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Infectious diseases remain a leading cause of morbidity and mortality worldwide, with HIV, tuberculosis and malaria estimated to cause 10% of all deaths each year. New pathogens continue to emerge, as demonstrated by the SARS epidemic in 2003, the swine flu pandemic in 2009, MERS CoV in 2013, Zika in 2016 and, recently, SARS-CoV-2.
Mathematical models are being increasingly used to understand the transmission of infections and to evaluate the potential impact of control programmes in reducing morbidity and mortality. Applications include determining optimal control strategies against new or emergent infections, such as SARS-Cov-2, swine flu, Zika or Ebola, or against HIV, tuberculosis and malaria, and predicting the impact of vaccination strategies against common infections such as measles and rubella. Modelling was used extensively in the UK during the recent swine flu pandemic to monitor the extent of ongoing transmission and the potential impact of control such as school closures and vaccination. It is currently being used in many countries to predict the impact of interventions against COVID-19.
This two week course, organised jointly between the London School of Hygiene & Tropical Medicine and the UK Health Security Agency (formerly, Public Health England) is intended to introduce professionals working on infectious diseases in either developing or developed countries to this exciting and expanding area. The emphasis will be on developing a conceptual understanding of the basic methods and on their practical application, rather than the manipulation of mathematical equations. The methods will be illustrated by “hands-on” experience of setting up models in spreadsheets as well as other specialist modelling packages, small group work, and seminars in which the applications of modelling will be discussed.
By the end of the course participants will have deepened their current understanding of infectious disease epidemiology and have gained an understanding and practical experience of the basics of infectious disease modelling, which will be useful in their future work.
Course dates for 2023 19 – 30 June
