Abstract
Eastern African countries rank in the top ten most highly infected nations globally. To shed light on this, therefore this study investigated the impact of population dynamics on Human Immunodeficiency Virus (HIV) prevalence using a two-stage residual inclusion (2SRI) regression model to address potential endogeneity. The Hausman Test confirmed endogeneity among the variables, justifying the 2SRI model's application. Key findings indicate that population growth rate, fertility rate, and the population aged 15-64 significantly and positively affect Human Immunodeficiency Virus (HIV) prevalence. The instrumental variable, Children ages 0 to 14 young individual infected by HIV, 15 to 24 newly affected by Human Immunodeficiency Virus (HIV), and Children 0 to 14 living with Human Immunodeficiency Virus (HIV), was validated for strength, demonstrating robustness against weak instrument issues. Results revealed that a 1% increase in population growth rate leads to a 53% increase in Human Immunodeficiency Virus (HIV) prevalence. Additionally, the Dumitrescu & Hurlin Granger non-causality test established that population growth rate Granger causes Human Immunodeficiency Virus (HIV) prevalence. These findings underscore the critical role of demographic factors in shaping Human Immunodeficiency Virus (HIV) prevalence and highlight the necessity for targeted public health interventions to manage and reduce Human Immunodeficiency Virus (HIV) prevalence effectively.
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