Risk factors for arbovirus infections in a low-income community of Rio de Janeiro, Brazil, 2015-2016.

BACKGROUND: Dengue epidemics have occurred in the city of Rio de Janeiro (Brazil) since 1986. In the year 2015, Zika and chikungunya viruses were introduced in the city, causing sequential and simultaneous epidemics. Poor socioeconomic conditions have been suggested as contributing factors of arboviral infection. OBJECTIVE: To describe the spatial distribution of human cases of symptomatic arboviral infections and to identify risk factors for infection in a poor community of Rio de Janeiro in the years 2015 and 2016. METHODS: We built thematic maps of incidence rates for 78 micro-areas in the Manguinhos neighborhood. The micro-areas congregate about 600 inhabitants. Simple and multiple multilevel logistic regression models were used to evaluate the association between the incidence of arboviral diseases and socio-demographic factors at both the individual and micro-area levels. RESULTS: From 2015 to 2016, 370 human cases of arbovirus infection were reported in the Manguinhos community: 123 in 2015 and 247 in 2016. There was a significant difference in the risk of arbovirus diseases among different micro-areas, but this was not explained by water and sanitation indicators. The cumulative incidence rate was 849/100,000 in two years. The incidence was greater in those individuals with familiar vulnerability (1,156/100,000 vs. 794/100,000). The multilevel adjusted model showed that the odds of acquiring an arbovirus infection was 55% greater in those with familiar vulnerability. CONCLUSION: Arbovirus infections cause a high burden of disease in Brazilian urban centers. Our results suggest that even in poor neighborhoods, there is a high spatial variability in the risk of acquiring an arbovirus infection. The conditions that favor vector proliferation and infection by arboviruses are complex and involve both individual and environmental characteristics that vary from place to place. To reduce the burden of arboviral diseases, continued public health policies and basic services should be provided to the communities at risk that consider specific local needs.

Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system.

BACKGROUND: We identified dengue transmission areas by using the Geographic Information Systems located at local surveillance units of the Itaboraí municipality in state of Rio de Janeiro. We considered the association among the house infestation index, the disease incidence, and sociodemographic indicators during a prominent dengue outbreak in 2007 and 2008. METHODS: In this ecological study, the Local Surveillance Units (UVLs) of the municipality were used as spatial pattern units. For the house analysis, we used the period of higher vector density that occurred previous to the larger magnitude epidemic range of dengue cases. The average dengue incidence rates calculated in this epidemic range were smoothed using the Bayesian method. The associations among the House Infestation Index (HI), the Bayesian rate of the average dengue incidence, and the sociodemographic indicators were evaluated using a Pearson's correlation coefficient. The areas that were at a higher risk of dengue occurrence were detected using a kernel density estimation with the kernel quartic function. RESULTS: The dengue transmission pattern in Itaboraí showed that the increase in the vector density preceded the increase in incidence. The HI was positively correlated to the Bayesian dengue incidence rate (r = 0.641; p = 0.01). The higher risk areas were those that were close to the main highways. In the Kernel density estimation analysis, we observed that the regions that were at a higher risk of dengue were those that were located in the UVLs and had the highest population densities; these locations were typically located along major highways. Four nuclei were identified as epicenters of high risk. CONCLUSIONS: The spatial analysis units used in this research, i.e., UVLs, served as a methodological resource for examining the compatibility of different information sources concerning the disease, the vector indices, and the municipal sociodemographic aspects and were arranged in distinct cartographic bases. Dengue is a multi-scale geographic phenomenon, and using the UVLs as analysis units made it possible to differentiate the dengue occurrence throughout the municipality. The methodological approach used in this research helped improve the Itaboraí municipality monitoring activities and the local territorial monitoring in other municipalities that are affected by this public health issue.