The importance of saturating density dependence for population-level predictions of SARS-CoV-2 resurgence compared with density-independent or linearly density-dependent models, England, 23 March to 31 July 2020.

BackgroundPopulation-level mathematical models of outbreaks typically assume that disease transmission is not impacted by population density ('frequency-dependent') or that it increases linearly with density ('density-dependent').AimWe sought evidence for the role of population density in SARS-CoV-2 transmission.MethodsUsing COVID-19-associated mortality data from England, we fitted multiple functional forms linking density with transmission. We projected forwards beyond lockdown to ascertain the consequences of different functional forms on infection resurgence.ResultsCOVID-19-associated mortality data from England show evidence of increasing with population density until a saturating level, after adjusting for local age distribution, deprivation, proportion of ethnic minority population and proportion of key workers among the working population. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these classical model structures over- and underestimate the delay in infection resurgence following the release of lockdown.ConclusionIdentifying saturation points for given populations and including transmission terms that account for this feature will improve model accuracy and utility for the current and future pandemics

Analysis of temporal trends in potential COVID-19 cases reported through NHS Pathways England.

The National Health Service (NHS) Pathways triage system collates data on enquiries to 111 and 999 services in England. Since the 18th of March 2020, these data have been made publically available for potential COVID-19 symptoms self-reported by members of the public. Trends in such reports over time are likely to reflect behaviour of the ongoing epidemic within the wider community, potentially capturing valuable information across a broader severity profile of cases than hospital admission data. We present a fully reproducible analysis of temporal trends in NHS Pathways reports until 14th May 2020, nationally and regionally, and demonstrate that rates of growth/decline and effective reproduction number estimated from these data may be useful in monitoring transmission. This is a particularly pressing issue as lockdown restrictions begin to be lifted and evidence of disease resurgence must be constantly reassessed. We further assess the correlation between NHS Pathways reports and a publicly available NHS dataset of COVID-19-associated deaths in England, finding that enquiries to 111/999 were strongly associated with daily deaths reported 16 days later. Our results highlight the potential of NHS Pathways as the basis of an early warning system. However, this dataset relies on self-reported symptoms, which are at risk of being severely biased. Further detailed work is therefore necessary to investigate potential behavioural issues which might otherwise explain our conclusions

COVID-19 vaccination in Sindh province, Pakistan: A modelling study of health impact and cost-effectiveness

Background: Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million).Methods and findings: We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70$27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question.Conclusions: COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries

Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data.

BACKGROUND: Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. METHODS: We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. RESULTS: Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. CONCLUSION: Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening

COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness.

BACKGROUND: Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million). METHODS AND FINDINGS: We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70$27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question. CONCLUSIONS: COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries

Global and national estimates of the number of healthcare workers at high risk of SARS-CoV-2 infection

In order to promote equitable and efficient allocation of coronavirus disease 2019 (COVID-19) vaccines, the World Health Organization (WHO) Strategic Advisory Group of Experts on Immunization (WHO-SAGE-I) has published a 'Roadmap for Prioritizing Uses of COVID-19 Vaccines in the Context of Limited Supply', outlining which groups should be prioritized under various supply scenarios [1]. Healthcare workers (HCWs) at high or very high risk of acquiring and transmitting severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are included in Stage I when supply is very limited

Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence.

Emerging evidence suggests that contact tracing has had limited success in the UK in reducing the R number across the COVID-19 pandemic. We investigate potential pitfalls and areas for improvement by extending an existing branching process contact tracing model, adding diagnostic testing and refining parameter estimates. Our results demonstrate that reporting and adherence are the most important predictors of programme impact but tracing coverage and speed plus diagnostic sensitivity also play an important role. We conclude that well-implemented contact tracing could bring small but potentially important benefits to controlling and preventing outbreaks, providing up to a 15% reduction in R. We reaffirm that contact tracing is not currently appropriate as the sole control measure

Serial intervals in SARS-CoV-2 B.1.617.2 variant cases.

The SARS-CoV-2 lineage B.1.617.2, also known as the delta variant, was declared a variant of concern by WHO on the basis of preliminary evidence suggesting faster spread relative to other circulating variants. However, the epidemiological factors contributing to this difference remain unclear. In particular, an increase in observed growth rate of COVID-19 cases could be the result of a shorter generation interval (i.e., the delay from one infection to the next) or an increase in the effective reproduction number, R, of an infected individual (i.e., the average number of secondary cases generated by an infectious individual), or both. Whereas a shorter generation interval would increase the speed but not the number of individual-level transmissions, a larger value of R would require both faster and wider coverage of outbreak control measures such as vaccination or physical distancing to suppress transmission

What settings have been linked to SARS-CoV-2 transmission clusters?

Background: Concern about the health impact of novel coronavirus SARS-CoV-2 has resulted in widespread enforced reductions in people's movement ("lockdowns"). However, there are increasing concerns about the severe economic and wider societal consequences of these measures. Some countries have begun to lift some of the rules on physical distancing in a stepwise manner, with differences in what these "exit strategies" entail and their timeframes. The aim of this work was to inform such exit strategies by exploring the types of indoor and outdoor settings where transmission of SARS-CoV-2 has been reported to occur and result in clusters of cases. Identifying potential settings that result in transmission clusters allows these to be kept under close surveillance and/or to remain closed as part of strategies that aim to avoid a resurgence in transmission following the lifting of lockdown measures. Methods: We performed a systematic review of available literature and media reports to find settings reported in peer reviewed articles and media with these characteristics. These sources are curated and made available in an editable online database. Results: We found many examples of SARS-CoV-2 clusters linked to a wide range of mostly indoor settings. Few reports came from schools, many from households, and an increasing number were reported in hospitals and elderly care settings across Europe. Conclusions: We identified possible places that are linked to clusters of COVID-19 cases and could be closely monitored and/or remain closed in the first instance following the progressive removal of lockdown restrictions. However, in part due to the limits in surveillance capacities in many settings, the gathering of information such as cluster sizes and attack rates is limited in several ways: inherent recall bias, biased media reporting and missing data