YELLOW FEVER VULNERABILITY AND RISK PATTERN: A GEOSPATIAL ANALYSIS OF THE 2019 AND 2020 CASES IN BAUCHI STATE, NIGERIA

Bauchi has recently experienced yellow fever outbreak, it is therefore critical to look at the spatio-temporal pattern, vulnerability and risk factors for the disease. This was accomplished by first building a database of illness cases based on their location, and then utilizing IDW interpolation ArcGIS 10.3 software to create disease maps for the outbreak. Optimised hotspot analysis was used to identify the concentration of yellow fever cases in the local government areas within the study area, and spatial auto-correlation was utilized to determine the pattern of yellow fever spread. The factors aiding yellow fever spread (euclidean distance for monkeys, mosquitoes, and forest along with temperature, rainfall, altitude, and built-up) were assessed for vulnerability. To identify places sensitive to yellow fever within the research area, a multicriteria analysis was conducted using weighted sum overlay to integrate the yellow fever risk factors. Both the 2019 and 2020 outbreaks have a random pattern of spread, with Moran's Index values of -0.070041 and 0.074746, respectively. In 2019, the Alkaleri local government area was identified as a hotspot for yellow fever outbreaks, followed by Ganjuwa in 2020. The entire research area is at risk of yellow fever spread, according to the Multicriteria analysis. Bauchi State is threatened by the spread of yellow feveroutbreaks with more widespread in the southern part of the state. Because there is no known active antiviral treatment, the study suggests immunization and mitigating measures such as vector control as the options.