Malaria Journal

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Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

Alberto Gomez-Elipe*, Angel Otero, Michel van Herp and Armando Aguirre-Jaime

Malaria Journal 2007, 6:129 doi:10.1186/1475-2875-6-129

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Geo-additive modelling of malaria in Burundi

Hermenegilde Nkurunziza, Albrecht Gebhardt, Jürgen Pilz Malaria Journal 2011, 10:234 (11 August 2011)

Models suggest a strong positive association between malaria incidence in a given month and the minimum temperature of the previous month. Non-climatic variables include socio-economic conditions, food shortage, limited access to healthcare service, precarious housing, promiscuity, poor hygienic conditions, limited access to drinking water, land use and displacement of the population.

Research   Open Access

Model variations in predicting incidence of Plasmodium falciparum malaria using 1998-2007 morbidity and meteorological data from south Ethiopia

Eskindir Loha, Bernt Lindtjørn Malaria Journal 2010, 9:166 (16 June 2010)

This study describes falciparum malaria incidence models linked with meteorological data. Variability in the models was principally attributed to regional differences, and a single model was not found that fits all locations. Past falciparum malaria incidence appeared to be a superior predictor than meteorology. Future efforts in malaria modelling may benefit from inclusion of non-meteorological factors.

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Bayesian modelling of the effect of climate on malaria in Burundi

Hermenegilde Nkurunziza, Albrecht Gebhardt, Jürgen Pilz Malaria Journal 2010, 9:114 (29 April 2010)

A spatial/longitudinal statistical analysis to identify important climatic variables that influence malaria incidences in Burundi

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Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

Jean Gaudart, Ousmane Touré, Nadine Dessay, A lassane Dicko, Stéphane Ranque, Loic Forest, Jacques Demongeot, Ogobara K Doumbo Malaria Journal 2009, 8:61 (10 April 2009)

This paper reports an ambitious attempt to produce a spatially structured model for malaria transmission in Mali, based on remote sensed vegetation indices (NDVI), together with an SIRS type transmission model, calibrated using data from the village of Bancoumana.

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Spatially-explicit risk profiling of Plasmodium falciparum infections at a small scale: a geostatistical modelling approach

Kigbafori D Silué, Giovanna Raso, Ahoua Yapi, Penelope Vounatsou, Marcel Tanner, Eliézer K N'Goran, Jürg Utzinger Malaria Journal 2008, 7:111 (23 June 2008)

A paper that expands on recent work by the authors on geostatistical modeling of helminth infections and explores risk factors for malaria in a small area of western Ivory Coast