza wave while vaccine efficacy controls the size of the peak of the influenza wave. With pre-season susceptibility higher than pre-COVID-19 levels, under the planned vaccine programme an early influenza epidemic wave is possible, its size dependent on vaccine effectiveness against the circulating strain. If pre-season susceptibility is low and similar to pre-COVID levels, the planned influenza vaccine programme with an effective vaccine could largely suppress a winter 2022 influenza outbreak in England.

Evaluating the impact on health outcomes of an event that resulted in a delay in contact tracing of COVID-19 cases (preprint)

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

Comparative transmission of SARS-CoV-2 Omicron (B.1.1.529) and Delta (B.1.617.2) variants and the impact of vaccination: national cohort study, England (preprint)

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.

Early signals of Omicron severity in sentinel UK hospitals (preprint)

On 26th November 2021, a novel SARS-CoV-2 variant B.1.1.529 (Omicron variant) was designated as a variant of concern by the World Health Organisation. Using data from the Virology laboratory at the Manchester Medical Microbiology Partnership (MMMP, a partnership between UKHSA and the Manchester Foundation Trust), we have extracted a real-time feed of Omicron samples from hospitals across Greater Manchester, an area of the United Kingdom with a population size of approximately three million individuals. Omicron hospital samples are growing exponentially across Greater Manchester (doubling time 2.7 days (95% CI: 2.1, 3.7)). The proportion of Omicron in hospital samples follows a similar trajectory to the SGTF proportion in cases, but with a two-day offset. This is consistent with the delay from testing positive to hospital admission, implying a similar proportion of Omicron cases are converting to hospital admissions as for Delta cases. Comparing the Greater Manchester data to national hospitalisation data, similar tends are observed. Therefore, there is no signal of a substantial reduction in hospital admission risk with Omicron, and Omicron epidemics are likely to place a substantial burden on public health infrastructure.

Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study (preprint)

Widespread vaccination campaigns have changed the landscape for COVID-19, vastly altering symptoms and reducing morbidity and mortality. We estimate trends in mortality by month of admission and vaccination status among those hospitalised with COVID-19 in England between March 2020 to September 2021, controlling for demographic factors and hospital load. Among 259,727 hospitalised COVID-19 cases, 51,948 (20.0%) experienced mortality in hospital. Hospitalised fatality risk ranged from 40.3% (95% confidence interval 39.4-41.3%) in March 2020 to 8.1% (7.2-9.0%) in June 2021. Older individuals and those with multiple co-morbidities were more likely to die or else experienced longer stays prior to discharge. Compared to unvaccinated people, the hazard of hospitalised mortality was 0.71 (0.67-0.77) with a first vaccine dose, and 0.56 (0.52-0.61) with a second vaccine dose. Compared to hospital load at 0-20% of the busiest week, the hazard of hospitalised mortality during periods of peak load (90-100%), was 1.23 (1.12-1.34). The prognosis for people hospitalised with COVID-19 in England has varied substantially throughout the pandemic and according to case-mix, vaccination, and hospital load. Our estimates provide an indication for demands on hospital resources, and the relationship between hospital burden and outcomes.

Effectiveness and durability of protection against future SARS-CoV-2 infection conferred by COVID-19 vaccination and previous infection; findings from the UK SIREN prospective cohort study of healthcare workers March 2020 to September 2021 (preprint)

BackgroundUnderstanding the duration and effectiveness of infection and vaccine-acquired SARS-CoV-2 immunity is essential to inform pandemic policy interventions, including the timing of vaccine-boosters. We investigated this in our large prospective cohort of UK healthcare workers undergoing routine asymptomatic PCR testing. MethodsWe assessed vaccine effectiveness (VE) (up to 10-months after first dose) and infection-acquired immunity by comparing time to PCR-confirmed infection in vaccinated and unvaccinated individuals using a Cox regression-model, adjusted by prior SARS-CoV-2 infection status, vaccine-manufacturer/dosing-interval, demographics and workplace exposures. ResultsOf 35,768 participants, 27% (n=9,488) had a prior SARS-CoV-2 infection. Vaccine coverage was high: 97% had two-doses (79% BNT162b2 long-interval, 8% BNT162b2 short-interval, 8% ChAdOx1). There were 2,747 primary infections and 210 reinfections between 07/12/2020 and 21/09/2021. Adjusted VE (aVE) decreased from 81% (95% CI 68%-89%) 14-73 days after dose-2 to 46% (95% CI 22%-63%) >6-months; with no significant difference for short-interval BNT162b2 but significantly lower aVE (50% (95% CI 18%-70%) 14-73 days after dose-2 from ChAdOx1. Protection from infection-acquired immunity showed evidence of waning in unvaccinated follow-up but remained consistently over 90% in those who received two doses of vaccine, even in those infected over 15-months ago. ConclusionTwo doses of BNT162b2 vaccination induce high short-term protection to SARS-CoV-2 infection, which wanes significantly after six months. Infection-acquired immunity boosted with vaccination remains high over a year after infection. Boosters will be essential to maintain protection in vaccinees who have not had primary infection to reduce infection and transmission in this population. Trial registration numberISRCTN11041050

