Predicting subnational incidence of COVID-19 cases and deaths in EU countries (preprint)

Background: Recurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, vaccination, waning and immune escape, alongside other factors (population density, social contact patterns). Immunity patterns are spatially and demographically heterogeneous, and are challenging to capture in country-level forecast models. Methods: We used a spatiotemporal regression model to forecast subnational case and death counts and applied it to three EU countries as test cases: France, Czechia, and Italy. Cases in local regions arise from importations or local transmission. Our model produces age-stratified forecasts given age-stratified data, and links reported case counts to routinely collected covariates (test number, vaccine coverage..). We assessed the predictive performance of our model up to four weeks ahead using proper scoring rules and compared it to the European COVID-19 Forecast Hub ensemble model. Using simulations, we evaluated the impact of variations in transmission on the forecasts. We developed an open-source RShiny App to visualise the forecasts and scenarios. Results: At a national level, the median relative difference between our median weekly case forecasts and the data up to four weeks ahead was 25% (IQR: 12-50%) over the prediction period. The accuracy decreased as the forecast horizon increased (on average 24% increase in the median ranked probability score per added week), while the accuracy of death forecasts remained stable. Beyond two weeks, the model generated a narrow range of likely transmission dynamics. The median national case forecasts showed similar accuracy to forecasts from the European COVID-19 Forecast Hub ensemble model, but the prediction interval was narrower in our model. Generating forecasts under alternative transmission scenarios was therefore key to capturing the range of possible short-term transmission dynamics. Discussion: Our model captures changes in local COVID-19 outbreak dynamics, and enables quantification of short-term transmission risk at a subnational level. The outputs of the model improve our ability to identify areas where outbreaks are most likely, and are available to a wide range of public health professionals through the Shiny App we developed.

Dosing interval strategies for two-dose COVID-19 vaccination in 13 low- and middle-income countries of Europe: health impact modelling and benefit-risk analysis (preprint)

Background: In settings where the COVID-19 vaccine supply is constrained, extending the intervals between the first and second doses of the COVID-19 vaccine could let more people receive their first doses earlier. Our aim is to estimate the health impact of COVID-19 vaccination alongside benefit-risk assessment of different dosing intervals for low- and middle-income countries of Europe. Methods: We fitted a dynamic transmission model to country-level daily reported COVID-19 mortality in 13 low- and middle-income countries in the World Health Organization European Region (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Republic of Moldova, Russian Federation, Serbia, North Macedonia, Turkey, and Ukraine). A vaccine product with characteristics similar to the Oxford/AstraZeneca COVID-19 (AZD1222) vaccine was used in the base case scenario and was complemented by sensitivity analyses around efficacies related to other COVID-19 vaccines. Both fixed dosing intervals at 4, 8, 12, 16, and 20 weeks and dose-specific intervals that prioritise specific doses for certain age groups were tested. Optimal intervals minimise COVID-19 mortality between March 2021 and December 2022. We incorporated the emergence of variants of concern into the model, and also conducted a benefit-risk assessment to quantify the trade-off between health benefits versus adverse events following immunisation. Findings: In 12 of the 13 countries, optimal strategies are those that prioritise the first doses among older adults (60+ years) or adults (20-59 years). These strategies lead to dosing intervals longer than six months. In comparison, a four-week fixed dosing interval may incur 10.2% [range: 4.0% - 22.5%; n = 13 (countries)] more deaths. There is generally a negative association between dosing interval and COVID-19 mortality within the range we investigated. Assuming a shorter first dose waning duration of 120 days, as opposed to 360 days in the base case, led to shorter optimal dosing intervals of 8-12 weeks. Benefit-risk ratios were the highest for fixed dosing intervals of 8-12 weeks. Interpretation: We infer that longer dosing intervals of over six months, which are substantially longer than the current label recommendation for most vaccine products, could reduce COVID-19 mortality in low- and middle-income countries of WHO/Europe. Certain vaccine features, such as fast waning of first doses, significantly shorten the optimal dosing intervals.

Optimising health and economic impacts of COVID-19 vaccine prioritisation strategies in the WHO European Region (preprint)

