Along with advances in understanding the biological cycle of DENV, numerous alternatives for prevention and combating the virus in the public health scenario were conceived. However, data about its social determinants in the national context are conflicting and still remain obscure. Recognizing circumstances that relate to dengue morbidity is relevant in the context of public administration, in which resources are finite. Therefore, identifying such variables may direct the use of resources and the creation of intervention plans aimed at these indicators. This work aims to explore the relationship between dengue morbidity and social, economic, demographic, and spatial indicators in municipalities of the State of São Paulo. This is an ecological study that evaluated 640 municipalities of the State of São Paulo regarding dengue incidence in 2019 and 37 variables, selected in order to represent the demographic, social, economic, and spatial spheres of each location. This information was obtained from public federal and state databases. Initially, the Pearson Coefficient (PC) between dengue incidence and the 37 variables was determined, followed by multiple linear regression analysis (ARLM) with those that showed association, in order to generate a prediction model for dengue incidence. Among the 37 variables listed, only 6 presented an isolated statistically significant relationship with dengue incidence: households with tree cover in the surroundings (PC +0.41), number of people per household (PC -0.36), households with a private motorcycle (PC +0.31), households with a storm drain/manhole in the surroundings (PC -0.22), per capita water consumption (PC +0.22), and economically active population (PC +0.23). The ARLM with these 6 variables resulted in a significant model, F(6, 296)=22.167; p<0.001; R=0.557, capable of explaining 30% of the variation in dengue incidence. Taken together, the results indicate that certain conditions previously strongly associated with dengue, such as water supply, garbage disposal, and sewage system, do not show a relationship with its morbidity. Furthermore, those variables that were associated, together explain only 30% of the incidence rate. These findings highlight the importance of considering the plurality of factors involved in disease morbidity during the discussion of interventions in the public health field.
Bastos et al. (Sun,) studied this question.