Long-term health-related quality of life in non-hospitalised COVID-19 cases with confirmed SARS-CoV-2 infection in England: Longitudinal analysis and cross-sectional comparison with controls (preprint)

Background This study measured the long-term health-related quality of life of non-hospitalised COVID-19 cases with PCR-confirmed SARS-CoV-2(+) infection using the recommended instrument in England (the EQ-5D). Methods Prospective cohort study of SARS-CoV-2(+) cases aged 12-85 years and followed up for six months from 01 December 2020, with cross-sectional comparison to SARS-CoV-2(-) controls. Main outcomes were loss of quality-adjusted life days (QALDs); physical symptoms; and COVID-19-related private expenditures. We analysed results using multivariable regressions with post-hoc weighting by age and sex, and conditional logistic regressions for the association of each symptom and EQ-5D limitation on cases and controls. Results Of 548 cases (mean age 41.1 years; 61.5% female), 16.8% reported physical symptoms at month 6 (most frequently extreme tiredness, headache, loss of taste and/or smell, and shortness of breath). Cases reported more limitations with doing usual activities than controls. Almost half of cases spent a mean of £18.1 on non-prescription drugs (median: £10.0), and 52.7% missed work or school for a mean of 12 days (median: 10). On average, all cases lost 15.9 (95%-CI: 12.1, 19.7) QALDs, while those reporting symptoms at month 6 lost 34.1 (29.0, 39.2) QALDs. Losses also increased with older age. Cumulatively, the health loss from morbidity contributes at least 21% of the total COVID-19-related disease burden in England. Conclusions One in 6 cases report ongoing symptoms at 6 months, and 10% report prolonged loss of function compared to pre-COVID-19 baselines. A marked health burden was observed among older COVID-19 cases and those with persistent physical symptoms. summary Losses of health-related quality of life in non-hospitalised COVID-19 cases increase by age and for cases with symptoms after 6 months. At a population level, at least 21% of the total COVID-19-related disease burden in England is attributable to morbidity.

Evaluating the impact of local tracing partnerships on the performance of contact tracing for COVID-19 in England (preprint)

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.

Hospitalisation risk for COVID-19 patients infected with SARS-CoV-2 variant B.1.1.7: cohort analysis (preprint)

Objective: To evaluate the relationship between coronavirus disease 2019 (COVID-19) diagnosis with SARS-CoV-2 variant B.1.1.7 (also known as Variant of Concern 202012/01) and the risk of hospitalisation compared to diagnosis with wildtype SARS-CoV-2 variants. Design: Retrospective cohort, analysed using stratified Cox regression. Setting: Community-based SARS-CoV-2 testing in England, individually linked with hospitalisation data. Participants: 839,278 laboratory-confirmed COVID-19 patients, of whom 36,233 had been hospitalised within 14 days, tested between 23rd November 2020 and 31st January 2021 and analysed at a laboratory with an available TaqPath assay that enables assessment of S-gene target failure (SGTF). SGTF is a proxy test for the B.1.1.7 variant. Patient data were stratified by age, sex, ethnicity, deprivation, region of residence, and date of positive test. Main outcome measures: Hospitalisation between 1 and 14 days after the first positive SARS-CoV-2 test. Results: 27,710 of 592,409 SGTF patients (4.7%) and 8,523 of 246,869 non-SGTF patients (3.5%) had been hospitalised within 1-14 days. The stratum-adjusted hazard ratio (HR) of hospitalisation was 1.52 (95% confidence interval [CI] 1.47 to 1.57) for COVID-19 patients infected with SGTF variants, compared to those infected with non-SGTF variants. The effect was modified by age (P<0.001), with HRs of 0.93-1.21 for SGTF compared to non-SGTF patients below age 20 years, 1.29 in those aged 20-29, and 1.45-1.65 in age groups 30 years or older. Conclusions: The results suggest that the risk of hospitalisation is higher for individuals infected with the B.1.1.7 variant compared to wildtype SARS-CoV-2, likely reflecting a more severe disease. The higher severity may be specific to adults above the age of 30.

SARS-CoV-2 infectivity by viral load, S gene variants and demographic factors and the utility of lateral flow devices to prevent transmission (preprint)

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.

