Paul Birrell

2.7k total citations
30 papers, 686 citations indexed

About

Paul Birrell is a scholar working on Epidemiology, Modeling and Simulation and Infectious Diseases. According to data from OpenAlex, Paul Birrell has authored 30 papers receiving a total of 686 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Epidemiology, 19 papers in Modeling and Simulation and 9 papers in Infectious Diseases. Recurrent topics in Paul Birrell's work include COVID-19 epidemiological studies (19 papers), Influenza Virus Research Studies (14 papers) and Data-Driven Disease Surveillance (10 papers). Paul Birrell is often cited by papers focused on COVID-19 epidemiological studies (19 papers), Influenza Virus Research Studies (14 papers) and Data-Driven Disease Surveillance (10 papers). Paul Birrell collaborates with scholars based in United Kingdom, United States and Netherlands. Paul Birrell's co-authors include Daniela De Angelis, Anne M. Presanis, Richard Pebody, André Charlett, Valérie Delpech, Xu‐Sheng Zhang, Thomas House, Tim Chadborn, Alison Brown and Nick Gent and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of the American Statistical Association.

In The Last Decade

Paul Birrell

28 papers receiving 673 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Paul Birrell United Kingdom 14 384 327 323 71 56 30 686
Christopher E. Overton United Kingdom 13 146 0.4× 198 0.6× 155 0.5× 80 1.1× 67 1.2× 35 793
Andrew J. Shattock Australia 13 226 0.6× 104 0.3× 270 0.8× 47 0.7× 109 1.9× 29 500
Anne M. Presanis United Kingdom 20 738 1.9× 509 1.6× 709 2.2× 33 0.5× 97 1.7× 49 1.5k
Carl A. B. Pearson United Kingdom 17 193 0.5× 365 1.1× 443 1.4× 109 1.5× 173 3.1× 41 1.1k
Ngai Sze Wong Hong Kong 18 521 1.4× 179 0.5× 555 1.7× 139 2.0× 70 1.3× 108 993
Andrew Schroeder United States 8 163 0.4× 247 0.8× 89 0.3× 25 0.4× 39 0.7× 13 521
Bradley G. Wagner United States 11 334 0.9× 241 0.7× 365 1.1× 34 0.5× 94 1.7× 17 679
Cari van Schalkwyk South Africa 15 328 0.9× 164 0.5× 818 2.5× 60 0.8× 50 0.9× 42 1.1k
Daniel J. Klein United States 16 453 1.2× 340 1.0× 685 2.1× 119 1.7× 72 1.3× 37 1.1k
Anthony Amoroso United States 13 184 0.5× 308 0.9× 359 1.1× 66 0.9× 73 1.3× 39 899

Countries citing papers authored by Paul Birrell

Since Specialization
Citations

This map shows the geographic impact of Paul Birrell's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Paul Birrell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Birrell more than expected).

Fields of papers citing papers by Paul Birrell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Birrell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Paul Birrell. The network helps show where Paul Birrell may publish in the future.

