Temporal trend, space risk and factors associated with the occurrence of dengue in northeast Brazil, 2009–2018

• Published in: Transactions of the Royal Society of Tropical Medicine and Hygiene Vol. 116; no. 9; pp. 853 - 867
• Main Authors: Coutinho, Helder Silveira, Silva, Jhonathan Oliveira, Santana, Gibson Barros de Almeida, do Carmo, Rodrigo Feliciano, Souza, Sírius Oliveira, de Faria, Marcelo Domingues, Matos, Thais Silva, da Silva, Tarcísio Fulgêncio Alves, Bezerra-Santos, Márcio, de Souza, Carlos Dornels Freire
• Format: Journal Article
• Language: English
• Published: 10-09-2022
• ISSN: 0035-9203; 1878-3503
• DOI: 10.1093/trstmh/trac027

BACKGROUNDDengue is an acute viral disease of major relevance and impact on public health, causing major epidemics around the world, especially in tropical regions. Here we aimed to analyse the temporal trend and spatial risk, as well as social vulnerability factors, associated with the occurrence of dengue in the state of Bahia, Brazil between 2009 and 2018. METHODSThis is an ecological study carried out with all suspected cases of dengue in Bahia between 2009 and 2018. The data were obtained from the National Notifiable Diseases Information System, available on the website of the Health Department of the State of Bahia, and from the Brazilian Institute of Geography and Statistics. We used the Joinpoint regression model, local empirical Bayesian model for smoothing, global and local Moran statistics and spatial scanning statistics. The relationship between the dengue incidence rate and social determinants was tested using Moran's bivariate correlation. RESULTSDuring the study period, 451 847 probable dengue cases were registered in Bahia. A declining trend was observed in 39.28% (n=11) of the state's health regions and 60.71% (n=17) showed a stationary tendency. The spatiotemporal scanning statistic showed nine clusters of dengue occurrence. The largest cluster had a radius of 342.14 km, consisting of 160 municipalities, 120 094 cases (710.20 cases/100 000 inhabitants) and a relative risk of 2.80. In the multivariate regression model, 11 variables showed a significant association: Social Vulnerability Index (SVI), Municipal Human Development Index (MHDI), SVI urban infrastructure, SVI human capital, MHDI longevity, MHDI education, proportion of people living in households with per capita income less than half the minimum wage (in 2010) and who spend more than 1 h commuting, proportion of mothers who are heads of household who did not complete elementary school and with children <15 y of age, activity rate of persons ages 10-14 y and per capita income. CONCLUSIONSIn the analysis of the spatial distribution, areas of risk of disease transmission throughout the state were identified. These results can provide subsidies for the strategic planning of actions, as well as for the implementation of programs and/or public policies in order to control the incidence of dengue in the population.