Description of impact
The Institute of Pure and Applied Mathematics (IPAM), with the Department of Physics and School of Medicine, Medical Sciences and Nutrition developed and applied mathematical models to tackle infectious diseases in the UK and EU. Specifically:Our machine learning research underpinned action on human campylobacteriosis and informed professional debate on the source of human listeriosis in the UK and EU.
We used compartmental models to determine progress of the COVID19 epidemic, understand role of asymptomatic cases in local outbreaks and predict outbreaks in higher education institutions. This informed the actions of public health teams.
Our research and advice contributed to food safety standards and embedding of risk assessment practice in the UK and EU.
| Impact status | Impact Completed (Open) |
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Keywords
- Political
Documents & Links
Related content
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Research output
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Estimating the number of COVID-19 cases being introduced into UK Higher Education Institutions during Autumn 2020
Research output: Working paper
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Immunization and Targeted Destruction of Networks using Explosive Percolation
Research output: Contribution to journal › Article › peer-review
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Hierarchical dose response of E. coli O157:H7 from human outbreaks incorporating heterogeneity in exposure
Research output: Contribution to journal › Article › peer-review
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Importance of untested infectious individuals for the suppression of COVID-19 epidemics
Research output: Working paper
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Mining whole genome sequence data to efficiently attribute individuals to source populations
Research output: Contribution to journal › Article › peer-review
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Campylobacter genotyping to determine the source of human infection
Research output: Contribution to journal › Article › peer-review