Search

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]

Copyright of Cadernos de Saude Publica is the property of Escola Nacional de Saude Publica Sergio Arouca and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The incidence of visceral leishmaniasis (VL), one of the most important neglected diseases worldwide, is increasing in Brazil. The objectives of this study were to determine the canine VL (CanL) seroprevalence in an urban area of Araçatuba municipality and to evaluate its relationship with the characteristics of dogs and their owners. Results: The CanL seroprevalence in the study area was 0.081 (95% credible interval [CI]: 0.068–0.096). The following covariates/categories were positively associated with the occurrence of a seropositive dog: more than 10 dogs that had lived in the house (odds ratio [OR] = 2.36; 95% CI: 1.03–5.43) (baseline: 0–10 dogs); house with dogs that previously died of VL (OR = 4.85; 95% CI: 2.65–8.86) or died of causes other than old age (OR = 2.26; 95% CI: 1.12–4.46) (baseline: natural or no deaths); dogs that spent the day in a sheltered backyard (OR = 2.14; 95% CI: 1.05–4.40); dogs that spent the day in an unsheltered backyard or the street (OR = 2.67; 95% CI: 1.28–5.57) (baseline: inside home). Spatial dependence among observations occurred within about 45.7 m. Conclusions: The number of dogs that had lived in the house, previous deaths by VL or other cause, and the place the dog stayed during the day were associated with the occurrence of a VL seropositive dog. The short-distance spatial dependence could be related to the vector characteristics, producing a local neighbourhood VL transmission pattern. The geostatistical approach in a Bayesian context using integrated nested Laplace approximation (INLA) allowed to identify the covariates associated with VL, including its spatially dependent transmission pattern. [ABSTRACT FROM AUTHOR]

Breast cancer is the most frequently diagnosed type of cancer and is the leading cause of death from cancer in the female population. Screening mammograms and early treatment are the most frequently used means to attempt to reduce this mortality and are promoted during Pink October, an annual awareness-raising campaign. However, recent studies have correlated the increase in screening with higher morbidity and mortality, due to overdiagnosis and overtreatment. The current study assessed searches related to breast cancer and mammogram in Google Trends from 2004 to 2019 in terms of trend, seasonality, and distribution in Brazilian states. The study also evaluatedH the correlation between the number of searches in Google Trends and the number of screening mammograms. The two series showed a seasonal pattern with peaks in October, and there was an excess in tests performed outside the recommended age bracket. Pink October transmitted and popularized health information and induced behaviors related to this information, which are three desirable aspects in health communication and education. However, the campaign also generated an excess in screening mammograms and did not encourage autonomy and free and informed consent. Pink October revealed both the potential of mass communication in health and the need for messages to be aligned with the best available scientific evidence.

Objective: To verify the spatial pattern of mortality from breast and cervical cancer in areas of primary health care, considering socioeconomic conditions., Methods: This is an ecological study, from January 2000 to December 2016. The study area is the municipality of São Paulo, Brazil, and its 456 coverage areas of primary health units. Information on deaths of women aged 20 years or over were geocoded according to residence address. We calculated mortality rates, standardized by age, and smoothed by the local empirical Bayesian method, and grouped into three or two years to reduce the random fluctuation of the data. In addition, bivariate global and local Moran indexes were calculated to verify the existence of spatial agglomeration of standardized mortality rates with a domain of socioeconomic condition, elaborated based on the Índice Paulista de Vulnerabilidade Social (IPVS - São Paulo Index of Social Vulnerability)., Results: The success rate of geocoding was 98.9%. Mortality from breast cancer, without stratification by time, showed a pattern with higher rates located in central regions with better socioeconomic conditions. It showed a decrease at the end of the period and a change in spatial pattern, with increased mortality in peripheral regions. On the other hand, mortality from cervical cancer remained with the highest rates in peripheral regions with worse socioeconomic conditions, despite being reduced over time., Conclusion: The spatial pattern of mortality from the studied cancers, over time, suggests association with the best socioeconomic conditions of the municipality, either as protection (cervical) or risk (breast). This knowledge may direct resources to prevent and promote health in the territories.

Visceral leishmaniasis is an emerging and neglected disease that is currently expanding to urban areas. The incidence of human disease is related to canine infection. Araçatuba and Birigui are municipalities (counties) in the state of São Paulo, Brazil, with 8-10% seroprevalence of canine infection and that employ control strategies targeting the canine reservoir, based on serological survey and culling of seropositive dogs. Using data from these control programs to parameterize mathematical models, this study assessed the efficacy of these activities. We estimated that current control is capable of reducing the incidence of canine visceral leishmaniasis (CVL) by approximately 20%. Assuming continuous control and three times the current serological survey activities in Araçatuba and Birigui, culling dogs with a positive CVL diagnosis would be effective for the control of canine infection. Although theoretically possible, in practice the control of CVL with the currently recommended strategies is insufficient, since it would require overcoming the difficulties in these activities, such as lack of material, human, and financial resources, besides associated ethical and legal issues.

We describe the discovery of Aedes aegypti underground breeding site in the Pinheiros neighborhood of São Paulo, SP, during an entomological survey program performed in 2016. Even with intense surveillance and vector control, large numbers of mosquitoes were present in this area. A detailed investigation allowed for the detection of Ae. aegypti in an underground reservoir used for rainwater storage. After the implementation of protection screens in the accesses, the presence of the vector was no longer detected. In this study, we discuss the frequent use of this type of reservoir structure and its risk for mosquito production.