Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa. This work, led by Ph.D student Amelia Bertozzi-Villa and Dr. Samir Bhatt, combines mechanistic and geospatial modelling tools and takes advantage of data from a range of sources to generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. While highlighting the immense progress made over the past 20 years, this analysis also highlights important barriers to high ITN coverage, such as short net retention time and inefficient allocation of nets during mass campaigns. These results can inform both policy decisions and downstream malaria analyses.
Read MoreInsecticide-Treated Net Coverage in Africa
Current Project
Indirect effects of the COVID-19 pandemic on malaria intervention coverage
Current Project
Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control.
Read MoreAccessibility to Healthcare
Current Project
Access to healthcare is a measure of human well-being that is constrained by numerous geographically-varying factors, the most immediate of which is the time it takes individuals to travel to a properly equipped and adequately staffed healthcare facility. Under the leadership of Dr Daniel Weiss, Director of Global Malaria Epidemiology at MAP, we characterize travel time to healthcare facilities in unprecedented detail. We produce global travel time maps with and without access to motorized transport, thus characterizing travel time to healthcare for populations distributed across the wealth spectrum.
Read MoreHousing In Africa
Past Project
Catchment modelling for area-averaged malaria data
Current Project
Until recently, the limited availability and low quality of routine health care data on the incidence of febrile malaria in low resource settings has meant that the vast majority of risk mapping has relied upon direct observations of parasite prevalence as a proxy for disease burden, particularly those from the large-scale Malaria Indicator Survey program. Under the leadership of Director of Malaria Risk Stratification Dr Ewan Cameron, MAP is developing a statistical framework for simultaneous estimation of malaria risk maps and health facility catchments based on a modified ‘gravity model’. Read More
Semi-mechanistic modelling for serological survey data
Current Project
As countries near malaria elimination, serological measurements become increasingly important for malaria burden estimation. MAP is working to integrate serological data within our risk mapping framework using novel semi-mechanistic models based.
Read MoreImproved intervention coverage models
Current Project
The Global Malaria Epidemiology team generates detailed models of interventions to improve burden estimation models and attribute declines in malaria to specific measures.
Read MorePixel-level modelling in low burden areas
Current Project
In low burden areas of the world, surveillance data is often a more informative measurement of malaria burden than parasite rate surveys, but these data are challenging to use in pixel-level modelling. We are developing disaggregation models that use these data alongside pixel-level environmental and human covariates in order to produce high-resolution burden estimates.
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