Madagascar

Large-scale variation in ecological parameters across Madagascar is hypothesized to drive varying spatial patterns of malaria infection. However, to date, few studies of parasite prevalence with resolution at finer, sub-regional spatial scales are available. As a result, there is a poor understanding of how Madagascar’s diverse local ecologies link with variation in the distribution of infections at the community and household level. Efforts to preserve Madagascar’s ecological diversity often focus on improving livelihoods in rural communities near remaining forested areas but are limited by a lack of data on their infectious disease burden.

Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care.

Malaria transmission in Madagascar is highly heterogeneous, exhibiting spatial, seasonal and long-term trends. Previous efforts to map malaria risk in Madagascar used prevalence data from Malaria Indicator Surveys. These cross-sectional surveys, conducted during the high transmission season most recently in 2013 and 2016, provide nationally representative prevalence data but cover relatively short time frames.

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.

In low-malaria-transmission areas of Madagascar, annual parasite incidence (API) from routine data has been used to target indoor residual spraying at sub-district commune levels. To assess validity of this approach, we conducted school-based serological surveys and health facility (HF) data quality assessments in seven districts to compare API to “gold-standard” commune-level serological measures.