Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis.

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.

Human movement and environmental barriers shape the emergence of dengue.

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Big Data-Planetary Health approach for evaluating the Brazilian Dengue Control Program.

OBJECTIVE: This study aims to integrate the concepts of planetary health and big data into the Donabedian model to evaluate the Brazilian dengue control program in the state of São Paulo. METHODS: Data science methods were used to integrate and analyze dengue-related data, adding context to the structure and outcome components of the Donabedian model. This data, considering the period from 2010 to 2019, was collected from sources such as Department of Informatics of the Unified Health System (DATASUS), the Brazilian Institute of Geography and Statistics (IBGE), WorldClim, and MapBiomas. These data were integrated into a Data Warehouse. K-means algorithm was used to identify groups with similar contexts. Then, statistical analyses and spatial visualizations of the groups were performed, considering socioeconomic and demographic variables, soil, health structure, and dengue cases. OUTCOMES: Using climate variables, the K-means algorithm identified four groups of municipalities with similar characteristics. The comparison of their indicators revealed certain patterns in the municipalities with the worst performance in terms of dengue case outcomes. Although presenting better economic conditions, these municipalities held a lower average number of community healthcare agents and basic health units per inhabitant. Thus, economic conditions did not reflect better health structure among the three studied indicators. Another characteristic of these municipalities is urbanization. The worst performing municipalities presented a higher rate of urban population and human activity related to urbanization. CONCLUSIONS: This methodology identified important deficiencies in the implementation of the dengue control program in the state of São Paulo. The integration of several databases and the use of Data Science methods allowed the evaluation of the program on a large scale, considering the context in which activities are conducted. These data can be used by the public administration to plan actions and invest according to the deficiencies of each location.

Big Data-Planetary Health approach for evaluating the Brazilian Dengue Control Program / Abordagem Big Data-Saúde Planetária para avaliação do Programa de Combate à Dengue

ABSTRACT OBJECTIVE This study aims to integrate the concepts of planetary health and big data into the Donabedian model to evaluate the Brazilian dengue control program in the state of São Paulo. METHODS Data science methods were used to integrate and analyze dengue-related data, adding context to the structure and outcome components of the Donabedian model. This data, considering the period from 2010 to 2019, was collected from sources such as Department of Informatics of the Unified Health System (DATASUS), the Brazilian Institute of Geography and Statistics (IBGE), WorldClim, and MapBiomas. These data were integrated into a Data Warehouse. K-means algorithm was used to identify groups with similar contexts. Then, statistical analyses and spatial visualizations of the groups were performed, considering socioeconomic and demographic variables, soil, health structure, and dengue cases. OUTCOMES Using climate variables, the K-means algorithm identified four groups of municipalities with similar characteristics. The comparison of their indicators revealed certain patterns in the municipalities with the worst performance in terms of dengue case outcomes. Although presenting better economic conditions, these municipalities held a lower average number of community healthcare agents and basic health units per inhabitant. Thus, economic conditions did not reflect better health structure among the three studied indicators. Another characteristic of these municipalities is urbanization. The worst performing municipalities presented a higher rate of urban population and human activity related to urbanization. CONCLUSIONS This methodology identified important deficiencies in the implementation of the dengue control program in the state of São Paulo. The integration of several databases and the use of Data Science methods allowed the evaluation of the program on a large scale, considering the context in which activities are conducted. These data can be used by the public administration to plan actions and invest according to the deficiencies of each location.

