Search

Background Deforestation and land use change is widespread in Madagascar, altering local ecosystems and creating opportunities for disease vectors, such as the Anopheles mosquito, to proliferate and more easily reach vulnerable, rural populations. Knowledge of risk factors associated with malaria infections is growing globally, but these associations remain understudied across Madagascar’s diverse ecosystems experiencing rapid environmental change. This study aims to uncover socioeconomic, demographic, and ecological risk factors for malaria infection across regions through analysis of a large, cross-sectional dataset.Methods The objectives were to assess(1) the ecological correlates of malaria vector breeding through larval surveys, and (2) the socioeconomic, demographic, and ecological risk factors for malaria infection in four ecologically distinct regions of rural Madagascar. Risk factors were determined using multilevel models for the four regions included in the study.Results The presence of aquatic agriculture (both within and surrounding communities) is the strongest predictive factor of habitats containing Anopheles larvae across all regions. Ecological and socioeconomic risk factors for malaria infection vary dramatically across study regions and range in their complexity.Conclusions Risk factors for malaria transmission differ dramatically across regions of Madagascar. These results may help stratifying current malaria control efforts in Madagascar beyond the scope of existing interventions.

Background Deforestation and land use change is widespread in Madagascar, altering local ecosystems and creating opportunities for disease vectors, such as the Anopheles mosquito, to proliferate and more easily reach vulnerable, rural populations. Knowledge of risk factors associated with malaria infections is growing globally, but these associations remain understudied across Madagascar’s diverse ecosystems experiencing rapid environmental change. This study aims to uncover socioeconomic, demographic, and ecological risk factors for malaria infection across regions through analysis of a large, cross-sectional dataset. Methods The objectives were to assess (1) the ecological correlates of malaria vector breeding through larval surveys, and (2) the socioeconomic, demographic, and ecological risk factors for malaria infection in four ecologically distinct regions of rural Madagascar. Risk factors were determined using multilevel models for the four regions included in the study. Results The presence of aquatic agriculture (both within and surrounding communities) is the strongest predictive factor of habitats containing Anopheles larvae across all regions. Ecological and socioeconomic risk factors for malaria infection vary dramatically across study regions and range in their complexity. Conclusions Risk factors for malaria transmission differ dramatically across regions of Madagascar. These results may help stratifying current malaria control efforts in Madagascar beyond the scope of existing interventions.

Background: Deforestation and land use change is widespread in Madagascar, altering local ecosystems and creating opportunities for disease vectors, such as the Anopheles mosquito, to proliferate and more easily reach vulnerable, rural populations. Knowledge of risk factors associated with malaria infections is growing globally, but these associations remain understudied across Madagascar’s diverse ecosystems experiencing rapid ecological change. This study aims to uncover socioeconomic, demographic, and ecological risk factors for malaria infection across regions through analysis of a large, cross-sectional dataset.Methods: Here, we assess (1) the ecological correlates of malaria vector breeding through larval surveys, and (2) the socioeconomic, demographic, and ecological risk factors for malaria infection in four ecological regions of rural Madagascar. We determine risk factors using multilevel models for each unique ecological region of included in the study.Results: We find that regardless of the region, the presence of forms of aquatic agriculture around a community are predictive of the presence of malaria vectors. We determine that ecological and socioeconomic risk factors for malaria infection vary dramatically across study regions and range in their complexity.Conclusions: Risk factors for malaria transmission differ dramatically across regions of Madagascar. These results may help stratifying current malaria control efforts in Madagascar beyond the scope of existing interventions.

Background Land-use changes, such as deforestation, can increase the transmission potential of a landscape by increasing the abundance of preferred microhabitats for malaria vectors. However, this relationship between malaria and deforestation is complex and depends on factors such as the type of land use, the local ecology of malaria vector species, and the health resources available to the human population. In Madagascar, despite alarmingly high rates of deforestation and concerning reports of increases in malaria, this link remains poorly studied. Methods The feasibility of traditional approaches to studying the link between malaria and deforestation is limited for Madagascar because (i) health systems lack capacity to collect regular and accurate malaria data, especially in many rural areas, (ii) vector habitat preferences are poorly understood, and (iii) most existing malaria infection outcome datasets lack data on important mediating factors. To circumvent inadequacies in current data streams, we discuss a new framework that integrates novel primary data collection efforts on malaria infection and vector ecology from cross-sectional studies with longitudinal land-use data from remote sensing. Incorporating these data into hierarchical models allows us to infer structural associations between macro and micro level predictors of malaria risk in different ecological contexts in Madagascar. We compare the outputs from these models to analyses that can be conducted with robust data from the Brazilian health system. Findings We report data on malaria burden, deforestation, its covariates, and vector larval habitat preference for four distinct, previously understudied, ecoregions of Madagascar. Risk factors of malaria infection vary in sign and magnitude of effect across ecological contexts. Interpretation While data such as Brazil's allow for predictive modelling and assessment of temporally dynamic systems, our proposed modelling framework demonstrates variations in risk factors regionally in the meantime. This approach can help to mitigate current data gaps and better inform existing malaria control efforts in Madagascar during health system development. Funding The Ren Che Foundation, Henry David Thoreau Foundation, Catholic Relief Services through a grand from United States Agency for International Development, and Madagascar Health and Environmental Research (MAHERY).