Modelling the prevalence of some zoonotic diseases among farmers in Benue state using Poisson Autoregessive model - Fater-Mtomga, Fater-Mtomga Iveren Blessing; Kuhe, David Adugh; Ogwuche, Innocent Otache (Journal of Statistical Modeling and Analytics (JOSMA), 2025)
The aim of this work is to model the infection rates of some infectious diseases among farmers in Benue state using Poisson autoregressive model. The study utilizes monthly secondary data on serologically confirmed infection cases of Human Immunodeficiency Virus (HIV), tuberculosis (TB), and viral hepatitis (VHP)—the data span from January 2010 to December 2022. The study employs summary statistics and the Anderson-Darling normality test, time plots, bar graphs, and the Poisson autoregressive model as the principal methods of investigation. Results show that HIV, TB, and VHP have positive and increasing trends over time with non-Gaussian tendencies. All three infections peaked between 2017 and 2019 and had their lowest occurrence in 2010, indicating a potential common relationship among them. The results of the PAR (1) model indicate positive time trends in the HIV, TB, and VHP infection rates, suggesting that infections are increasing over time. The results further revealed a significant monthly increase of 2.25% in HIV, 1.22% in TB, and 12.08% in VHP respectively over the study period. The coefficient of determinations of the models explained 83.3%, 78.8%, and 80.8% of the variability in the HIV, TB, and VHP data indicating better fit for all the fitted models. The positive time trend suggests that monitoring the infection rates over time is crucial. Public health strategies need to account for this increasing trend and aim to reverse it.