BackgroundCountries in the World Health Organization (WHO) European Region differ in terms of the COVID-19 vaccine roll-out speed. We evaluated the health and economic impact of different age-based vaccine prioritisation strategies across this demographically and socio-economically diverse region. MethodsWe fitted country-specific age-stratified compartmental transmission models to reported COVID-19 mortality in the WHO European Region to inform the immunity level before vaccine roll-out. Building upon broad recommendations from the WHO Strategic Advisory Group of Experts on Immunisation (SAGE), we examined four strategies that prioritise: all adults (V+), younger (20-59 year-olds) followed by older adults (60+) (V20), older followed by younger adults (V60), and the oldest adults (75+) (V75) followed by incremental expansion to successively younger five-year age groups. We explored four roll-out scenarios based on projections or recent observations (R1-4) - the slowest scenario (R1) covers 30% of the total population by December 2022 and the fastest (R4) 80% by December 2021. Five decision-making metrics were summarised over 2021-22: mortality, morbidity, and losses in comorbidity-adjusted life expectancy (cLE), comorbidity- and quality-adjusted life years (cQALY), and the value of human capital (HC). Six sets of infection-blocking and disease-reducing vaccine efficacies were considered. FindingsThe optimal age-based vaccine prioritisation strategies were sensitive to country characteristics, decision-making metrics and roll-out speeds. Overall, V60 consistently performed better than or comparably to V75. There were greater benefits in prioritising older adults when roll-out is slow and when VE is low. Under faster roll-out, V+ was the most desirable option. InterpretationA prioritisation strategy involving more age-based stages (V75) does not necessarily lead to better health and economic outcomes than targeting broad age groups (V60). Countries expecting a slow vaccine roll-out may particularly benefit from prioritising older adults. FundingWorld Health Organization, Bill and Melinda Gates Foundation, the Medical Research Council (United Kingdom), the National Institute of Health Research (United Kingdom), the European Commission, the Foreign, Commonwealth and Development Office (United Kingdom), Wellcome Trust Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and medRxiv for articles published in English from inception to 9 Jun 2021, with the search terms: ("COVID-19" OR "SARS-CoV-2") AND ("priorit*) AND ("model*") AND ("vaccin*") and identified 66 studies on vaccine prioritization strategies. Of the 25 studies that compared two or more age-based prioritisation strategies, 12 found that targeting younger adults minimised infections while targeting older adults minimised mortality; an additional handful of studies found similar outcomes between different age-based prioritisation strategies where large outbreaks had already occurred. However, only two studies have explored age-based vaccine prioritisation using models calibrated to observed outbreaks in more than one country, and no study has explored the effectiveness of vaccine prioritisation strategies across settings with different population structures, contact patterns, and outbreak history. Added-value of this studyWe evaluated various age-based vaccine prioritisation strategies for 38 countries in the WHO European Region using various health and economic outcomes for decision-making, by parameterising models using observed outbreak history, known epidemiologic and vaccine characteristics, and a range of realistic vaccine roll-out scenarios. We showed that while targeting older adults was generally advantageous, broadly targeting everyone above 60 years might perform better than or comparably to a more detailed strategy that targeted the oldest age group above 75 years followed by those in the next younger five-year age band. Rapid vaccine roll-out has only been observed in a small number of countries. If vaccine coverage can reach 80% by the end of 2021, prioritising older adults may not be optimal in terms of health and economic impact. Lower vaccine efficacy was associated with greater relative benefits only under relatively slow roll-out scenarios considered. Implication of all the available evidenceCOVID-19 vaccine prioritization strategies that require more precise targeting of individuals of a specific and narrow age range may not necessarily lead to better outcomes compared to strategies that prioritise populations across broader age ranges. In the WHO European Region, prioritising all adults equally or younger adults first will only optimise health and economic impact when roll-out is rapid, which may raise between-country equity issues given the global demand for COVID-19 vaccines.

Time use and social mixing during and around festive periods: Potential changes in the age distribution of COVID-19 cases from increased intergenerational interactions (preprint)

RationaleAmid the ongoing coronavirus disease 2019 (COVID-19) pandemic in which many countries have adopted physical distancing measures, tiered restrictions, and episodic "lockdowns," the impact of potentially increased social mixing during festive holidays on the age distribution of new COVID-19 cases remains unclear. ObjectiveWe aimed to gain insights into possible changes in the age distribution of COVID-19 cases in the UK after temporarily increased intergenerational interactions in late December 2020. MethodWe modelled changes in time use and social mixing based on age-stratified contact rates using historical nationally-representative surveys and up-to-date Google mobility data from four weeks before and after the festive period. We explored changes in the effective reproduction number and the age distribution of cases, in four scenarios: (1) "normal": time use and contact patterns as observed historically, (2) "pre-lockdown": patterns as seen before the lockdown in November 2020, (3) "lockdown": patterns restricted as in November 2020, and (4) "festive break": similar to 3 but with social visits over the holiday period as in 1. ResultsAcross ages, the estimated Reff decreases during the festive break in scenarios 1-3 and returns to pre-holiday levels in scenarios 2-3, while remaining relatively stable in scenario 4. Relative incidence is likely to decrease in children aged 0-15 but increase in other ages. Changes in age distribution were large during the holidays, and are likely to start before the holidays for individuals aged 16-24 years in scenarios 1-3. ConclusionsOur modelling findings suggest that increased contacts during the festive period may shift the age distribution of COVID-19 cases from children towards adults. Given that COVID-19-related hospitalisations and deaths rise by age, more intergenerational mixing risks an increased burden in the period following the holidays. HighlightsO_LIHome visits are associated with increased intergenerational mixing. C_LIO_LIThe effective reproduction number is likely to remain stable or even reduce slightly due to a reduction in contacts at work and school. C_LIO_LIRelative incidence is likely to become lower in children, but higher in the C_LIO_LIolder (more vulnerable) age groups around the holiday period, which could lead to increased health care burden. C_LI