Details of Award
NERC Reference : NE/P004407/1
Impact of El Ni?o on malaria vector dynamics in Tanzania: observation, improvement and unleashing forecasting potential
Grant Award
- Principal Investigator:
- Professor M Baylis, University of Liverpool, Institute of Infection and Global Health
- Co-Investigator:
- Professor H Ferguson, University of Glasgow, College of Medical, Veterinary, Life Sci
- Co-Investigator:
- Professor AP Morse, University of Liverpool, Geography and Planning
- Grant held at:
- University of Liverpool, Institute of Infection and Global Health
- Science Area:
- Terrestrial
- Overall Classification:
- Unknown
- ENRIs:
- Environmental Risks and Hazards
- Science Topics:
- Climate & Climate Change
- Human health impacts
- Regional & Extreme Weather
- Environment & Health
- Abstract:
- El Nino events have been shown to impact significantly on many vector-borne diseases (VBDs), including malaria, dengue, Rift Valley fever and others. While the link between El Nino and disease is well established, the mechanism underlying it is not fully resolved, but probably involves impact of the change in rainfall patterns (often drought and then heavy rain, or vice versa) or altered temperatures brought by El Nino on the vectors themselves. Here we aim to take advantage of the collection over the past 9 years of detailed entomological data on one VBD to detect a perturbation to vector dynamics caused by the current El Nino event. The strength of the current El Nino, the existence of high quality entomological data, the inclusion of the team responsible in this proposal, and access to local meteorological data provide a unique opportunity to understand how El Ni?o events trigger the emergence of VBDs. We focus on malaria, which remains the VBD with the greatest impact on human mortality and morbidity, and propose new fieldwork in the Kilombero valley area of central Tanzania, where there is a 30% prevalence of infection in people. Malaria is caused by parasitic protozoa of the genus Plasmodium and it is transmitted by female Anopheles mosquitoes. The spatial limits of malaria distribution, its seasonal activity and the mosquito vector dynamics are very sensitive to climate factors, as well as the local capacity to control the disease. The aim of this proposal is to characterize the chain of connections between the current El Ni?o event, its impact on regional and local climate, and the subsequent consequences on malaria vectors and malaria burden in Tanzania. This is carried out to better understand how El Nino affects malaria, and in order to build an early warning system prototype for malaria risk in Tanzania. We will achieve this though the use of new and standard technologies to measure mosquito vector properties within the Kilombero Valley. We will undertake 12 months of detailed entomological study in a number of previously-studied villages in the region, in the expectation of detecting a change or perturbation to vector dynamics or behaviour caused by El Nino. These new data will be analysed in the context of the 9 years of historic data already collected between 2006-2015 (this field campaign ended in May 2015), as well as malaria clinical data and different climate datasets, ranging from regional scale satellite estimates to local scale meteorological station data available for the studied region. Detailed weather data for the areas are available from a local weather station, and will be supported by temperature/humidity data collection in the study villages. Based on the findings, we will develop a better understanding of how El Nino impacts on malaria and its vectors (with applicability to a wider range of VBDs) and build a prototype early warning system for malaria risk in Tanzania. This will be a useful resource for local decision makers and public health specialists to target and allow vector control resources in future.
- NERC Reference:
- NE/P004407/1
- Grant Stage:
- Completed
- Scheme:
- Directed (RP) - NR1
- Grant Status:
- Closed
- Programme:
- El Nino
This grant award has a total value of £262,752
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Exception - Other Costs | Indirect - Indirect Costs | DA - Investigators | DI - Staff | DA - Estate Costs | Exception - Staff | Exception - T&S | DI - T&S |
|---|---|---|---|---|---|---|---|---|
| £2,020 | £44,995 | £47,025 | £10,983 | £46,976 | £7,776 | £88,801 | £4,241 | £9,936 |
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