Development of spatial statistical methods for geographical mapping of malaria transmission parameters derived from mathematical models of transmission

• Unité de recherche: TPH
• Numéro de projet: 6.02
• Titre du projet anglais: Development of spatial statistical methods for geographical mapping of malaria transmission parameters derived from mathematical models of transmission

Mots-clé (Anglais)

Africa, Bayesian methods, cyclical feeding model , Garki model, geostatistics, kriging, malaria, Markov chain Monte Carlo

Description succincte (Anglais)

The project aims

(a) To develop statistical methods for spatial analysis and mapping of the parameters of dynamic models of malaria transmission, and for estimating the effects on transmission of environmental covariates.

(b) To apply these methods to the mapping of malaria transmission intensity, in particular using a large set of age-specific prevalence data for P. falciparum from West and Central Africa.

(c) To apply these methods to provide spatially structured estimates of malaria transmission within microepidemiological studies, as inputs for new mathematical models of malaria dynamics in humans.

(d) To apply related methods to the mapping of the spatial distribution of different malaria vectors (using a dataset from Mali as an example) and thus to analyse the relationship between transmission potential and sibling species of Anopheles mosquitoes.

Objectifs du projet (Anglais)

(a) The project will develop novel statistical methods applicable in a wide range of disease mapping applications where risk is measured indirectly or as a multinomial outcome.

(b) Maps of malaria transmission intensity, and of the numbers of people exposed at each level of transmission, at the regional, or national level will provide estimates of burden of disease, replacing current estimates that assume uniformity in risk across wide areas. These maps will be of value in gauging needs of control programs, and as baseline for estimating the effectiveness of national control plans.

(c) The methods for estimating the effects of covariates (including insecticide-treated net coverage) on spatial patterns of malaria transmission indices will provide estimates of the spatial effects of interventions, and thus improved effectiveness estimates. This is especially relevant evaluating mosquito net programs.

(d) Estimates of vectorial capacity based on spatial modelling of the micro-epidemiological data will be useful for the development of new dynamic models of malaria transmission that allow appropriately for local heterogeneity in transmission.

Résumé des résultats (Abstract) (Anglais)

The project is developing statistical methods for spatial analysis and mapping of the parameters of dynamic models of malaria transmission, and for estimating the effects on transmission of environmental covariates.

In addition the project applies these methods to the mapping of malaria transmission intensity, in particular using a large set of age-specific prevalence data for P. falciparum from West and Central Africa.
The methods are also applied in the analysis of other microepidemiological studies of malaria.