Identification of risk areas for arboviruses transmitted by Aedes aegypti in northern Brazil: A One Health analysis

Abstract

Introduction: The complex and growing problem generated by the rapid expansion of unplanned urban areas includes high population density and increased infestation by vectors responsible for the transmission of several diseases. This requires interdisciplinary and intersectoral interventions due to the burden of diseases, especially those caused by arboviruses, which can present severe forms and generate significant pressure on health systems, especially in more vulnerable regions. The objective of this study was to analyze the spatial distribution of arboviruses transmitted by Aedes aegypti (dengue, Zika, and chikungunya) and assess their correlations with demographic, social, and environmental data from the state of Tocantins, Brazil.

Methods: This was an ecological time series study of the dengue, Zika, and chikungunya arboviruses in the state of Tocantins. Local Moran's indices were used to observe the spatial autocorrelation of cases and to delimit clusters of high and low risks, correlating them with socioenvironmental indicators, in addition to analyses to detect case clusters.

Results: The state reported a mean incidence of 591 annual cases of arbovirus infections per 100,000 inhabitants and a stationary trend with seasonal pattern. Female Pardo individuals aged 20-39 years, with an education level of below college education, were the most affected; Palmas and Araguaína, the two largest cities in the state in terms of economy and population, were the most affected.

Conclusion: A better understanding of the interaction between social characteristics, the environment, and ecology of wild animals and vectors is important for the development of mechanisms to predict outbreaks as well as to develop strategies to reduce and/or mitigate recurring arboviral epidemics and other diseases.

Keywords: Arboviruses; Epidemiology; One health; Spatial analysis.

Fig. 1

The state of Tocantins, Brazil and health regions.

Fig. 2

Spatial distribution by the Kernel estimator of absolute cases and the mean incidence of arboviruses (2015–2019; TO, Brazil).

Fig. 3

Conditional maps of analyses of the level of correlation between socioeconomic factors and the incidence of arboviruses by city in the state of Tocantins (2015–2019).

Fig. 4

Conditional maps of analyses of the level of correlation between environmental factors and the incidence of arboviruses by city in the state of Tocantins (2015–2019).