Remote sensing of environmental risk factors for malaria in different geographic contexts

Abstract Background Despite global intervention efforts, malaria remains a major public health concern in many parts of the world. Understanding geographic variation in malaria patterns and their environmental determinants can support targeting of malaria control and development of elimination strategies. Methods We used remotely sensed environmental data to analyze the influences of environmental risk factors on malaria cases caused by Plasmodium falciparum and Plasmodium vivax from 2014 to 2017 in two geographic settings in Ethiopia. Geospatial datasets were derived from multiple sources and characterized climate, vegetation, land use, topography, and surface water. All data were summarized annually at the sub-district (kebele) level for each of the two study areas. We analyzed the associations between environmental data and malaria cases with Boosted Regression Tree (BRT) models. Results We found considerable spatial variation in malaria occurrence. Spectral indices related to land cover greenness (NDVI) and moisture (NDWI) showed negative associations with malaria, as the highest malaria rates were found in landscapes with low vegetation cover and moisture during the months that follow the rainy season. Climatic factors, including precipitation and land surface temperature, had positive associations with malaria. Settlement structure also played an important role, with different effects in the two study areas. Variables related to surface water, such as irrigated agriculture, wetlands, seasonally flooded waterbodies, and height above nearest drainage did not have strong influences on malaria. Conclusion We found different relationships between malaria and environmental conditions in two geographically distinctive areas. These results emphasize that studies of malaria-environmental relationships and predictive models of malaria occurrence should be context specific to account for such differences

Malaria case investigation with reactive focal testing and treatment: operational feasibility and lessons learned from low and moderate transmission areas in Amhara Region, Ethiopia

Abstract Background When malaria transmission is very low, investigation of passively detected malaria cases and reactive focal testing and treatment (FTAT) in the case and neighbouring households can identify and contain the source and spread of infections. Methods Case investigation with reactive FTAT for malaria was implemented in 10 villages in Amhara Region, Ethiopia during the 2014/2015 malaria transmission season. Intervention villages were purposively selected based on the incidence of passively detected Plasmodium falciparum and mixed infections (P. falciparum and Plasmodium vivax) during the 2013 transmission season. A passively detected P. falciparum or mixed index case triggered an investigation that targeted the index case household and the closest 10 neighbouring households in a 100-m radius. All consenting household members received a rapid diagnostic test (RDT) and RDT-positive individuals received artemether–lumefantrine (P. falciparum, mixed) or chloroquine (P. vivax). Results From October 2014 to February 2015, 407 P. falciparum or mixed index cases (approximately 6.5 per 1000 population) were passively detected. Of these, 220 (54.1%) were investigated, of which 87.3% were male, 61.8% were age 20–39 years [median age: 27 years (range 1–90)], and 58.6% spent ≥ 1 night away from home in the past month (ranging from 0.0 to 94.1% by village). Among the 4077 residents in the 914 households investigated, 3243 (79.5%) received an RDT and 127 (3.9%) were RDT-positive (2.2% P. falciparum, 0.5% P. vivax, 1.2% mixed). Three epidemiological patterns were found. In six villages, there were almost no cases, with less than 10 index and secondary cases. In three villages, most index cases had a history of travel (> 62%), but there were a small number of secondary cases (< 10). Lastly, in one village none of the index cases had a history of recent travel and there was a large number of secondary cases (n = 105). Conclusions Three types of malaria transmission patterns were observed: (1) low importation and low local transmission; (2) high importation and low local transmission; and, (3) low importation and high local transmission. To achieve malaria elimination in Amhara Region, intervention strategies targeting these different patterns of transmission and population movement are required