Role of Genomic, Economic, and Demographic Disparities in Mpox Epidemic in Africa: A Retrospective Cross-Country Analysis

To investigate the role of epidemic predictors in the mpox outbreak in Africa. This was a retrospective analysis of national-level mpox surveillance data from 20 mpox-affected African countries from January through December 2024. Predictors included viral clades, gross domestic product (GDP) per capita, and population density. A negative binomial regression model estimated the incidence rates ratio (IRR) [95% confidence interval] for mpox incidence and mortality. Random forest models assessed the influence of each predictor in the epidemic dynamic. Clade II was associated with lower mpox incidence (IRR = 0.15 [0.02-0.97]) and mortality (IRR = 0.09 [0.01-1.72]) compared to Clade I. GDP per capita was associated with a 95% reduction in cases count per US $1000 (IRR = 0.05 [0.38-0.74]). Population density was not significantly associated with mpox incidence or mortality. Random forest analysis confirmed GDP per capita as the strongest predictor of mpox burden. The 2024 mpox epidemic highlights how countries with low GDP per capita and Clade I face greater outbreak burdens. Strengthening health systems and addressing poverty as a key social determinant of health through a multisectoral approach are essential to ensure equitable outbreak prevention, control, and long-term resilience.