Influenza transmission models and detecting infection outcomes in electronic health records: a big data study in OpenSafely
Influenza causes hospitalisations and deaths especially in
older people, either resulting directly from infection or by
triggering worsening of pre-existing conditions such as heart
disease, or asthma. Quantifying how many health events
result from influenza infection has been approached by a
variety of methods, but this has not yet included dynamic
transmission models. These are needed because the
dynamics of influenza in groups at risk of infection vary from
the general population. As examples: i) older adults are
generally vaccinated, but the risk of transmission (& size of
the epidemic) depends on vaccine coverage and efficacy in
the entire population, ii) older adults live in households or in
long-term care facilities, which have very different risks of
infection.
This project will build on ongoing work for combining
infectious disease modelling with individual-level analysis of
risk of outcomes to build methodology and the scientific
evidence base for how to link influenza circulation with health
outcomes (specifically hospitalisation and death).
The project may also consider COVID-19 depending on the
epidemiological situation during the PhD.
Details on application procedures are available at: https://mrc-lid.lshtm.ac.uk/
- Type
- PhD position
- Institution
- LSHTM
- City
- London
- Country
- UK
- Closing date
- January 18th, 2021
- Posted on
- November 29th, 2020 12:21
- Last updated
- November 30th, 2020 22:21
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