Climate-Driven Shifts in Dengue Epidemiology A Multilayered Analysis of Transmission Dynamics and Future Risk in Mauritius 2nd edition

This study examines the dynamics between climate change and dengue epidemiology in Mauritius, a Small Island Developing State (SIDS) in the Indian Ocean. The research combines climate, epidemiology, entomology, and advanced statistical modeling to identify key drivers and transmission dynamics of dengue transmission in a changing climate and socio-ecological context using a multidisciplinary approach. The analyses show enormous increases in mean annual temperature, changes in precipitation patterns, and sea surface temperatures, which are all known to affect mosquito population dynamics and dengue incidence. Spatiotemporal analyses reveal a significant inland shift of dengue hotspots in recent decades, corresponding to a changing vector habitat in response to rising temperatures and urbanization. Mid-range climate change scenarios predict that climatically suitable habitats for Aedes mosquitoes will expand by 2050 in mid-elevation zones. The latter projection suggests that dengue transmission will increase substantially in high-risk areas, increasing the proportion of the population at risk of sustained dengue outbreaks. The study notes that urban density, water storage practices and the resulting economic inequalities are shown to be key drivers of dengue risk. These burden areas tend to be areas lacking in proper infrastructure and have lower socio-economic status and that compound public health challenges. Existing intervention strategies such as community-based vector control, improvement in diagnostic tools and new approaches of Wolbachia-infected mosquito releases are evaluated. While some measures achieve localized success, lack of implementation gaps and lack of resource allocation equitability impede their overall efficacy. Non-linear and lagged effects of climatic variables on dengue transmission as modeled by advanced statistical models, including machine learning algorithms and Bayesian frameworks. Finally, these models are integrated with climate projections into high-resolution risk maps that inform actionable interventions. The results emphasize the need to integrate climate adaptation approaches into public health policies, especially for SIDS at high risk from climate impacts. This study is a useful reference for policymakers of Mauritius and other contexts for developing a robust approach to addressing the problems caused by climate-sensitive vector-borne diseases. It bridges disciplines and uses innovative methodologies to improve our understanding of climate-driven health risks and to highlight the importance of coordinated, sustainable disease prevention and climate resilience approaches.