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

Abstract

Background Dengue 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. Methods This 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. Results During 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. Conclusions In 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.

Are Land Use and Cover Changes and Socioeconomic Factors Associated with the Occurrence of Dengue Fever? A Case Study in Minas Gerais State, Brazil

“…As in the case of deforestation, studies carried out in Brazil have not shown a consistent pattern regarding which socioeconomic factors most strongly influence the number of dengue cases. However, this disease is usually positively affected by a high inequality in income distribution and low education [67,[72][73][74]. Despite this, Morais [66] found a greater number of cases in municipalities with a higher GDP in the Atlantic Forest of Minas Gerais, suggesting that, often, even richer municipalities do not prioritize basic sanitation and health care.…”

Land Use and Cover Changes and the Occurrence of Dengue Fever in Minas Gerais State, Brazil: Governing Deforestation for Public Health

“…As in the case of deforestation, studies carried out in Brazil have not shown a consistent pattern regarding which socioeconomic factors most strongly influence the number of dengue cases. However, this disease is usually positively affected by high inequality in income distribution and low education (ALVES 2015, CARMO et al 2020, SOUSA et al 2021, COUTINHO et al 2022. Despite this, Morais (2011) found a greater number of cases in municipalities with higher GDP in the Atlantic Forest of Minas Gerais, suggesting that, often, even richer municipalities do not prioritize basic sanitation and health care.…”

Analysis of the correlation between climatic variables and Dengue cases in the city of Alagoinhas/BA

“…The transmitting agent is the female Aedes aegypti mosquito, and its transmission occurs through its bite, passing the virus to the host. The individual may develop the disease or not 4 . Dengue affects thousands of people each year in several countries, including Brazil and other regions of Latin America 5 – 7 .…”

“…The epidemiological situation of dengue in Brazil and Latin America is complex and challenging, as the disease is endemic in many areas and transmission can be influenced by factors such as climate change, urbanization and population migration 2 . Dengue control requires a multifaceted approach that involves prevention measures, early detection and adequate treatment of cases, thus understanding how climate variations affect this transmission is of paramount importance for understanding the vectors 4 , 10 .…”