Mapping Risk of Malaria as a Function of Anthropic and Environmental Conditions in Sussundenga Village, Mozambique

Abstract

Mozambique is a country in Southern Africa with around 30 million inhabitants. Malaria is the leading cause of mortality in the country. According to the WHO, Mozambique has the third highest number of malaria cases in the world, representing approximately 5% of the world total cases. Sussundenga District has the highest incidence in the Manica province and environmental conditions are the major contributor to malaria transmission. There is a lack of malaria risk maps to inform transmission dynamics in Sussundenga village. This study develops a malaria risk map for Sussundenga Village in Mozambique and identifies high risk areas to inform on appropriate malaria control and eradication efforts. One hundred houses were randomly sampled and tested for malaria in Sussundenga Rural Municipality. To construct the map, a spatial conceptual model was used to estimate risk areas using ten environmental and anthropic factors. Data from Worldclim, 30 × 30 Landsat images were used, and layers were produced in a raster data set. Layers between class values were compared by assigning numerical values to the classes within each layer of the map with equal rank. Data set input was classified, using diverse weights depending on their appropriateness. The reclassified data outputs were combined after reclassification. The map indicated a high risk for malaria in the northeast and southeast, that is, the neighborhoods of Nhamazara, Nhamarenza, and Unidade. The central eastern areas, that is, 25 de Junho, 1 and 2, 7 de Abril, and Chicueu presented a moderate risk. In Sussundenga village there was 92% moderate and 8% high risk. High malaria risk areas are most often located in densely populated areas and areas close to water bodies. The relevant findings of this study can inform on effective malaria interventions.

Mapping of Malaria Risk Related to Climatic and Environmental Factors by Multicriteria Analysis in the Marahoué Region of Côte d’Ivoire

“…This result confirms the work of Ferrão et al (2021) show that there is a 15-day lag between the increase in NDVI and the increase in malaria incidence, which is explained by the duration of the development of Anopheles larvae. With respect to altitude, the results show that this parameter influences the risk of malaria (Sahondra et al, 2001).…”

“…With respect to altitude, the results show that this parameter influences the risk of malaria (Sahondra et al, 2001). Water points and market gardening areas maintain moisture for vector survival and transmission even in dry season (Martiny et al, 2012;Ferrão et al, 2021). This risk could be due to land use types (Ferrão et al, 2021).…”

“…Water points and market gardening areas maintain moisture for vector survival and transmission even in dry season (Martiny et al, 2012;Ferrão et al, 2021). This risk could be due to land use types (Ferrão et al, 2021). Indeed, the land use map shows that more than half of the region is occupied by crops and fallow.…”

“…And the density of vector aggressiveness is very high after the pricking of young rice shoots (Dossou-Yovo et al, 1998). Rainfall, relative humidity, temperatures (min and max), elevation, NDVI, NDWI, population density, land use, and distance to permanent water points are significant variables in predicting malaria risk (Dansou & Odoulami, 2015;Ferrão et al, 2021;Zewga, 2021). This method prioritizes malaria control based on climate, remote sensing, and mapping data.…”

“…These data are the factors that favor malaria transmission and the proliferation of malaria mosquito breeding sites (Guerra et al, 2008;Gething et al, 2011). Studies (Hay et al, 2009;Ferrão et al, 2021) have used mean temperature sometimes with precipitation and/or humidity to develop maps representing spatiotemporal variation in malaria transmission risk. The approach consists of classification and standardization of criteria, weighting of criteria and aggregation following the multi-criteria approach (Jourda et al, 2006;Koudou et al, 2013).…”