Background:
In temperate climates, influenza dynamics are well characterized with outbreaks occurring in late winter [1]; this means that annual vaccinations can be planned for early winter to have the maximal impact [2]. In the tropics the pattern is less clear [3]; Influenza A occurs throughout the year in Kenya [4], but patterns of occurrence differ geographically with some areas experiencing two peaks each year. In Kenya (as in other countries) school-aged children appear to be the main drivers of transmission. There is a need to better understand the dynamics of influenza and strain co-circulation, and hence predict the impact of different vaccination strategies [5].
The project aims to:
In consultation with the Kenya National Vaccines and Immunization Programme (NVIP),
- Develop or adapt an age-structured strain-structured transmission dynamic for influenza in Kenya
- Explore a range of vaccination strategies (school-aged vs maternal immunisation vs high-risk groups) and their impact on influenza cases.
- Provide evidence on control options and recommendations on future data needs
Methods/Study design:
Data will be collated on the spatial and temporal dynamics of influenza and the strain structure. A hierarchy of mathematical models will be developed to interpret these data in terms of the transmission dynamics and strain cross reactivity. These models will be used to assess the optimal vaccination pattern both regionally and nationally, and how this is influenced by the observed pattern of cases. Consideration will also be given to how to assess the impact of any vaccination program once it is in operation.
The outputs will be:
- Advice to National Vaccines and Immunization Program on strategy options
- Recommendation on surveillance data requirement for Kenya such as serology
- Develop in-country skills in predictive modelling of infectious disease
Role of /links with National / Local Public-Health Organisation
(including access to data, sources of samples, role in defining question and potential impact on policy)
- These ideas arose from discussions with the Director of the National Vaccine and Immunization Programme (NVIP) and the Director of the Division of Disease Surveillance and Epidemic Response, Ministry of Health– see meeting notes.
- This work would benefit from strong interaction with genomic-based fellowships that could interrogate influenza samples.
References:
- L. Simonsen. The global impact of influenza on morbidity and mortality. Vaccine 17: S3-S10. doi: 10.1016/S0264-410X(99)00099-7
- World Health Organisation. Vaccines against influenza WHO position paper – November 2012. Weekyl Epidemiological Record (87)47:462-476.
- C. Viboud, W. Alonso, L. Simonsen. Influenza in Tropical Regions. PLoS Medicine. 3(4): e89. doi: 10.1371/journal.pmed.0030089
- M. Katz et al. Results From the First Six Years of National Sentinel Surveillance for Influenza in Kenya, July 2007–June 2013. PLoS ONE 9(6): e98615. doi: 10.1371/journal.pone.0098615
- S. Hirve et al. Influenza Seasonality in the Tropics and Subtropics – When to Vaccinate? PLoS ONE 11(4): e0153003. doi: 10.1371/journal.pone.0153003