Assessment of Mortality and Hospital Admissions Associated with Confirmed Infection with SARS-CoV-2 Variant of Concern VOC-202012/01 (B.1.1.7) a Matched Cohort and Time-to-Event Analysis (preprint)

Background: The emergence of VOC202012/01 in England, known as B.1.1.7 or informally as the ‘UK variant’, has coincided with rapid increases in the number of PCR-confirmed positive cases in areas where the variant has been concentrated. Methods: To assess whether infection with SARS-CoV-2 variant VOC202012/01 is associated with more severe clinical outcomes compared to wild-type infection, genomically sequenced and confirmed variant and wild-type cases were linked to routine healthcare and surveillance datasets. Two statistical analyses were conducted to compare the risk of hospital admission and death within 28 days of test between variant and wild-type cases: a case-control study and an adjusted Cox proportional hazards model. Differences in severity of disease were assessed by comparing hospital admission and mortality, including length of hospitalisation and time to death.Results: Of 63,609 genomically sequenced COVID-19 cases tested in England between October and December 2020 6,038 were variant cases. In the matched cohort analysis 2,821 variant cases were matched to 2,821 to wild-type cases. In the time to event analysis we observed a 34% increased risk in hospitalisation associated with the variant compared to wild-type cases, however, no significant difference in the risk of mortality was observed. Conclusion: We found evidence of increased risk of hospitalisation after adjusting for key confounders, suggesting increase infection severity associated with this variant. Follow-up studies are needed to assess potential longer-term differences in the clinical outcomes of people infected with the VOC-202012/01 variant.

The spatio-temporal distribution of COVID-19 infection in England between January and June 2020. (preprint)

The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed. A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk. Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first six months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on the 23rd March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout. In terms of controlling transmission, the most important practical application is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.

Effectiveness of BNT162b2 mRNA Vaccine Against Infection and COVID-19 Vaccine Coverage in Healthcare Workers in England, Multicentre Prospective Cohort Study (the SIREN Study) (preprint)

Background: BNT162b2 mRNA and ChAdOx1 nCOV-19 adenoviral vector vaccines have been rapidly rolled out in the UK. We determined the factors associated with vaccine coverage for both vaccines and documented the vaccine effectiveness of the BNT162b2 mRNA vaccine in our healthcare worker (HCW) cohort study of staff undergoing regular asymptomatic testing.Methods: The SIREN study is a prospective cohort study among staff working in publicly funded hospitals. Baseline risk factors, vaccination status (from 8/12/2020-5/2/2021), and symptoms are recorded at 2 weekly intervals and all SARS-CoV-2 polymerase chain reaction (PCR) and antibody test results documented. A mixed effect proportional hazards frailty model using a Poisson distribution was used to calculate hazard ratios to compare time to infection in unvaccinated and vaccinated participants to estimate the impact of the BNT162b2 vaccine on all (asymptomatic and symptomatic) infection.Findings: Vaccine coverage was 89% on 5/2/2021. Significantly lower coverage was associated with prior infection (aOR 0.59 95% confidence interval [CI] 0.54-0.64), female (aOR 0.72, 95% CI 0.63-0.82), aged under 35 years, being from minority ethnic groups (especially Black, aOR 0.26, 95% CI 0.21-0.32), porters/security guards (aOR 0.61, 95% CI 0.42-0.90),or midwife (aOR 0.74, 95% CI 0.57-0.97), and living in more deprived neighbourhoods (IMD 1 (most) vs. 5 (least) (aOR 0.75, 95% CI 0.65-0.87). A single dose of BNT162b2 vaccine demonstrated vaccine effectiveness of 72% (95% CI 58-86) 21 days after first dose and 86% (95% CI 76-97) seven days after two doses in the antibody negative cohort.Conclusion: Our study demonstrates that the BNT162b2 vaccine effectively prevents both symptomatic and asymptomatic infection in working age adults; this cohort was vaccinated when the dominant variant in circulation was B1.1.7 and demonstrates effectiveness against this variant.Trial Registration: IRAS ID 284460, REC reference 20/SC/0230 Berkshire Research Ethics Committee, Health Research Authority and Health and Care Research Wales approval granted 22 May 2020. Trial registered with ISRCTN, Trial ID: ISRCTN11041050. https://www.isrctn.com/ISRCTN11041050Funding: The study is funded by the United Kingdom’s Department of Health and Social Care and Public Health England, with contributions from the Scottish, Welsh and Northern Irish governments. Funding is also provided by the National Institute for Health Research (NIHR) as an Urgent Public Health Priority Study (UPHP). SH, VH are supported by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford in partnership with Public Health England (PHE) (NIHR200915). AC is supported by NIHR HealthProtection Research Unit in Behavioural Science and Evaluation at University of Bristol in partnership with Public Health England. MR, NA, AC are supported by NIHR HealthProtection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England.Conflict of Interest: The Immunisation and Countermeasures Division has provided vaccine manufacturers(including Pfizer) with post-marketing surveillance reports on pneumococcal andmeningococcal infection which the companies are required to submit to the UK Licensing authority in compliance with their Risk Management Strategy. A cost recovery charge is made for these reports.Ethical Approval: The study was approved by the Berkshire Research Ethics Committee, Health Research Authority (IRAS ID 284460, REC reference 20/SC/0230) on 22 May 2020; the vaccine amendment was approved on 12/1/2021.