Spatial Identification of high-risk level of HIV/AIDS in Karu LGA using spatial Autocorrelation and Kriging interpolation

Abstract

To appropriately serve humanity better, the need to distribute the limited resources correctly to the needed persons and location remain nonnegotiable in our present dispensation. Indeed, it became very expedient to sort for means of allocating these minimum resources to the needy against all odds. The study seeks to identify communities with severe cases of HIV virus across Karu Local Government Area of Nasarawa State and communities at high risk of HIV/AIDS. The study used secondary data from the Karu Medical center Mararaba, which covered a period of ten (10) years, from 2013 to 2023. The study used Moran’s I Statistics, Kriging Model and Semivariogram model, and ArcGIS software was used to analyzed the data. The finding shows that the Moran’s I statistics recorded a positive value of 0.026684, z-score of 5.880192 and p-value 0.0000 which is statistically significant. The spatial autocorrelation flattens out at 0.817 by the semivariogram and Kriging model predicts communities at high risk of HIV/AIDS. This study conclude that resources should be allocated to the identified communities and alongside intervention program such as campaign programs and medical outreach to stop further prevalence of this virus.