Spatio-temporal modelling of the first Chikungunya epidemic in an intra-urban setting: The role of socioeconomic status, environment and temperature

Three key elements are the drivers of Aedes-borne disease: mosquito infestation, virus circulating, and susceptible human population. However, information on these aspects is not easily available in low- and middle-income countries. We analysed data on factors that influence one or more of those elements to study the first chikungunya epidemic in Rio de Janeiro city in 2016. Using spatio-temporal models, under the Bayesian framework, we estimated the association of those factors with chikungunya reported cases by neighbourhood and week. To estimate the minimum temperature effect in a non-linear fashion, we used a transfer function considering an instantaneous effect and propagation of a proportion of such effect to future times. The sociodevelopment index and the proportion of green areas (areas with agriculture, swamps and shoals, tree and shrub cover, and woody-grass cover) were included in the model with time-varying coefficients, allowing us to explore how their associations with the number of cases change throughout the epidemic. There were 13627 chikungunya cases in the study period. The sociodevelopment index presented the strongest association, inversely related to the risk of cases. Such association was more pronounced in the first weeks, indicating that socioeconomically vulnerable neighbourhoods were affected first and hardest by the epidemic. The proportion of green areas effect was null for most weeks. The temperature was directly associated with the risk of chikungunya for most neighbourhoods, with different decaying patterns. The temperature effect persisted longer where the epidemic was concentrated. In such locations, interventions should be designed to be continuous and to work in the long term. We observed that the role of the covariates changes over time. Therefore, time-varying coefficients should be widely incorporated when modelling Aedes-borne diseases. Our model contributed to the understanding of the spatio-temporal dynamics of an urban Aedes-borne disease introduction in a tropical metropolitan city.Author summary: Viruses transmitted by the Aedes mosquitoes represent a major public health concern. With the abundance of the mosquito and susceptible human population, the entry of new Aedes-transmitted viruses brings the risk of large epidemics. The first-ever chikungunya epidemic in Rio de Janeiro city, Brazil, happened in 2016. We used information neighbourhood information on the environment, socioeconomic status, and weekly temperature, to study the disease spread within the city. Our results show that better socioeconomic status plays a major role in preventing the disease, with poorer areas being affected first and harder by the epidemic. This highlights that improving sanitary and socioeconomic conditions is essential for Aedes-borne diseases prevention and control. The temperature increased the risk of chikungunya cases, and this effect persisted for longer in areas where the epidemic was concentrated. This indicates that interventions should be designed to be long-lasting in such locations. Our results contribute to understanding better the dynamics of a first urban Aedes-borne disease epidemic in a tropical metropolitan city, with the potential to help design better interventions for disease prevention and control.