Malaria Atlas Project

A key aspect of MAP’s work is to use statistical approaches to modelling the prevalence of different forms of malaria on a global scale using Bayesian model-based geostatistics.[6]

Various environmental factors are known to affect malaria prevalence. Malaria prevalence is known to vary in a relatively predictable fashion in space and time, and observed malaria prevalence depends heavily on people’s age and intervention coverage.

In spatial epidemiology, it is common to find that very few measurements have been taken in large parts of the geographical region of interest. The available measurements may be error-prone or incompletely reported, and almost always it is a subset of the local population that has been surveyed.

Since 2005, MAP has collated an extensive database of survey data from a variety of sources. These surveys are typically clustered at village level and record data on parasite positivity rates, usually determined by rapid diagnostic blood tests. Additionally, MAP has gathered extensive data on covariates such as temperature suitability and land cover. These factors affect the distribution of the mosquito vectors responsible for spreading malaria.

The benefit of using Bayesian model-based geostatistics is that it conveys the spatially varying level of uncertainty associated with the mapped surface.

The probability that any of the very many individual (candidate) maps is the single correct map is small, so it is not useful to report the single most likely map. Taken together, however, the candidate maps make it possible to compute the probability of correctness of statements about the map, such as Plasmodium falciparum endemicity at location x in 2010 was between 0.1 and 0.3".

Since the year 2000, a concerted campaign against malaria has led to unprecedented levels of intervention coverage across sub-Saharan Africa. Future control planning depends on understanding the effect of this effort. However, the effect of malaria interventions across the varied epidemiological settings of Africa remains poorly understood owing to the absence of reliable surveillance data and the simplistic approaches underlying current disease estimates.

In September 2015, research by MAP published in Nature quantified the attributable effect of malaria disease control efforts in Africa. The results showed Plasmodium falciparum infection prevalence in endemic Africa halved and the incidence of clinical disease fell by 40% between 2000 and 2015. The best estimate is that interventions have averted 663 million clinical cases since 2000. Insecticide-treated nets, the most widespread intervention, were by far the largest contributor. Although still below target levels, current malaria interventions have substantially reduced malaria disease incidence across the continent.[7][8]

World map of Plasmodium falciparum endemicity in 2010

In 2012, MAP published the first global maps for Plasmodium vivax endemicity.[4]

The spatial distribution of Plasmodium vivax malaria endemicity map in 2010 globally

The MAP team works in collaboration with the World Health Organization (WHO) to provide the prevalence estimates for sub-Saharan African countries for the annual World Malaria Report. Additionally, MAP aids the WHO in production of the annual prevalence rates maps in the World Malaria Report.

The MAP database is the biggest source of processed malariometric data available.

By April 2015, the MAP database contained:

• 40,000 geo-referenced cluster locations’ parasite rate survey records from 2,010 sources
• The database contains approximately 50,000 Annual Parasite Incidence (hereafter API) records for the years 2002 – 2010.

MAP actively seeks out and curates a wide variety of additional data from different sources, including the following:

• Malaria intervention coverage indicator data
• Parasite rate data
• Annual Parasite Incidence data
• Treatment-seeking data
• Satellite data to provide covariate raster surfaces
• Blood disorder data
• Mosquito bionomics and distribution data

MAP is committed to the free and open dissemination of this data (where permission has been granted by the data owner to release it). Dissemination of data is facilitated via the main MAP webpage and the Explorer tool. The latter allows users to download tabular data on malaria by countries.