| Journal: | Revista do Instituto de Medicina Tropical de Sao Paulo |
| Database: | |
| System number: | 000537151 |
| ISSN: | 0036-4665 |
| Authors: | Vernal, Sebastian1 Nahas, Andressa K.2 Chiaravalloti Neto, Francisco2 Prete Junior, Carlos A.3 Cortez, André L.1 Sabino, Ester Cerdeira4 Luna, Expedito José de Albuquerque4 |
| Institutions: | 1Universidade de São Paulo, Faculdade de Medicina, São Paulo, São Paulo. Brasil 2Universidade de São Paulo, Faculdade de Saúde Pública, São Paulo, São Paulo. Brasil 3Universidade de São Paulo, Escola Politécnica, São Paulo, São Paulo. Brasil 4Universidade de São Paulo, Instituto de Medicina Tropical de São Paulo, São Paulo, São Paulo. Brasil |
| Year: | 2021 |
| Volumen: | 63 |
| Country: | Brasil |
| Language: | Inglés |
| English abstract | Dengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. “Hot spots” are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil. |
| Keyword: | Dengue, Arbovirus, Infectious diseases outbreak, Epidemiologic study, Spatiotemporal analysis |
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