New analysis could help forecast malaria outbreaks PLOSGPH
]. To further support local malaria control programs, PIVOT aims to support the MoH to optimize interventions geographically in a context of heterogeneous disease burdens.Data was obtained from health center registers on all individuals who visited a public health center for an outpatient consultation in Ifanadiana district between January 2014 and December 2017.
Finally, we used a geographic information system containing data on locations of all health centers, more than 20,000 km of footpaths, over 100,000 buildings, and nearly 5,000 residential areas in the district. This was obtained following a participatory complete mapping of Ifanadiana in 2018–2019, from very high resolution satellite images available through OpenStreetMap [
]. This data was queried on QGIS via the QuickOSM plugin and was used to estimate shortest path distances between health centers and each Fokontany.Patient-level information from each health center was aggregated to estimate per capita utilization rates and malaria incidence per month for each Fokontany in Ifanadiana district. Each Fokontany was then matched with its nearest health center.
A simplified benchmark multiplier method was used to adjust malaria incidence with a health care utilization index produced from non-malaria patients. This method combines information about the known members of a target population with the proportion of the target population that appears in the benchmark []. The reciprocal of the proportion is called the multiplier. The true size of the target population is estimated as the product of the benchmark and the multiplier.
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