Space-time conditional autoregressive modeling to estimate neighborhood-level risks for dengue fever in Cali, Colombia [article]

Michael Richard Desjardins, Matthew D Eastin, Rajib Paul, Irene Casas, Eric M Delmelle
2020 biorxiv/medrxiv   pre-print
Vector-borne diseases (VBDs) affect more than 1 billion people a year worldwide, cause over 1 million deaths, and cost hundreds of billions of dollars in societal costs. Mosquitoes are the most common vectors, responsible for transmitting a variety of arboviruses. Dengue fever (DENF) has been responsible for nearly 400 million infections annually. Dengue fever is primarily transmitted by female Aedes aegypti and Aedes albopictus mosquitoes. Since both Aedes species are peri-domestic and
more » ... omestic and container-breeding mosquitoes, dengue surveillance should begin at the local level - where a variety of local factors may increase the risk of transmission. Dengue has been endemic in Colombia for decades and is notably hyperendemic in the city of Cali. For this study, we use weekly cases of DENF in Cali, Colombia from 2015-2016; and develop space-time conditional autoregressive models to quantify how DENF risk is influenced by socioeconomic, environmental, and accessibility risk factors, and lagged weather variables. Our models identify high-risk neighborhoods for DENF throughout Cali. Statistical inference is drawn under Bayesian paradigm using Markov Chain Monte Carlo techniques. The results provide detailed insight about the spatial heterogeneity of DENF risk and the associated risk factors (such as weather, proximity to Aedes habitats, and socioeconomic classification) at a fine-level, informing public health officials to motivate at-risk neighborhoods to take an active role in vector surveillance and control, and improving educational and surveillance resources throughout the city of Cali.
doi:10.1101/2020.06.20.20136226 fatcat:iiqshgupjne23avlh37uwmknha