Publications
2024
The Incidence and Prevalence of SARS-CoV-2 in the UK Population from the UKHSA Winter COVID Infection Study
Modelling multiplex testing for outbreak control.
Fyles, M., Overton, C. E., Ward, T., Bennett, E., Fowler, T., & Hall, I. (2024). Modelling multiplex testing for outbreak control.. The Journal of infection, 89(6), 106303. doi:10.1016/j.jinf.2024.106303
Deterministic epidemic models overestimate the basic reproduction number of observed outbreaks.
Ali, W., Overton, C. E., Wilkinson, R. R., & Sharkey, K. J. (2024). Deterministic epidemic models overestimate the basic reproduction number of observed outbreaks.. Infectious Disease Modelling, 9(3), 680-688. doi:10.1016/j.idm.2024.02.007
Modelling multiplex testing for outbreak Control
Epidemiological Parameters of SARS-CoV-2 in the UK during the 2023/2024 Winter: A Cohort Study
An Application of Nowcasting Methods: Cases of Norovirus during the Winter 2023/2024 in England
How effective is the BNT162b2 mRNA vaccine against SARS-CoV-2 transmission and infection? A national programme analysis in Monaco, July 2021 to September 2022.
Althaus, T., Overton, C. E., Devaux, I., House, T., Lapouze, A., Troel, A., . . . Voiglio, E. J. (2024). How effective is the BNT162b2 mRNA vaccine against SARS-CoV-2 transmission and infection? A national programme analysis in Monaco, July 2021 to September 2022.. BMC medicine, 22(1), 227. doi:10.1186/s12916-024-03444-6
The real-time infection hospitalisation and fatality risk across the COVID-19 pandemic in England.
Ward, T., Fyles, M., Glaser, A., Paton, R. S., Ferguson, W., & Overton, C. E. (2024). The real-time infection hospitalisation and fatality risk across the COVID-19 pandemic in England.. Nature communications, 15(1), 4633. doi:10.1038/s41467-024-47199-3
Best practices for estimating and reporting epidemiological delay distributions of infectious diseases using public health surveillance and healthcare data
Understanding the infection severity and epidemiological characteristics of mpox in the UK.
Ward, T., Overton, C. E., Paton, R. S., Christie, R., Cumming, F., & Fyles, M. (2024). Understanding the infection severity and epidemiological characteristics of mpox in the UK.. Nature communications, 15(1), 2199. doi:10.1038/s41467-024-45110-8
Author Correction: Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models.
Mellor, J., Christie, R., Overton, C. E., Paton, R. S., Leslie, R., Tang, M., . . . Ward, T. (2024). Author Correction: Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models.. Communications medicine, 4(1), 14. doi:10.1038/s43856-024-00435-9
Estimating epidemiological delay distributions for infectious diseases
Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study
Overton, C., Abbey, R., Baird, T., Christie, R., Daniel, O., Day, J., . . . Chen, Y. (2024). Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study. Occupational and Environmental Medicine. doi:10.1136/oemed-2023-109032
Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic.
Sherratt, K., Carnegie, A. C., Kucharski, A., Cori, A., Pearson, C. A. B., Jarvis, C. I., . . . Abbott, S. (2024). Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic.. Wellcome open research, 9, 12. doi:10.12688/wellcomeopenres.19601.1
2023
Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models.
Mellor, J., Christie, R., Overton, C. E., Paton, R. S., Leslie, R., Tang, M., . . . Ward, T. (2023). Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models.. Communications medicine, 3(1), 190. doi:10.1038/s43856-023-00424-4
Hierarchical Forecasting Models for Covid-19 Hospital Bed Occupancy and Admissions for Individual National Health Service Trusts in the UK.
Nixon, E. (2023, November 28). Hierarchical Forecasting Models for Covid-19 Hospital Bed Occupancy and Admissions for Individual National Health Service Trusts in the UK.. In https://ssrn.com/abstract=4654894. Bologna.
Bayesian spatial modelling of localised SARS-CoV-2 transmission through mobility networks across England.
Ward, T., Morris, M., Gelman, A., Carpenter, B., Ferguson, W., Overton, C., & Fyles, M. (2023). Bayesian spatial modelling of localised SARS-CoV-2 transmission through mobility networks across England.. PLoS computational biology, 19(11), e1011580. doi:10.1371/journal.pcbi.1011580
Nowcasting the 2022 mpox outbreak in England.
Overton, C. E., Abbott, S., Christie, R., Cumming, F., Day, J., Jones, O., . . . Ward, T. (2023). Nowcasting the 2022 mpox outbreak in England.. PLoS computational biology, 19(9), e1011463. doi:10.1371/journal.pcbi.1011463
Understanding the leading indicators of hospital admissions from COVID-19 across successive waves in the UK.
