We are a research group based at the Centre for Mathematical Modelling of Infectious Diseases of the London School of Hygiene & Tropical Medicine developing methodology and tools for real-time modelling and forecasting of infectious disease outbreaks. We systematically assess these methods by their predictive ability and apply them in order to improve decision making. Ultimately, our goal is to develop and use robust methodology that makes the most of available resources to provide insights useful for outbreak response, control and prevention, and to make them available as tools to others.
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Researchers at the London School of Hygiene & Tropical Medicine doing research to forecast infectious diseases and perform real-time analyses.
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Showing 10 of 125 repositories
- BVDOutbreakSize Public
Joint Bayesian generative Turing model for the 2026 DRC BVD outbreak. Combines exports, deaths and reported suspected cases (with ascertainment) in a single posterior. Includes a no-onward-transmission deaths lower bound.
- eval-by-method Public
- omicron-sgtf-forecast Public
In this work, we use S-gene target failure (SGTF) as a proxy of variant status combined with reported case counts to explore the evidence for changes in transmission advantage over time for the Omicron variant. If present this could indicate the impact of immune escape, bias in SGTF data or differences in the populations within which the variant…
- inc2prev Public
Estimate epidemiological quantities from repeated cross-sectional prevalence measurements
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