In the last 40 years, Latin America countries, including Brazil, have suffered from the emergence and reemergence of arboviruses, first Dengue (DENV) and recently Zika (ZIKV) and Chikungunya (CHIKV). All three arboviruses are currently endemic in Brazil and have caused major outbreaks in recent years. Rio de Janeiro city, host of the last Summer Olympic Games and the Football World Cup, has been specially affected by them. A surveillance system based on symptomatic reports is in place in Rio, but the true number of affected individuals is unknown due to the great number of Zika, Dengue and Chikungunya asymptomatic cases. Seroprevalence studies are more suitable to evaluate the real number of cases in a given population. We performed a populational seroprevalence survey in Rio, with recruitment of a sample of volunteers of all ages and gender from July to October 2018, within randomly selected census tracts and household. A total of 2,120 volunteers were interviewed and tested with rapid immunochromatographic test for ZIKV, DENV and CHIKV. Individuals with positive results for IgG and/or IgM from only one virus were classified accordingly, while those with test results positive for both ZIKV and DENV were classified as flaviviruses. We corrected for sample design and non-response in data analysis, and calculated point estimate prevalence and 95% confidence intervals for each virus. Arbovirus prevalence in the Rio's population (n = 6,688,927) was estimated at 48.6% [95% CI 44.8–52.4] (n = 3,254,121) for flaviviruses and at 18.0% [95% CI 14.8–21.2] (n = 1,204,765) for CHIKV. Approximately 17.0% [95% CI 14.1–20.1] (n = 1,145,674) of Rio´s population had no contact with any of the three arboviruses. The reported cases of Zika, Dengue and Chikungunya by the current surveillance system in place is insufficient to estimate their real numbers, and our data indicate that Zika seroprevalence could be at least five times and Chikungunya 45 times bigger. The high number of individuals having never been infected by any of the three arboviruses, may indicate a proper scenario for future outbreaks.

Abstract: This research applies indicators concerning control of the visceral leishmaniasis canine reservoir in the city of Belo Horizonte, Minas Gerais State, Brazil. Data were obtained from the Zoonoses Control Information System (SCZOO) and the Brazilian Information System on Diseases of Notification (SINAN) database. First we analyzed (i) existing associations between canine epidemiological indicators, where the dependent variable was the canine seroprevalence A (2007 to 2013), and the independent variables were, as follows: canine seroprevalence B (2006 to 2012); percentage of positive dogs by ELISA test reagents that were not euthanized; the relationship between the human and canine population; canine population testing coverage by census surveys; and the years of study (2006 to 2013); (ii) then, we examined the association between human visceral leishmaniasis (HVL) cases between 2007 to 2013 and the mentioned variables related to dogs and years. Statistical analysis was done by a generalized linear model (GLM). One unit increases in canine seroprevalence B and canine seroprevalence A were associated to 13% and 12% increases in HVL rates, respectively. The increase in one human/dog ratio unit was associated with a 13% decrease in HVL rates. Canine seroprevalence, human/dog ratio and non-euthanasia of ELISA-reactive dogs in the environment were adequate indicators for analyzing the canine enzootic transmission and the occurrence of HVL cases.

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.

Climate change affects human health either directly or indirectly, and related impacts are complex, non-linear, and depend on several variables. The various climate change impacts on health include a change in the spatial distribution of vector-borne diseases. In this regard, this study presents and discusses changes in the spatial distribution of climate suitability for visceral leishmaniasis, yellow fever and malaria in Brazil, in different global warming scenarios. Maximum entropy (MaxEnt) was used to construct climate suitability models in warming scenarios. Models were based in climate variables generated by the Eta-HadGEM2 ES regional model, in the baseline period 1965-2005 and RCP8.5 scenario, representing global warming levels of 1,5ºC (2011-2040), 2,0ºC (2041-2070) and 4,0ºC (2071-2099). The three diseases studied are largely influenced by climate and showed different distribution patterns within the country. In global warming scenarios, visceral leishmaniasis found more favorable climate conditions in the Southeastern and Southern regions of Brazil, while climate in the Northern and Center-West regions gradually became more favorable to yellow fever. In malaria scenarios, an increase in favorable climate conditions to its high incidence was observed in the Atlantic Forest, where currently extra-Amazonian cases occur. The scenarios presented herein represent different possible consequences for the health sector in terms of adopting (or not) different measures to mitigate climate change in Brazil, such as reducing the emission of greenhouse gases.