Mellor, J., Overton, C. E., Fyles, M., Chawner, L., Baxter, J., Baird, T., & Ward, T. (2023). Understanding the leading indicators of hospital admissions from COVID-19 across successive waves in the UK.. Epidemiology and infection, 151, e172. doi:10.1017/s0950268823001449
Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic
Real-time COVID-19 hospital admissions forecasting with leading indicators and ensemble methods in England
Quantifying the risk of workplace COVID-19 clusters in terms of commuter, workplace, and population characteristics
Understanding the leading indicators of hospital admissions from COVID-19 across successive waves in the UK
Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models
Nowcasting the 2022 mpox outbreak in England
2022
Replacement dynamics and the pathogenesis of the Alpha, Delta and Omicron variants of SARS-CoV-2.
Ward, T., Glaser, A., Overton, C. E., Carpenter, B., Gent, N., & Seale, A. C. (2022). Replacement dynamics and the pathogenesis of the Alpha, Delta and Omicron variants of SARS-CoV-2.. Epidemiology and infection, 151, e32. doi:10.1017/s0950268822001935
Estimation of reproduction numbers in real time: Conceptual and statistical challenges
Pellis, L., Birrell, P. J., Blake, J., Overton, C. E., Scarabel, F., Stage, H. B., . . . De Angelis, D. (2022). Estimation of reproduction numbers in real time: Conceptual and statistical challenges. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, 185, S112-S130. doi:10.1111/rssa.12955
Authors' reply to the discussion of 'Estimation of reproduction numbers in real time: conceptual and statistical challenges' by Pellis et al. in Session 3 of the Royal Statistical Society's Special Topic Meeting on COVID-19 transmission: 11 June 2021
Pellis, L., Birrell, P. J. J., Blake, J., Hall, I., House, T. A. A., Overton, C. E. E., . . . De Angelis, D. (2022). Authors' reply to the discussion of 'Estimation of reproduction numbers in real time: conceptual and statistical challenges' by Pellis et al. in Session 3 of the Royal Statistical Society's Special Topic Meeting on COVID-19 transmission: 11 June 2021. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, 185, S153-S157. doi:10.1111/rssa.12984
Transmission dynamics of monkeypox in the United Kingdom: contact tracing study.
Ward, T., Christie, R., Paton, R. S., Cumming, F., & Overton, C. E. (2022). Transmission dynamics of monkeypox in the United Kingdom: contact tracing study.. BMJ (Clinical research ed.), 379, e073153. doi:10.1136/bmj-2022-073153
Adjusting for time of infection or positive test when estimating the risk of a post-infection outcome in an epidemic.
Seaman, S. R., Nyberg, T., Overton, C. E., Pascall, D. J., Presanis, A. M., & De Angelis, D. (2022). Adjusting for time of infection or positive test when estimating the risk of a post-infection outcome in an epidemic.. Statistical methods in medical research, 31(10), 1942-1958. doi:10.1177/09622802221107105
Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England
Overton, C. E., Webb, L., Datta, U., Fursman, M., Hardstaff, J., Hiironen, I., . . . Hall, I. (2022). Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England. PLOS COMPUTATIONAL BIOLOGY, 18(10). doi:10.1371/journal.pcbi.1010554
EpiBeds: Data informed modelling of the COVID-19 hospital burden in England
Overton, C. E., Pellis, L., Stage, H. B., Scarabel, F., Burton, J., Fraser, C., . . . Lythgoe, K. A. (2022). EpiBeds: Data informed modelling of the COVID-19 hospital burden in England. PLOS COMPUTATIONAL BIOLOGY, 18(9). doi:10.1371/journal.pcbi.1010406
Approximating quasi-stationary behaviour in network-based SIS dynamics
The rapid replacement of the SARS-CoV-2 Delta variant by Omicron (B.1.1.529) in England
Paton, R. S., Overton, C. E., & Ward, T. (2022). The rapid replacement of the SARS-CoV-2 Delta variant by Omicron (B.1.1.529) in England. SCIENCE TRANSLATIONAL MEDICINE, 14(652). doi:10.1126/scitranslmed.abo5395
Effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines for reducing susceptibility to infection with the Delta variant (B.1.617.2) of SARS-CoV-2
Pattni, K., Hungerford, D., Adams, S., Buchan, I., Cheyne, C. P., García-Fiñana, M., . . . Sharkey, K. J. (n.d.). Effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines for reducing susceptibility to infection with the Delta variant (B.1.617.2) of SARS-CoV-2. BMC Infectious Diseases, 22(1). doi:10.1186/s12879-022-07239-z
Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector
Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England
Challenges for modelling interventions for future pandemics
Kretzschmar, M. E., Ashby, B., Fearon, E., Overton, C. E., Panovska-Griffiths, J., Pellis, L., . . . Villela, D. (2022). Challenges for modelling interventions for future pandemics. Epidemics, 38, 100546. doi:10.1016/j.epidem.2022.100546
Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling
Swallow, B., Birrell, P., Blake, J., Burgman, M., Challenor, P., Coffeng, L. E., . . . Vernon, I. (2022). Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 38, 100547. doi:10.1016/j.epidem.2022.100547
2021
Early signals of Omicron severity in sentinel UK hospitals
Approximating Quasi-Stationary Behaviour in Network-Based SIS Dynamics
Overton, C. E., Wilkinson, R. R., Loyinmi, A., Miller, J. C., & Sharkey, K. J. (2022). Approximating Quasi-Stationary Behaviour in Network-Based SIS Dynamics. BULLETIN OF MATHEMATICAL BIOLOGY, 84(1). doi:10.1007/s11538-021-00964-7
EpiBeds: Data informed modelling of the COVID-19 hospital burden in England
Adjusting for time of infection or positive test when estimating the risk of a post-infection outcome in an epidemic
Hospital length of stay for COVID-19 patients: Data-driven methods for forward planning
Vekaria, B., Overton, C., Wisniowski, A., Ahmad, S., Aparicio-Castro, A., Curran-Sebastian, J., . . . Elliot, M. J. (2021). Hospital length of stay for COVID-19 patients: Data-driven methods for forward planning. BMC INFECTIOUS DISEASES, 21(1). doi:10.1186/s12879-021-06371-6
Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic
Fyles, M., Fearon, E., Overton, C., Wingfield, T., Medley, G. F., Hall, I., . . . House, T. (2021). Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 376(1829). doi:10.1098/rstb.2020.0267
Evolutionary graph theory derived from eco-evolutionary dynamics
Pattni, K., Overton, C. E., & Sharkey, K. J. (2021). Evolutionary graph theory derived from eco-evolutionary dynamics. JOURNAL OF THEORETICAL BIOLOGY, 519. doi:10.1016/j.jtbi.2021.110648
Challenges in control of COVID-19: short doubling time and long delay to effect of interventions
Pellis, L., Scarabel, F., Stage, H. B., Overton, C. E., Chappell, L. H. K., Fearon, E., . . . Hall, I. (2021). Challenges in control of COVID-19: short doubling time and long delay to effect of interventions. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 376(1829). doi:10.1098/rstb.2020.0264
Evolutionary bet-hedging in structured populations
Overton, C. E., & Sharkey, K. J. (2021). Evolutionary bet-hedging in structured populations. JOURNAL OF MATHEMATICAL BIOLOGY, 82(5). doi:10.1007/s00285-021-01597-z
Using a household structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic
Fyles, M., Fearon, E., Overton, C., University of Manchester COVID-19 Working Group., Wingfield, T., Medley, G., . . . House, T. (2021). Using a household structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic. doi:10.1101/2021.02.03.21250992
2020
Short-term forecasts to inform the response to the Covid-19 epidemic in the UK
Funk, S., Abbott, S., Atkins, B. D., Baguelin, M., Baillie, J. K., Birrell, P., . . . ISARIC4C Investigators. (2020). Short-term forecasts to inform the response to the Covid-19 epidemic in the UK. doi:10.1101/2020.11.11.20220962
Evolutionary graph theory derived from eco-evolutionary dynamics
Hospital Length of Stay For COVID-19 Patients: Data-Driven Methods for Forward Planning
Stochastic evolutionary and epidemic processes on networks
Overton, C. (2020, July 28). Stochastic evolutionary and epidemic processes onnetworks.
Stochastic evolutionary and epidemic processes on networks
Overton, C. (2020, July 28). Stochastic evolutionary and epidemic processes onnetworks.
Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example
Overton, C. E., Stage, H. B., Ahmad, S., Curran-Sebastian, J., Dark, P., Das, R., . . . Webb, L. (2020). Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example. INFECTIOUS DISEASE MODELLING, 5, 409-441. doi:10.1016/j.idm.2020.06.008
Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example
Challenges in control of Covid-19: short doubling time and long delay to effect of interventions
2019
Methods for approximating stochastic evolutionary dynamics on graphs
Overton, C. E., Broom, M., Hadjichrysanthou, C., & Sharkey, K. J. (2019). Methods for approximating stochastic evolutionary dynamics on graphs. JOURNAL OF THEORETICAL BIOLOGY, 468, 45-59. doi:10.1016/j.jtbi.2019.02.009