RESUMO OBJETIVO Integrar os conceitos de Saúde Planetária e Big Data ao modelo de Donabedian, para avaliar o Programa de Combate à Dengue no estado de São Paulo. MÉTODOS Foram adotados métodos de Ciência de Dados para integração e análise de dados relacionados à dengue, agregando o contexto aos componentes de estrutura e de resultado do modelo de Donabedian. Esses dados, considerando o período de 2010 a 2019, foram coletados de fontes como Datasus, Instituto Brasileiro de Geografia e Estatística (IBGE), WorldClim e MapBiomas, e integrados em um Data Warehouse. Para a identificação de grupos com contextos similares, foi utilizado o algoritmo K-means. Em seguida, foram realizadas análises estatísticas e visualizações espaciais dos grupos, considerando variáveis socioeconômicas, demográficas, solo, estrutura de saúde e casos de dengue. RESULTADOS Com o uso das variáveis climáticas, o algoritmo K-means identificou quatro grupos de municípios com características similares. A comparação dos seus indicadores revelou certos padrões nos municípios com pior desempenho quanto aos resultados de casos de dengue. Embora tivessem melhores condições econômicas, eles tinham menor número médio de agentes comunitários e de unidades básicas de saúde por habitante. Dessa forma, as condições econômicas não refletiram em melhor estrutura de saúde nos três indicadores avaliados. Outra característica desses municípios é a urbanização. Os municípios de pior desempenho tinham maior taxa de população urbana e de modificações antrópicas relacionadas à urbanização. CONCLUSÕES Por meio desta metodologia, foi possível identificar importantes deficiências nas condições para a execução do programa de combate à dengue no estado de São Paulo. A integração de diversas bases de dados e a utilização de métodos de Ciência de Dados permitiram a avaliação do programa em larga escala, considerando o contexto em que as ações são executadas. Dessa forma, a gestão pública pode utilizar as informações coletadas para planejar ações e investir de acordo com as deficiências de cada local.

The SisaMob Information System: Implementation of Digital Data Collection as a Tool for Surveillance and Vector Control in the State of São Paulo.

Information systems are essential instruments in managing resources, in the evaluation of the epidemiological situation, and for decision-making at all hierarchical levels. Technological advances have allowed the development of systems that meet these premises. Therefore, it is recommended to consider the optimization of data entry and its immediate georeferencing in order to obtain information in real time. To meet this objective, we describe the application introduction process for the implementation of the digital collection of primary data and its integration with the database through synchronization with the SisaWeb platform (Information System for surveillance and control of Aedes aegypti), developed to meet the needs of the Arbovirus Surveillance and Control Program in the state of São Paulo, Brazil. For this purpose, the application-SisaMob-was conceived in the Android Studio development environment, Google®, following the same guidelines as the traditional collection method. Tablets equipped with the Android® operating system were used. To evaluate the implementation of the application, a semi-structured test was applied. The results highlighted that 774.9% (27) of the interviewees evaluated its use positively and, replacing the standard bulletin, 61.1% (22) of the users considered it regular to excellent. The automatic collection of geographic coordinates represented the greatest innovation in the use of the portable device, with reductions in errors and in the time taken to complete the report in the field. The integration to SisaWeb allowed obtaining information in real-time, being easily presented in tabular and graphic modes and spatially arranged through maps, making it possible to monitor the work at a distance, and allowing preliminary analyses during the data collection process. For the future, we must improve the mechanisms for assessing the effectiveness of information, increase the potential of the tool to produce more accurate analyses, which can direct actions more efficiently.

Influência das medidas de isolamento social pela Covid-19nos criadouros de Aedes aegypti em domicílios do Estado de São Paulo / Influence of social isolation measures by Covid-19 on Aedes aegypti breeding sites in households in the State of São Paulo

Introdução: O estudo objetivou analisar a distribuição de criadouros registrados nas atividades de avaliação de densidade larvária do Aedes aegypti em alguns anos que antecederam a pandemia de Covid-19 e que se seguiram a ela para verificar se as medidas de isolamento social impostas, que resultaram em maior tempo de permanência da população nas residências, influenciaram o comportamento dos indivíduos no que diz respeito aos cuidados relacionados à remoção de potenciais criadouros e, portanto, se alteraram o perfil e a quantidade de tipos de criadouros de Aedes aegypti no ano que se segue à pandemia de Covid-19. Método: Utilizaram-se dados de criadouros do mosquito no período de 2015 a 2019, antes da pandemia, e o ano de 2021, período da pandemia. Comparou-se a proporção relativa de criadouros por imóvel do estado de São Paulo em anos que antecederam a pandemia de Covid-19 com o ano de 2021 por região e total do estado. Resultados:Observou-se no estado de São Paulo uma média de 2,5 criadouros por imóvel de 2015 a 2019 e 3,1 no ano de 2021. Os resultados mostram que não há diferença entre a distribuição dos criadouros nos anos comparados com o ano de 2021. Conclusão: Apesar das medidas restritivas de isolamento social impostas pela pandemia de Covid-19, não houve alteração na distribuição e na quantidade de criadouros por imóvel.

