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Background: Dengue, Zika, and chikungunya, whose viruses are transmitted mainly by Aedes aegypti, significantly impact human health worldwide. Despite the recent development of promising vaccines against the dengue virus, controlling these arbovirus diseases still depends on mosquito surveillance and control. Nonetheless, several studies have shown that these measures are not sufficiently effective or ineffective. Identifying higher-risk areas in a municipality and directing control efforts towards them could improve it. One tool for this is the premise condition index (PCI); however, its measure requires visiting all buildings. We propose a novel approach capable of predicting the PCI based on facade street-level images, which we call PCINet. Methodology: Our study was conducted in Campinas, a one million-inhabitant city in São Paulo, Brazil. We surveyed 200 blocks, visited their buildings, and measured the three traditional PCI components (building and backyard conditions and shading), the facade conditions (taking pictures of them), and other characteristics. We trained a deep neural network with the pictures taken, creating a computational model that can predict buildings' conditions based on the view of their facades. We evaluated PCINet in a scenario emulating a real large-scale situation, where the model could be deployed to automatically monitor four regions of Campinas to identify risk areas. Principal findings: PCINet produced reasonable results in differentiating the facade condition into three levels, and it is a scalable strategy to triage large areas. The entire process can be automated through data collection from facade data sources and inferences through PCINet. The facade conditions correlated highly with the building and backyard conditions and reasonably well with shading and backyard conditions. The use of street-level images and PCINet could help to optimize Ae. aegypti surveillance and control, reducing the number of in-person visits necessary to identify buildings, blocks, and neighborhoods at higher risk from mosquito and arbovirus diseases. Author summary: The strategies to control Ae. aegypti require intensive work and considerable financial resources, are time-consuming, and are commonly affected by operational problems requiring urgent improvement. The PCI is a good tool for identifying higher-risk areas; however, its measure requires a high amount of human and material resources, and the aforementioned issues remain. In this paper, we propose a novel approach capable of predicting the PCI of buildings based on street-level images. This first work combines deep learning-based methods with street-level data to predict facade conditions. Considering the good results obtained with PCINet and the good correlations of facade conditions with PCI components, we could use this methodology to classify building conditions without visiting them physically. With this, we intend to overcome the high cost of identifying high-risk areas. Although we have a long road ahead, our results show that PCINet could help to optimize Ae. aegypti and arbovirus surveillance and control, reducing the number of in-person visits necessary to identify buildings or areas at risk. [ABSTRACT FROM AUTHOR]

Abstract Background Many factors have been associated with circulation of the dengue fever virus and vector, although the dynamics of transmission are not yet fully understood. The aim of this work is to estimate the spatial distribution of the risk of dengue fever in an area of continuous dengue occurrence. Methods This is a spatial population-based case-control study that analyzed 538 cases and 727 controls in one district of the municipality of Campinas, São Paulo, Brazil, from 2006-2007, considering socio-demographic, ecological, case severity, and household infestation variables. Information was collected by in-home interviews and inspection of living conditions in and around the homes studied. Cases were classified as mild or severe according to clinical data, and they were compared with controls through a multinomial logistic model. A generalized additive model was used in order to include space in a non-parametric fashion with cubic smoothing splines. Results Variables associated with increased incidence of all dengue cases in the multiple binomial regression model were: higher larval density (odds ratio (OR) = 2.3 (95%CI: 2.0-2.7)), reports of mosquito bites during the day (OR = 1.8 (95%CI: 1.4-2.4)), the practice of water storage at home (OR = 2.5 (95%CI: 1.4, 4.3)), low frequency of garbage collection (OR = 2.6 (95%CI: 1.6-4.5)) and lack of basic sanitation (OR = 2.9 (95%CI: 1.8-4.9)). Staying at home during the day was protective against the disease (OR = 0.5 (95%CI: 0.3-0.6)). When cases were analyzed by categories (mild and severe) in the multinomial model, age and number of breeding sites more than 10 were significant only for the occurrence of severe cases (OR = 0.97, (95%CI: 0.96-0.99) and OR = 2.1 (95%CI: 1.2-3.5), respectively. Spatial distribution of risks of mild and severe dengue fever differed from each other in the 2006/2007 epidemic, in the study area. Conclusions Age and presence of more than 10 breeding sites were significant only for severe cases. Other predictors of mild and severe cases were similar in the multiple models. The analyses of multinomial models and spatial distribution maps of dengue fever probabilities suggest an area-specific epidemic with varying clinical and demographic characteristics.

