Comparative risk of cerebral venous sinus thrombosis (CVST) following COVID-19 vaccination or infection: A national cohort study using linked electronic health records.

To inform the public and policy makers, we investigated and compared the risk of cerebral venous sinus thrombosis (CVST) after SARS-Cov-2 vaccination or infection using a national cohort of 2,643,699 individuals aged 17 y and above, alive, and resident in Wales on 1 January 2020 followed up through multiple linked data sources until 28 March 2021. Exposures were first dose of Oxford-ChAdOx1 or Pfizer-BioNTech vaccine or polymerase chain reaction (PCR)-confirmed SARS-Cov-2 infection. The outcome was an incident record of CVST. Hazard ratios (HR) were calculated using multivariable Cox regression, adjusted for confounders. HR from SARS-Cov-2 infection was compared with that for SARS-Cov-2 vaccination. We identified 910,556 (34.4%) records of first SARS-Cov-2 vaccination and 165,862 (6.3%) of SARS-Cov-2 infection. A total of 1,372 CVST events were recorded during the study period, of which 52 (3.8%) and 48 (3.5%) occurred within 28 d after vaccination and infection, respectively. We observed slight non-significant risk of CVST within 28 d of vaccination [aHR: 1.34, 95% CI: 0.95-1.90], which remained after stratifying by vaccine [BNT162b2, aHR: 1.18 (95% CI: 0.63-2.21); ChAdOx1, aHR: 1.40 (95% CI: 0.95-2.05)]. Three times the number of CVST events is observed within 28 d of a positive SARS-Cov-2 test [aHR: 3.02 (95% CI: 2.17-4.21)]. The risk of CVST following SARS-Cov-2 infection is 2.3 times that following SARS-Cov-2 vaccine. This is important information both for those designing COVID-19 vaccination programs and for individuals making their own informed decisions on the risk-benefit of vaccination. This record-linkage approach will be useful in monitoring the safety of future vaccine programs.

Developing a population data science approach to assess increased risk of COVID-19 associated with attending large events.

Introduction: In summer 2021, as rates of COVID-19 decreased and social restrictions were relaxed, live entertainment and sporting events were resumed. In order to inform policy on the safe re-introduction of spectator events, a number of test events were organised in Wales, ranging in setting, size and audience. Objectives: To design and test a method to assess whether test events were associated with an increase in risk of confirmed COVID-19, in order to inform policy. Methods: We designed a cohort study with fixed follow-up time and measured relative risk of confirmed COVID-19 in those attending two large sporting events. First, we linked ticketing information to individual records on the Welsh Demographic Service (WDS), a register of all people living in Wales and registered with a GP, and identified NHS numbers for attendees. Where NHS numbers were not found we used combinations of other identifiers such as email, name, postcode and/or mobile number. We then linked attendees to routine SARS-CoV-2 test data to calculate positivity rates in people attending each event for the period one to fourteen days following the event. We selected a comparison cohort from WDS for each event, individually matched by age band, gender and locality of residence. As many people attended events in family groups we explored the possibility of also matching on household clusters within the comparison group. Risk ratios were then computed for the two events. Results: We successfully assigned NHS numbers to 91% and 84% of people attending the two events respectively. Other identifiers were available for the remainder. Only a small number of attendees (<10) had a record of confirmed COVID-19 following attendance at each event (14 day cumulative incidence: 36 and 26 per 100,000, respectively). There was no evidence of significantly increased risk of COVID-19 at either event. However, the event that didn't include pre-event testing in their mitigations, had a higher risk ratio (3.0 compared to 0.3). Conclusions: We demonstrate the potential for using population data science methods to inform policy. We conclude that, at that point in the epidemic, and with the mitigations that were in place, attending large outdoor sporting events did not significantly increase risk of COVID-19. However, these analyses were carried out between epidemic waves when background incidence and testing rate was low, and need to be repeated during periods of greater transmission. Having a mechanism to identify attendees at events is necessary to calculate risk and feasibility and acceptability of data sharing should be considered.

Cost-effectiveness of a whole-area testing pilot of asymptomatic SARS-CoV-2 infections with lateral flow devices: a modelling and economic analysis study.

