Imperial College London


Faculty of MedicineSchool of Public Health

GIS/Database/HPTC Analyst Tech Support



+44 (0)20 7594 3269w.hinsley




G31Norfolk PlaceSt Mary's Campus





I provide technical help with high-performance computing, cluster support, large dataset issues, database handling and general programming assistance to members of the MRC Centre for Outbreak Analysis, in the Department of Infectious Diseases and Epidemiology in St. Mary's. I also am continuing development of the Global Epidemic Simulator: a platform for modelling of directly-transmitted infectious diseases such as influenza. Simulations are individual-based, involving the travel moments and interactions between infected and susceptible people.

My background is Computer Engineering, with an M.Eng and Ph.D from Imperial College Department of Computing. My main areas of experience are software engineering, code-generating compilers (auto-programming), and individual-based modelling. Previously I designed the Virtual Ecology Workbench (VEW), a suite of tools for creating individual-based plankton ecosystem models.



Gaythorpe K, Fitzjohn R, Hinsley W, et al., 2023, Data pipelines in a public health emergency: the human in the machine, Epidemics: the Journal of Infectious Disease Dynamics, Vol:43, ISSN:1755-4365

Laydon D, Cauchemez S, Hinsley W, et al., 2023, Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study, The Lancet Global Health, Vol:11, ISSN:2214-109X, Pages:e759-e769

Imai N, Rawson T, Knock E, et al., 2023, Quantifying the impact of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study, The Lancet Public Health, Vol:8, ISSN:2468-2667, Pages:e174-e183

Nyberg T, Ferguson NM, Blake J, et al., 2022, Misclassification bias in estimating clinical severity of SARS-CoV-2 variants - Authors' reply., Lancet, Vol:400, Pages:809-810

Laydon DJ, Cauchemez S, Hinsley WR, et al., 2022, Prophylactic and reactive vaccination strategies for healthcare workers against MERS-CoV

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