Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period

Author(s)

Vernal, Sebastian ^[1] ; Nahas, Andressa K. ^[2] ; Neto, Francisco Chiaravalloti ^[2] ; Prete Junior, Carlos A. ^[3] ; Cortez, Andre L. ^[1] ; Sabino, Ester Cerdeira ^[4] ; Luna, Expedito Jose de Albuquerque ^{[4, 5]}

Affiliation

^[1] Univ Sao Paulo, Dept Molestias Infecciosas & Parasitarias, Fac Med, Av Dr Eneas Carvalho Aguiar 647, BR-05403000 Sao Paulo, SP - Brazil

^[2] Univ Sao Paulo, Dept Epidemiol, Fac Saude Publ, Sao Paulo, SP - Brazil

^[3] Univ Sao Paulo, Dept Engn Sistemas Eletron, Escola Politec, Sao Paulo, SP - Brazil

^[4] Univ Sao Paulo, Inst Med Trop Sao Paulo, Sao Paulo, SP - Brazil

^[5] Univ Sao Paulo, Dept Med Prevent, Fac Med, Sao Paulo, SP - Brazil

• Document type: Journal article
• Source: Revista do Instituto de Medicina Tropical de São Paulo; v. 63, 2021.
• Web of Science Citations: 0

Abstract

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. (AU)

• FAPESP's process: 18/14389-0 - Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology (CADDE)
• Grantee: Ester Cerdeira Sabino
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 19/21858-0 - Bayesian models for estimating the attack rate of epidemics
• Grantee: Carlos Augusto Prete Junior
• Support Opportunities: Scholarships in Brazil - Doctorate