Abstract: The need to study the spatial pattern of malaria prevalence and vulnerability emanates from the fact that malaria prevalence is not evenly distributed in any geographical area but heavily depends on the prevailing of both environmental and socioeconomic factors. Multi-Criteria Decision Analysis (MCDA) and geospatial techniques were employed in this study to assess the vulnerable areas to malaria occurrence [based on suitable breeding sites for mosquitoes] in Borno State. Seven environmental factors [rainfall, temperature and humidity [climatic factors, obtained online] as well as relief, water body and slope [processed from ASTERDEM data] and vegetation which was generated from Landsat Imageries of 2020 were used. The seven criteria were processed and integrated to model malaria vulnerable areas in the state. Reported cases of malaria in each of the Local Government Areas (LGAs) in the state during the periods [2011-2013 and 2016-2018] were also obtained from the Epidemiological unit of Borno State Ministry of Health for the determination of malaria reported cases and prevalence among the LGAs. The results were analyzed based on the three ecological zones in the State. The study revealed that vulnerable land area to malaria decreases from Guinea Savannah in the south through Sudan Savannah at the central to Sahel Savannah in the North. The spatial pattern of the malaria vulnerability was found to be the same pattern with the number of reported cases and the pattern of malaria prevalence in the State. This similar pattern shows the reliability of the generated malaria vulnerability map. Lake Chad, Jere bowl and the valleys of major rivers like Komadougou-Yobe and Hawul with dense vegetation and water body which are more suitable to the breeding of mosquitoes were found to be more vulnerable to malaria occurrence than the dry land areas. High relief areas like Biu Plateau and Gwoza hills with cooler temperature and scanty vegetation are less vulnerable. It was recommended that the use of online climatic data should be encouraged because of its wider coverage, up-to-date and reliability, while digital mapping for malaria vulnerability assessment should be embraced for generation of quick, consistent, good visual impression and reliable malaria vulnerability maps.
Key words: Borno State, Ecological Zones, Geospatial techniques, Malaria vulnerability, Multi-Criteria Decision Analysis.