Ovipositional Reproduction of the Dengue Vector for Identifying High-Risk Urban Areas.

Identification and classification of high-risk areas for the presence of Aedes aegypti is not an easy task. To develop suitable methods to identify this areas is an essential task that will increase the efficiency and effectiveness of control measures and to optimize the use of resources. The objectives of this study were to identify high- risk areas for the presence of Ae. aegypti using mosquito traps and household visits to identify breeding sites; to identify and validate aspects of the remote sensing images that could characterize these areas; to evaluate the relationship between this spatial risk classification and the occurrence of Ae. aegypti; and provide a methodology to the health and control vector services and prioritize these areas for development of control measure. Information about the geographical coordinates of these traps will enable us to apply the kriging spatial analysis tool to generate maps with the predicted numbers of Ae. aegypti. Satellite images were used to identify the characteristic features the four areas, so that other areas could also be classified using only the sensing remote images. The developed methodology enables the identification of high-risk areas for Ae. aegypti and for the occurrence of Dengue, as well as Zika fever and Chikungunya fever using only sensing remote images. These results allow health and vector control services to prioritize these areas for developing surveillance and control measures. The use of the available resources can be optimized and potentially promote a decrease in the expected incidences of these diseases, particularly Dengue.

Ovipositional Reproduction of the Dengue Vector for Identifying High-Risk Urban Areas

Identification and classification of high-risk areas for the presence of Aedes aegypti is not an easy task. To develop suitable methods to identify this areas is an essential task that will increase the efficiency and effectiveness of control measures and to optimize the use of resources. The objectives of this study were to identify high- risk areas for the presence of Ae. aegypti using mosquito traps and household visits to identify breeding sites; to identify and validate aspects of the remote sensing images that could characterize these areas; to evaluate the relationship between this spatial risk classification and the occurrence of Ae. aegypti; and provide a methodology to the health and control vector services and prioritize these areas for development of control measure. Information about the geographical coordinates of these traps will enable us to apply the kriging spatial analysis tool to generate maps with the predicted numbers of Ae. aegypti. Satellite images were used to identify the characteristic features the four areas, so that other areas could also be classified using only the sensing remote images. The developed methodology enables the identification of high-risk areas for Ae. aegypti and for the occurrence of Dengue, as well as Zika fever and Chikungunya fever using only sensing remote images. These results allow health and vector control services to prioritize these areas for developing surveillance and control measures. The use of the available resources can be optimized and potentially promote a decrease in the expected incidences of these diseases, particularly Dengue.

Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control.

Studies have shown that areas with lower socioeconomic standings are often more vulnerable to dengue and similar deadly diseases that can be spread through mosquitoes. This study aims to detect water tanks installed on rooftops and swimming pools in digital images to identify and classify areas based on the socioeconomic index, in order to assist public health programs in the control of diseases linked to the Aedes aegypti mosquito. This study covers four regions of Campinas, São Paulo, characterized by different socioeconomic contexts. With mosaics of images obtained by a 12.1 MP Canon PowerShot S100 (5.2 mm focal length) carried by unmanned aerial vehicles, we developed deep learning algorithms in the scope of computer vision for the detection of water tanks and swimming pools. An object detection model, which was initially created for areas of Belo Horizonte, Minas Gerais, was enhanced using the transfer learning technique, and allowed us to detect objects in Campinas with fewer samples and more efficiency. With the detection of objects in digital images, the proportions of objects per square kilometer for each region studied were estimated by adopting a Chi-square distribution model. Thus, we found that regions with low socioeconomic status had more exposed water tanks, while regions with high socioeconomic levels had more exposed pools. Using deep learning approaches, we created a useful tool for Ae. aegypti control programs to utilize and direct disease prevention efforts. Therefore, we concluded that it is possible to detect objects directly related to the socioeconomic level of a given region from digital images, which encourages the practicality of this approach for studies aimed towards public health.

Effect of social isolation in dengue cases in the state of Sao Paulo, Brazil: An analysis during the COVID-19 pandemic.

