Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors: Evidence from rural Madagascar

• Published in: PLOS global public health 2023-01, Vol.3 (2)
• Main Authors: Julie D. Pourtois, Krti Tallam, Isabel Jones, Elizabeth Hyde, Andrew J. Chamberlin, Michelle V. Evans, Felana A. Ihantamalala, Laura F. Cordier, Bénédicte R. Razafinjato, Rado J. L. Rakotonanahary, Andritiana Tsirinomen’ny Aina, Patrick Soloniaina, Sahondraritera H. Raholiarimanana, Celestin Razafinjato, Matthew H. Bonds, Giulio A. De Leo, Susanne H. Sokolow, Andres Garchitorena
• Format: Article
• Language: English
• ISSN: 2767-3375

While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria dynamics in rural Madagascar, estimated from facility-based passive surveillance data. Specifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by Fokontany, a cluster of villages) relevant to health care practitioners. Combining generalized linear mixed models (GLMM) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. In addition, out-of-sample predictions from our model were able to identify 58% of the Fokontany in the top quintile for malaria incidence and account for 77% of the variation in the Fokontany incidence rank. These results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.