ArticleBiometrics2022
Inferring UK COVID-19 fatal infection trajectories from daily mortality data: Were infections already in decline before the UK lockdowns?
Article in Biometrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- The need for methodological pluralism in epidemiological modelling.Global epidemiology · 2025Article
- What Lessons can Be Learned From the Management of the COVID-19 Pandemic?International journal of public health · 2025Review
- Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe.Journal of clinical medicine · 2024Article
- Spatio-temporal heterogeneity in the international trade resilience during COVID-19.Applied geography (Sevenoaks, England) · 2023Article
- Unintended Consequences of COVID-19 Non-Pharmaceutical Interventions (NPIs) for Population Health and Health Inequalities.International journal of environmental research and public health · 2023Review
- The changing contributory role to infections of work, public transport, shopping, hospitality and leisure activities throughout the SARS-CoV-2 pandemic in England and Wales.NIHR open research · 2023Article
- Inferring UK COVID-19 fatal infection trajectories from daily mortality data: Were infections already in decline before the UK lockdowns?Biometrics · 2022Article
- Estimating the course of the COVID-19 pandemic in Germany via spline-based hierarchical modelling of death counts.Scientific reports · 2022Article
- Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold.Journal of theoretical biology · 2022Article
- Drug markets and COVID-19: A spatiotemporal study of drug offence detection rates in Brisbane, Australia.The International journal on drug policy · 2022Article
- Mental Health and Wellbeing in Young People in the UK during Lockdown (COVID-19).International journal of environmental research and public health · 2022Article
- The Effects of Non-pharmaceutical Interventions on COVID-19 Mortality: A Generalized Synthetic Control Approach Across 169 Countries.Frontiers in public health · 2022Article
- Was R < 1 before the English lockdowns? On modelling mechanistic detail, causality and inference about Covid-19.PloS one · 2021Article
- The impact of casirivimab-imdevimab antibody cocktail in patients amidst and post COVID 19 treatment: A retro-prospective comparative study in India.Clinical epidemiology and global healthArticle
Corrections and comments
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1 author.
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Abstract
The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the number of new cases is likely to be increasing or decreasing: for example, estimating the pathogen-effective reproduction number, R, using data gathered from the clinical response to the disease. For coronavirus disease 2019 (Covid-19/SARS-Cov-2), such R estimation is heavily dependent on modelling assumptions, because the available clinical case data are opportunistic observational data subject to severe temporal confounding. Given this difficulty, it is useful to retrospectively reconstruct the time course of infections from the least compromised available data, using minimal prior assumptions. A Bayesian inverse problem approach applied to UK data on first-wave Covid-19 deaths and the disease duration distribution suggests that fatal infections were in decline before full UK lockdown (24 March 2020), and that fatal infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. gives the same result under relaxation of its prior assumptions on R, suggesting an enhanced role for non-pharmaceutical interventions short of full lockdown in the UK context. Similar patterns appear to have occurred in the subsequent two lockdowns.
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