Temporal trends of dengue cases and deaths from 2007 to 2020 in Belo Horizonte, Brazil.

Dengue, a disease with multifactorial determinants, is linked to population susceptibility to circulating viruses and the extent of vector infestation. This study aimed to analyze the temporal trends of dengue cases and deaths in Belo Horizonte, Minas Gerais, Brazil, from 2007 to 2020. Data from the Notifiable Diseases Information System (Sinan) were utilized for the investigation. To assess the disease's progression over the study period and predict its future incidence, time series analyses were conducted using a generalized additive model (GAM) and a seasonal autoregressive integrated moving average (SARIMA) model. Over the study period, a total of 463,566 dengue cases and 125 deaths were reported. Notably, there was an increase in severe cases and deaths, marking hyperendemics characterized by simultaneous virus circulation (79.17% in 2016-50% in 2019). The generalized additive model revealed a non-linear pattern with epidemic peaks in 2010, 2013, 2016, and 2019, indicating an explosive pattern of dengue incidence. The SARIMA (3,1,1) (0,0,0)12 model was validated for each year (2015 to 2019). Comparing the actual and predicted numbers of dengue cases, the model demonstrated its effectiveness for predicting cases in the municipality. The rising number of dengue cases emphasizes the importance of vector surveillance and control. Enhanced models and predictions by local health services will aid in anticipating necessary control measures to combat future epidemics.

Disentangling associations between vegetation greenness and dengue in a Latin American city: Findings and challenges.

Being a Re-Emerging Infectious Disease, dengue causes 390 million cases globally and is prevalent in many urban areas in South America. Understanding the fine-scale relationships between dengue incidence and environmental and socioeconomic factors can guide improved disease prevention strategies. This ecological study examines the association between dengue incidence and satellite-based vegetation greenness in 3826 census tracts nested in 474 neighborhoods in Belo Horizonte, Brazil, during the 2010 dengue epidemic. To reduce potential bias in the estimated dengue-greenness association, we adjusted for socioeconomic vulnerability, population density, building height and density, land cover composition, elevation, weather patterns, and neighborhood random effects. We found that vegetation greenness was negatively associated with dengue incidence in a univariate model, and this association attenuated after controlling for additional covariates. The dengue-greenness association was modified by socioeconomic vulnerability: while a positive association was observed in the least vulnerable census tracts, the association was negative in the most vulnerable areas. Using greenness as a proxy for vegetation quality, our results show the potential of vegetation management in reducing dengue incidence, particularly in socioeconomically vulnerable areas. We also discuss the role of water infrastructure, sanitation services, and tree cover in lowering dengue risk.

Twenty-Two years of dengue fever (1996-2017): an epidemiological study in a Brazilian city.

This ecological study analyzed the temporal pattern of clinically diagnosed and laboratory confirmed dengue cases in Belo Horizonte, Minas Gerais, Brazil from 1996 to 2017. The study was divided into two analytical parts, the first of which evaluated the association between dengue incidence and host and climatic factors. The second part encompassed data from 2002 to 2017 and examined dengue incidence in relation to virus serotype and an intra-urban socioeconomic index. Over 22 years there were 469,171 cases and four epidemic peaks. There was an increase in the number, severity, and lethality of cases over the last 10 years of the study period. Biological and environmental factors appear to modulate the behavior of dengue in a large urban center.

Spatial analysis of dengue incidence and Aedes aegypti ovitrap surveillance in Belo Horizonte, Brazil.

OBJECTIVES: Understanding the intra-urban spatial dynamics of Aedes aegypti and dengue transmission is important to effectively guide vector control. Ovitraps are a sensitive, cost-effective vector surveillance tool, yet few longitudinal studies have evaluated ovitrap indices and dengue occurrence. We aimed to assess the spatial patterns of dengue incidence and Ae. aegypti ovitrap positivity index (OPI) over time and to examine the spatial relationship between these two variables. METHODS: This study used 12 years (2007-2018) of dengue case records and biweekly Ae. aegypti ovitrap data in Belo Horizonte, Brazil. We aggregated data by year and health centre catchment area (n = 152) and used both univariate and bivariate global Moran's I statistic and LISA to evaluate spatial clustering. RESULTS: Annual dengue incidence ranged from 18 to 6262/100 000 residents and displayed spatial autocorrelation in 10/12 years, with shifting areas of high incidence. Annual OPI ranged from 35.7 to 47.6% and was clustered in all study years, but unlike dengue had consistent spatial patterns over time. Bivariate analysis found both positive (6/12 years) and negative (1/12 years) spatial associations between the two variables. CONCLUSIONS: Low detected presence of Ae. aegypti was not a limiting factor in dengue transmission. However, stable spatial distribution of OPI suggests that certain areas may have persistent breeding sites. Future research should identify factors related to persistent Ae. aegypti hotspots to better guide vector management. Vector control efforts should be paired with additional data on population immunity, circulating serotypes and urban factors to better predict and control outbreaks.

OBJECTIFS: La compréhension de la dynamique spatiale intra-urbaine d'Aedes aegypti et de la transmission de la dengue est importante pour guider efficacement la lutte antivectorielle. Les ovitraps sont un outil de surveillance des vecteurs sensible et rentable, mais peu d'études longitudinales ont évalué les indices d'ovitrap et l'occurrence de la dengue. Nous visions à évaluer les modèles spatiaux de l'incidence de la dengue et de l'indice de positivité d'ovitrap (OPI) d'Ae. aegypti au fil du temps, et à examiner la relation spatiale entre ces deux variables. MÉTHODES: Cette étude a utilisé des dossiers de cas de dengue et des données bihebdomadaires d'ovitrap Ae. aegypti sur 12 ans (2007-2018) à Belo Horizonte, au Brésil. Nous avons agrégé les données par année et par zone d'étude du centre de santé (n = 152) et avons utilisé à la fois la statistique I globale de Moran univariée et bivariée et LISA pour évaluer le regroupement spatial. RÉSULTATS: L'incidence annuelle de la dengue variait de 18 à 6.262/100.000 habitants et affichait une autocorrélation spatiale en 10/12 ans, avec des zones de déplacement de forte incidence. L'OPI annuel variait de 35,7 à 47,6% et était groupé dans toutes les années d'étude, mais contrairement à la dengue, il avait des modèles spatiaux consistents au fil du temps. Une analyse bivariée a trouvé des associations spatiales positives (6/12 ans) et négatives (1/12 ans) entre les deux variables. CONCLUSIONS: La détection d'une faible présence d'Ae. aegypti n'était pas un facteur limitant de la transmission de la dengue. Cependant, la distribution spatiale stable de l'OPI suggère que certaines zones peuvent avoir des sites de reproduction persistants. Les recherches futures devraient identifier les facteurs liés à des hotspots persistants d'Ae. aegypti pour mieux guider la gestion des vecteurs. Les efforts de lutte antivectorielle devraient être associés à des données supplémentaires sur l'immunité de la population, les sérotypes circulants et les facteurs urbains pour mieux prévoir et contrôler les flambées.