Co-authorship network of co-authors of Paul Birrell

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Birrell. A scholar is included among the top collaborators of Paul Birrell based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul Birrell. Paul Birrell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bowers, K. J., Daniela De Angelis, & Paul Birrell. (2025). Modelling with SPEED: a Stochastic Predictor of Early Epidemic Detection. Journal of Theoretical Biology. 607. 112120–112120.
2.
Leeuwen, Edwin van, et al.. (2025). Contact data and SARS-CoV-2: Retrospective analysis of the estimated impact of the first UK lockdown. Journal of Theoretical Biology. 610. 112158–112158.
3.
Birrell, Paul, et al.. (2023). An approximate diffusion process for environmental stochasticity in infectious disease transmission modelling. PLoS Computational Biology. 19(5). e1011088–e1011088. 3 indexed citations
4.
Kirwan, Peter, André Charlett, Paul Birrell, et al.. (2022). Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study. Nature Communications. 13(1). 4834–4834. 16 indexed citations
5.
Swallow, Ben, Paul Birrell, Mark A. Burgman, et al.. (2022). Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics. 38. 100547–100547. 21 indexed citations
6.
Finnie, Thomas, Emma Bennett, Paul Birrell, et al.. (2022). Risk of paediatric multisystem inflammatory syndrome (PIMS-TS) during the SARS-CoV-2 alpha and delta variant waves: National observational and modelling study, 2020–21, England. Frontiers in Pediatrics. 10. 1034280–1034280. 4 indexed citations
7.
Birrell, Paul, et al.. (2021). Variational inference for nonlinear ordinary differential equations.. International Conference on Artificial Intelligence and Statistics. 2719–2727. 1 indexed citations
8.
Birrell, Paul, et al.. (2021). Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave. Philosophical Transactions of the Royal Society B Biological Sciences. 376(1829). 20200279–20200279. 57 indexed citations
9.
Birrell, Paul, Peter Kirwan, Dana Ogaz, et al.. (2021). Tracking elimination of HIV transmission in men who have sex with men in England: a modelling study. The Lancet HIV. 8(7). e440–e448. 13 indexed citations
10.
Walker, A. Sarah, Emma Pritchard, Thomas House, et al.. (2021). Ct threshold values, a proxy for viral load in community SARS-CoV-2 cases, demonstrate wide variation across populations and over time. eLife. 10. 65 indexed citations
11.
Birrell, Paul, Xu‐Sheng Zhang, Edwin van Leeuwen, et al.. (2020). Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study. BMC Public Health. 20(1). 486–486. 7 indexed citations
12.
Birrell, Paul, Lorenz Wernisch, Brian D. M. Tom, et al.. (2020). Efficient real-time monitoring of an emerging influenza pandemic: How feasible?. The Annals of Applied Statistics. 14(1). 74–93. 8 indexed citations
13.
Birrell, Paul, Martyn Plummer, Peter Kirwan, et al.. (2019). Extending Bayesian back-calculation to estimate age and time specific HIV incidence. Lifetime Data Analysis. 25(4). 757–780. 4 indexed citations
14.
Zhang, Xu‐Sheng, Paul Birrell, Nicki L. Boddington, et al.. (2018). Exploiting routinely collected severe case data to monitor and predict influenza outbreaks. BMC Public Health. 18(1). 790–790. 4 indexed citations
15.
Ray, Samiran, et al.. (2017). Haemodynamic changes with paracetamol in critically-ill children. Journal of Critical Care. 40. 108–112. 8 indexed citations
16.
Birrell, Paul, Xu‐Sheng Zhang, Richard Pebody, Nigel Gay, & Daniela De Angelis. (2016). Reconstructing a spatially heterogeneous epidemic: Characterising the geographic spread of 2009 A/H1N1pdm infection in England. Scientific Reports. 6(1). 29004–29004. 7 indexed citations
17.
Angelis, Daniela De, Anne M. Presanis, Paul Birrell, Gianpaolo Scalia Tomba, & Thomas House. (2014). Four key challenges in infectious disease modelling using data from multiple sources. Epidemics. 10. 83–87. 49 indexed citations
18.
Birrell, Paul, O N Gill, Valérie Delpech, et al.. (2013). HIV incidence in men who have sex with men in England and Wales 2001–10: a nationwide population study. The Lancet Infectious Diseases. 13(4). 313–318. 90 indexed citations
19.
20.
Presanis, Anne M., Richard Pebody, Beverley Paterson, et al.. (2011). Changes in severity of 2009 pandemic A/H1N1 influenza in England: a Bayesian evidence synthesis. BMJ. 343(sep08 1). d5408–d5408. 60 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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Breakdown of academic impact, for papers by Christopher E. Overton Breakdown of academic impact, for papers by Andrew J. Shattock Breakdown of academic impact, for papers by Anne M. Presanis Breakdown of academic impact, for papers by Carl A. B. Pearson Breakdown of academic impact, for papers by Ngai Sze Wong Breakdown of academic impact, for papers by Andrew Schroeder Breakdown of academic impact, for papers by Bradley G. Wagner Breakdown of academic impact, for papers by Cari van Schalkwyk Breakdown of academic impact, for papers by Daniel J. Klein Breakdown of academic impact, for papers by Anthony Amoroso
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