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Last Updated: 18/06/2024
Use of hospital cases of uncomplicated malaria to identify malaria hot spots, risk factors and map malaria heterogeneity to guide targeting of malaria control interventions in under-five children in Malawi
Objectives
As an extension of previous work which focused on the use of malaria infection prevalence data to model and map malaria risk and develop adaptive sampling methods for household prevalence survey, this proposal sets to use under five uncomplicated malaria hospital cases to identify hotspots, risk factors, and map heterogeneity in malaria burden, to inform targeting of malaria control interventions in an area with declining clinical malaria burden due to intense malaria control interventions in Malawi.
Liverpool School of Tropical Medicine (LSTM), United Kingdom
Malaria control programmes are increasingly encouraged to define the variation in malaria risk within their countries and districts to help them take evidence informed decisions how to make the best use the available malaria control tools and resources. While variations in vector ecology, environment, and malaria control efforts may all contribute to variations in malaria risk and disease burden in place and time, control programs need tools that can be part of their existing routine malaria surveillance system. Utilizing the DHIS2 linked tracker tool, we will explore geostatistical method to model sub-district level malaria incidence e, accessible, and cost-effective option available to national control programmes to model and map malaria heterogeneity and understand risk factors in areas with declining malaria burden to guide malaria control.
Nov 2020 — Apr 2023
$161,264
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