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Professor Adam Kucharski

Professor of Infectious Disease Epidemiology

United Kingdom

My research focuses on making better use of data and analytics for understanding infectious disease dynamics, to inform epidemic preparedness and response. This includes large-scale studies of social behaviour and immunity, as well as development of statistical methods and open-source software tools. 

 

I was a founding co-director of the Centre for Epidemic Preparedness and Response at LSHTM (2022–2025), and have contributed scientific insights to multiple governments and health agencies. From 2017–23, I was a Wellcome Trust/Royal Society Sir Henry Dale Fellow and from 2013–17, I held a Medical Research Council Career Development Award in Biostatistics. Prior to joining the School in October 2013, I was a postdoc at Imperial College London. I have a degree in mathematics from the University of Warwick (2009) and a PhD in applied mathematics from the University of Cambridge (2012).

Affiliations

Department of Infectious Disease Epidemiology and Dynamics
Faculty of Epidemiology and Population Health

Centres

Centre for Epidemic Preparedness and Response
Centre for Mathematical Modelling of Infectious Diseases

Teaching

I teach about infectious disease epidemiology, outbreak analysis and modelling on a range of LSHTM modules, and have previosusly co-organised the MSc modules Epidemiology of Infectious Diseases (2437) and Modelling & the Dynamics of Infectious Diseases (2464), and the Outbreak Analytics and Applied Modelling in R shortcourse.

Research

Much of my work involves developing new mathematical and statistical approaches to understand the dynamics of infectious disease outbreaks. I am particularly interested in how to combine multiple data sources – including surveillance data, social behaviour studies and novel serological surveys – to uncover transmission dynamics and impact of interventions. This research covers directly transmitted infections like COVID-19, influenza and Ebola as well as arboviruses like dengue and Zika.

Public engagement is also an important part of my work: as well as running events in schools, museums and festivals, I have worked on several projects linking citizen science with large-scale data collection. My articles have appeared in places like Wired, Financial Times, New Scientist, Scientific American, The Times and The Observer. My popular science book 'The Rules of Contagion' was named as a 2020 Times, Guardian and FT Science Book of the Year, and my book 'Proof' was named an FT, New Scientist and Waterstones Science Book of 2025.

Selected Publications

Estimating the effectiveness of routine asymptomatic PCR testing at different frequencies for the detection of SARS-CoV-2 infections.
HELLEWELL, J; RUSSELL, TW; SAFER Investigators and Field Study Team,; Crick COVID-19 Consortium,; CMMID COVID-19 working group,; Beale, R; Kelly, G; Houlihan, C; Nastouli, E; KUCHARSKI, AJ;
2021
BMC medicine
Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study.
KUCHARSKI, AJ; KLEPAC, P; Conlan, AJ K; Kissler, SM; Tang, ML; Fry, H; Gog, JR; EDMUNDS, WJ; CMMID COVID-19 working group,;
2020
LANCET INFECTIOUS DISEASES
Early dynamics of transmission and control of COVID-19: a mathematical modelling study.
KUCHARSKI, AJ; RUSSELL, TW; DIAMOND, C; LIU, Y; EDMUNDS, J; FUNK, S; EGGO, RM; Centre for Mathematical Modelling of Infectious Di,;
2020
The Lancet. Infectious diseases
Real-time analysis of the diphtheria outbreak in forcibly displaced Myanmar nationals in Bangladesh.
Finger, F; FUNK, S; White, K; Siddiqui, MR; EDMUNDS, WJ; KUCHARSKI, AJ;
2019
BMC medicine
Timescales of influenza A/H3N2 antibody dynamics.
KUCHARSKI, AJ; Lessler, J; Cummings, DA T; Riley, S;
2018
PLoS biology
Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji.
KUCHARSKI, AJ; Kama, M; Watson, CH; Aubry, M; FUNK, S; HENDERSON, AD; BRADY, OJ; Vanhomwegen, J; Manuguerra, J-C; Lau, CL; EDMUNDS, WJ; Aaskov, J; Nilles, EJ; Cao-Lormeau, V-M; Hué, S; HIBBERD, ML;
2018
eLife
Exploring epidemic control policies using nonlinear programming and mathematical models.
Montes-Olivas, S; KUCHARSKI, AJ; Gravenor, MB; Frost, SD W;
2026
PLoS computational biology
Acute Febrile Illness Surveillance for Estimating Population Immunity, Dominican Republic, 2021.
Nilles, EJ; Paulino, CT; Vasquez, M; Duke, W; Jarolim, P; Ramm, RS; KUCHARSKI, A; Lau, CL;
2026
Emerging infectious diseases
Mucosal IgA to pre-fusion F protein predicts protection from RSV infection in a high burden setting
Hodgson, D; JARJU, S; Gatcombe, L; Coleman, T; Dowgier, G; Wenlock, R; Lindsey, B; Danso, M; Barratt, N; Gomes, M; Grouneva, I; JAGNE, YJ; KAMPMANN, B; Wu, M; Otter, A; FLASCHE, S; KUCHARSKI, A; De Silva, T;
2026
medRxiv
Kinetics of antibodies and risk of respiratory syncytial virus infection: a longitudinal cohort in Taizhou City, eastern China.
Wang, Q; Hodgson, D; Zheng, B; Liang, H; Zhang, S; Xu, J; Leung, K; KUCHARSKI, A; Lin, H; Wang, W;
2026
BMC medicine
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