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2024

Assessing the Impact of SARS-CoV-2 on Influenza-Like Illness Surveillance Trends in the Community during the 2023/2024 Winter in England.

Mellor, J., Fyles, M., Paton, R. S., Phillips, A., Overton, C. E., & Ward, T. (2024). Assessing the Impact of SARS-CoV-2 on Influenza-Like Illness Surveillance Trends in the Community during the 2023/2024 Winter in England.. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 107307. doi:10.1016/j.ijid.2024.107307

DOI
10.1016/j.ijid.2024.107307
Journal article

The Incidence and Prevalence of SARS-CoV-2 in the UK Population from the UKHSA Winter COVID Infection Study

DOI
10.1101/2024.10.23.24315984
Preprint

Epidemiological Parameters of SARS-CoV-2 in the UK during the 2023/2024 Winter: A Cohort Study

DOI
10.1101/2024.07.22.24310801
Preprint

An Application of Nowcasting Methods: Cases of Norovirus during the Winter 2023/2024 in England

DOI
10.1101/2024.07.19.24310696
Preprint

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

DOI
10.1186/s12916-024-03444-6
Journal article

Best practices for estimating and reporting epidemiological delay distributions of infectious diseases using public health surveillance and healthcare data

DOI
10.48550/arxiv.2405.08841
Preprint

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

DOI
10.12688/wellcomeopenres.19601.1
Journal article

2023

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.

Conference Paper

Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic

DOI
10.1101/2023.06.12.544667
Preprint

Real-time COVID-19 hospital admissions forecasting with leading indicators and ensemble methods in England

DOI
10.48550/arxiv.2306.05762
Preprint

Quantifying the risk of workplace COVID-19 clusters in terms of commuter, workplace, and population characteristics

DOI
10.48550/arxiv.2305.08745
Preprint

Understanding the leading indicators of hospital admissions from COVID-19 across successive waves in the UK

DOI
10.48550/arxiv.2303.12037
Preprint

Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models

DOI
10.48550/arxiv.2302.11904
Preprint

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

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

DOI
10.1111/rssa.12984
Journal article

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

DOI
10.1186/s12879-022-07239-z
Journal article

Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector

DOI
10.1101/2022.03.17.22272414
Preprint

Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England

DOI
10.48550/arxiv.2202.07325
Preprint

2021

Adjusting for time of infection or positive test when estimating the risk of a post-infection outcome in an epidemic

DOI
10.1101/2021.08.13.21262014
Preprint

2020

Hospital Length of Stay For COVID-19 Patients: Data-Driven Methods for Forward Planning

DOI
10.21203/rs.3.rs-56855/v1
Preprint

Stochastic evolutionary and epidemic processes on networks

Overton, C. (2020, July 28). Stochastic evolutionary and epidemic processes onnetworks.

Thesis / Dissertation

Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example

DOI
10.48550/arxiv.2005.04937
Preprint

Challenges in control of Covid-19: short doubling time and long delay to effect of interventions

DOI
10.48550/arxiv.2004.00117
Preprint

2019