Background: Measure the populations of Ae. aegypti and Ae. albopictus adults according to sex and location inside or outside the residence, estimate Ae. aegypti female density per house and per resident, and test the association with abiotic factors. Methods: Adult mosquitoes were collected monthly with a hand net and portable electric catcher in the peridomiciliary and intradomiciliary premises of residences in an urban area with ongoing dengue transmission in the municipality of São Sebastião, Brazil, from February 2011 to February 2012. Results: Of the 1,320 specimens collected, 1,311 were Ae. aegypti, and nine were Ae. albopictus. A total of 653 male and 658 female of Ae. aegypti were recorded, of which 80% were intradomiciliary. The mean density of Ae. aegypti adult females was 1.60 females/house and 0.42 females/resident. There was an association between the number of females and the number of residents in both intradomiciliary and peridomiciliary premises (r² = 0.92; p < 0.001 and r² = 0.68; p < 0.001, respectively). There was an association between the number of females and the mean and total rainfall; the correlation was better in peridomiciliary premises (p = 0.00; r² = 77%) than intradomiciliary premises in both cases (p = 0.01; r² = 48%). Minimum temperature was associated in both environments, exhibiting the same coefficient of determination (p = 0.02; r² = 40%). The low frequency of Ae. albopictus (seven females and two males) did not allow for detailed evaluation. Conclusions: Ae. aegypti is well established within the urban area studied, and the frequency of isolation is higher inside the houses. Female density was directly proportional to the number of residents in the houses. Our data show that human population density positively affects the number of Ae. aegypti females within the residence. Meteorological variables also affected mosquito populations. These data indicate a high probability of human-vector contact, increasing the possible transmission and spread of the DEN virus. Entomological indicators of adult females revealed important information complimenting what was obtained with traditional Stegomyia indices. This information should be a part of an interconnected data set for evaluating and controlling the vector. [ABSTRACT FROM AUTHOR]

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The epidemiology of dengue in the municipality of Campinas, São Paulo, Brazil, was studied in 1998 using a randomized sero-epidemiological survey. Epidemiological surveillance data from 1996-2003 were also analyzed, with an emphasis on virological surveillance. 1,260 individuals participated in the survey and had blood samples drawn by finger stick on filter paper. Blood samples were tested by EIA-ICC, an enzyme immunoassay using infected cells as antigen. Dengue antibody prevalence (14.79%) was lower than in other surveys in other States of Brazil, but higher than in two other serological surveys in São Paulo State. Dengue antibody prevalence was far higher than the reported case incidence during the 1996, 1997, and 1998 epidemics. Antibody prevalence and reported case incidence in different health districts were disproportional. The article concludes by recommending further research on the significance of transmission rates during epidemics and more intensive virological surveillance, especially in years with few reported cases.

Objective: To describe the hematophagous activity of Ae. aegypti and Ae. albopictus in an area under control and surveillance., Methods: The study was conducted during 18 months, from April, 1993 to October, 1994, in Cosmopolis, Sao Paulo state, Brazil. Human baits were used to collect mosquitoes. The number of females captured is presented monthly by area of the city and local in the household. The rainfall was measured and indices are presented without model adjustment., Results: The presence of females of both species was observed in 83% (Ae albopictus) and 61% (Ae. aegypti) of the period studied. The months of January, February and March presented the highest rates of activity for females of both species, with Ae. albopictus being more frequently captured than Ae. aegypti. Both species were captured in central and peripheral areas of the city, during the day from 9 to 12 am and from 4 to 7 pm. By a Poisson regression, it was observed that Ae. albopictus females were more frequently captured in the peri-housed area, in an independent way considering the area of the city., Conclusions: It has been identified difference on the hematophagous activity only for Ae. albopictus, being of importance the outside area of the house.