Unpacking Ross River virus trends in Queensland: Regional insights and predictive modeling

Abstract

Ross River virus (RRV) transmission cycle varies across Queensland, Australia. Identifying key exposures associated with regional RRV incidence can aid disease prevention and control. Using RRV notification data from 2001 to 2020, we developed negative binomial generalized linear models to predict RRV incidence across three Queensland regions categorized by thermal climate zones (Hot, Warm, and Dry). Predictors and RRV trends differed across regions, indicating unique transmission patterns: seasonally driven in the Hot region, outbreak driven in the Warm region, and a mixed transmission pattern in the Dry region. The important predictors included recent RRV cases, normalized difference vegetation index (vegetation cover density), accessibility/remoteness index of Australia scores (indicating remoteness), and land use proportions. These findings enhance the understanding of local RRV transmission dynamics, highlight primary environmental drivers of transmission, and inform targeted disease management strategies. This approach may also benefit studies on other vector-borne diseases with complex transmission cycles in varying environments and climates.