ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2021
A spatial model of COVID-19 transmission in England and Wales: early spread, peak timing and the impact of seasonality.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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51 citing papers in PubMed.
- On real-time calibrated prediction for complex model-based decision support in pandemics: Part 2.PLoS computational biology · 2026Article
- Human mobility and outbreak origins in epidemic spread: Insights from agent-based modeling.PLoS computational biology · 2026Article
- Estimating the effect of self-protection on transmission dynamics of SARS-CoV-2 in Germany in 2021: a modelling study.BMC public health · 2026Article
- Emulating computer models with high-dimensional count output.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Prevalence and correlates of facemask usage during the second wave of COVID-19 pandemic in Uganda.PLOS global public health · 2025Article
- Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model.PLoS computational biology · 2025Article
- Article
- Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey.Infectious Disease Modelling · 2024Article
- Predicting subnational incidence of COVID-19 cases and deaths in EU countries.BMC infectious diseases · 2024Article
- Variegated spatial-temporal landscape of COVID-19 infection in England: findings from spatially filtered multilevel models.Journal of public health (Oxford, England) · 2023Article
- Comparing intervention measures in a model of a disease outbreak on a university campus.Royal Society open science · 2023Article
- The Role of Mobility in the Dynamics of the COVID-19 Epidemic in Andalusia.Bulletin of mathematical biology · 2023Article
- Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.PLoS computational biology · 2023Article
- Designing Digital COVID-19 Screening: Insights and Deliberations.International journal of environmental research and public health · 2023Article
- Integration of Moran's I, geographically weighted regression (GWR), and ordinary least square (OLS) models in spatiotemporal modeling of COVID-19 outbreak in Qom and Mazandaran Provinces, Iran.Modeling earth systems and environment · 2023Article
- Exploration of the COVID-19 pandemic at the neighborhood level in an intra-urban setting.Frontiers in public health · 2023Article
- Hierarchical Bayesian spatio-temporal modeling of COVID-19 in the United States.Journal of applied statistics · 2023Article
- Spatial heterogeneity affects predictions from early-curve fitting of pandemic outbreaks: a case study using population data from Denmark.Royal Society open science · 2022Article
- Learning transmission dynamics modelling of COVID-19 using comomodels.Mathematical biosciences · 2022Article
- Effects of Vaccination and the Spatio-Temporal Diffusion of Covid-19 Incidence in Turkey.Geographical analysis · 2022Article
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4 authors.
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Abstract
An outbreak of a novel coronavirus was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable human-to-human transmission in England. We adapted an existing national-scale metapopulation model to capture the spread of COVID-19 in England and Wales. We used 2011 census data to inform population sizes and movements, together with parameter estimates from the outbreak in China. We predict that the epidemic will peak 126 to 147 days (approx. 4 months) after the start of person-to-person transmission in the absence of controls. Assuming biological parameters remain unchanged and transmission persists from February, we expect the peak to occur in June. Starting location and model stochasticity have a minimal impact on peak timing. However, realistic parameter uncertainty leads to peak time estimates ranging from 78 to 241 days following sustained transmission. Seasonal changes in transmission rate can substantially impact the timing and size of the epidemic. We provide initial estimates of the epidemic potential of COVID-19. These results can be refined with more precise parameters. Seasonal changes in transmission could shift the timing of the peak into winter, with important implications for healthcare capacity planning. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK.
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