BACKGROUND: Mass community testing for SARS-CoV-2 by lateral flow devices (LFDs) aims to reduce prevalence in the community. However its effectiveness as a public heath intervention is disputed. METHOD: Data from a mass testing pilot in the Borough of Merthyr Tydfil in late 2020 was used to model cases, hospitalisations, ICU admissions and deaths prevented. Further economic analysis with a healthcare perspective assessed cost-effectiveness in terms of healthcare costs avoided and QALYs gained. RESULTS: An initial conservative estimate of 360 (95% CI: 311-418) cases were prevented by the mass testing, representing a would-be reduction of 11% of all cases diagnosed in Merthyr Tydfil residents during the same period. Modelling healthcare burden estimates that 24 (16-36) hospitalizations, 5 (3-6) ICU admissions and 15 (11-20) deaths were prevented, representing 6.37%, 11.1% and 8.2%, respectively of the actual counts during the same period. A less conservative, best-case scenario predicts 2333 (1764-3115) cases prevented, representing 80% reduction in would-be cases. Cost -effectiveness analysis indicates 108 (80-143) QALYs gained, an incremental cost-effectiveness ratio of £2,143 (£860-£4,175) per QALY gained and net monetary benefit of £6.2 m (£4.5 m-£8.4 m). In the best-case scenario, this increases to £15.9 m (£12.3 m-£20.5 m). CONCLUSIONS: A non-negligible number of cases, hospitalisations and deaths were prevented by the mass testing pilot. Considering QALYs gained and healthcare costs avoided, the pilot was cost-effective. These findings suggest mass testing with LFDs in areas of high prevalence (> 2%) is likely to provide significant public health benefit. It is not yet clear whether similar benefits will be obtained in low prevalence settings or with vaccination rollout.

Developing a population data science approach to assess increased risk of COVID-19 associated with attending large events

Introduction In summer 2021, as rates of COVID-19 decreased and social restrictions were relaxed, live entertainment and sporting events were resumed. In order to inform policy on the safe re-introduction of spectator events, a number of test events were organised in Wales, ranging in setting, size and audience. Objectives To design and test a method to assess whether test events were associated with an increase in risk of confirmed COVID-19, in order to inform policy. Methods We designed a cohort study with fixed follow-up time and measured relative risk of confirmed COVID-19 in those attending two large sporting events. First, we linked ticketing information to individual records on the Welsh Demographic Service (WDS), a register of all people living in Wales and registered with a GP, and identified NHS numbers for attendees. Where NHS numbers were not found we used combinations of other identifiers such as email, name, postcode and/or mobile number. We then linked attendees to routine SARS-CoV-2 test data to calculate positivity rates in people attending each event for the period one to fourteen days following the event. We selected a comparison cohort from WDS for each event, individually matched by age band, gender and locality of residence. As many people attended events in family groups we explored the possibility of also matching on household clusters within the comparison group. Risk ratios were then computed for the two events. Results We successfully assigned NHS numbers to 91% and 84% of people attending the two events respectively. Other identifiers were available for the remainder. Only a small number of attendees (<10) had a record of confirmed COVID-19 following attendance at each event (14 day cumulative incidence: 36 and 26 per 100,000, respectively). There was no evidence of significantly increased risk of COVID-19 at either event. However, the event that didn’t include pre-event testing in their mitigations, had a higher risk ratio (3.0 compared to 0.3). Conclusions We demonstrate the potential for using population data science methods to inform policy. We conclude that, at that point in the epidemic, and with the mitigations that were in place, attending large outdoor sporting events did not significantly increase risk of COVID-19. However, these analyses were carried out between epidemic waves when background incidence and testing rate was low, and need to be repeated during periods of greater transmission. Having a mechanism to identify attendees at events is necessary to calculate risk and feasibility and acceptability of data sharing should be considered.

Social capital and geographical variation in the incidence of COVID-19: an ecological study.

BACKGROUND: The new behavioural norms needed to reduce the spread of COVID-19 are likely scaffolded by social capital. Research on social capital and COVID-19 has yielded mixed results, with some studies finding it to be protective while others identifying it as a risk factor. We examined the association between social capital and COVID-19 at a finer spatial scale than previous research, and examined changes in the relationship over the course of the pandemic. METHODS: Routine COVID-19 surveillance data from Wales were linked to estimates of social capital at a small area level. Generalised linear mixed effects models predicting COVID-19 case rates across areas using social capital estimates and possible confounding variables were fitted to the data. A moving window version of the analysis explored whether this relationship varied across time. RESULTS: Areas with higher levels of social capital had lower rates of COVID-19 (rate ratio for trust=0.94, 95% CI 0.92 to 0.96; rate ratio for belonging=0.94, 95% CI 0.92 to 0.96). These associations were strongest during periods of lockdown, with evidence that social capital was less protective, and potentially even a risk factor, during periods when restrictions were eased. Trust, but not belonging, remained protective after adjusting for deprivation, population density, ethnicity and proportion population aged over 65 years. CONCLUSIONS: Social capital is an important public health resource, which should be considered in future pandemic preparedness. Its importance may be greatest during times when social activity is most restricted.