BACKGROUND: Studies have shown that human mobility is an important factor in dengue epidemiology. Changes in mobility resulting from COVID-19 pandemic set up a real-life situation to test this hypothesis. Our objective was to evaluate the effect of reduced mobility due to this pandemic in the occurrence of dengue in the state of São Paulo, Brazil. METHOD: It is an ecological study of time series, developed between January and August 2020. We use the number of confirmed dengue cases and residential mobility, on a daily basis, from secondary information sources. Mobility was represented by the daily percentage variation of residential population isolation, obtained from the Google database. We modeled the relationship between dengue occurrence and social distancing by negative binomial regression, adjusted for seasonality. We represent the social distancing dichotomously (isolation versus no isolation) and consider lag for isolation from the dates of occurrence of dengue. RESULTS: The risk of dengue decreased around 9.1% (95% CI: 14.2 to 3.7) in the presence of isolation, considering a delay of 20 days between the degree of isolation and the dengue first symptoms. CONCLUSIONS: We have shown that mobility can play an important role in the epidemiology of dengue and should be considered in surveillance and control activities.

Effect of social isolation in dengue cases in the state of Sao Paulo, Brazil: An analysis during the COVID-19 pandemic

Background Studies have shown that human mobility is an important factor in dengue epidemiology. Changes in mobility resulting from COVID-19 pandemic set up a real-life situation to test this hypothesis. Our objective was to evaluate the effect of reduced mobility due to this pandemic in the occurrence of dengue in the state of São Paulo, Brazil. Method It is an ecological study of time series, developed between January and August 2020. We use the number of confirmed dengue cases and residential mobility, on a daily basis, from secondary information sources. Mobility was represented by the daily percentage variation of residential population isolation, obtained from the Google database. We modeled the relationship between dengue occurrence and social distancing by negative binomial regression, adjusted for seasonality. We represent the social distancing dichotomously (isolation versus no isolation) and consider lag for isolation from the dates of occurrence of dengue. Results The risk of dengue decreased around 9.1% (95% CI: 14.2 to 3.7) in the presence of isolation, considering a delay of 20 days between the degree of isolation and the dengue first symptoms. Conclusions We have shown that mobility can play an important role in the epidemiology of dengue and should be considered in surveillance and control activities.

Use of an Extended Premise Condition Index for detection of priority areas for vector control actions.

The Premise Condition Index (PCI), proposed by Tun-Lin and colleagues in 1995, is a score that considers the conditions of a premise as well its yards and degree of shading. They hypothesized that the higher its value the greater the probability of the premise having the presence of Aedes aegypti. This study aimed to evaluate if there is a correspondence between PCI and Ae. aegypti infestation in four areas of a large city in the State of São Paulo, Brazil, if the inclusion of new categories related to the presence of animals in premises would increase the probability of detecting predictive areas for vector control actions and, if so, to propose an expanded PCI. The positivity of the premises for the presence of Ae. aegypti was modeled considering a Bernoulli probability distribution, in a Bayesian context using the Integrated Nested Laplace Approximation. The study showed that, in general, the higher the value of the PCI of a premise, the more likely it is to have the presence of Ae. aegypti, and the inclusion of information on the animals' presence can increase the discriminatory power of PCI. These results support the proposition of an extended PCI that would consider, in addition to the conditions of the premise, the presence of animals to classify it regarding the risk of the presence of Ae. aegypti.

Use of an Extended Premise Condition Index for detection of priority areas for vector control actions

The Premise Condition Index (PCI), proposed by Tun-Lin and colleagues in 1995, is a score that considers the conditions of a premise as well its yards and degree of shading. They hypothesized that the higher its value the greater the probability of the premise having the presence of Aedes aegypti. This study aimed to evaluate if there is a correspondence between PCI and Ae. aegypti infestation in four areas of a large city in the State of São Paulo, Brazil, if the inclusion of new categories related to the presence of animals in premises would increase the probability of detecting predictive areas for vector control actions and, if so, to propose an expanded PCI. The positivity of the premises for the presence of Ae. aegypti was modeled considering a Bernoulli probability distribution, in a Bayesian context using the Integrated Nested Laplace Approximation. The study showed that, in general, the higher the value of the PCI of a premise, the more likely it is to have the presence of Ae. aegypti, and the inclusion of information on the animals' presence can increase the discriminatory power of PCI. These results support the proposition of an extended PCI that would consider, in addition to the conditions of the premise, the presence of animals to classify it regarding the risk of the presence of Ae. aegypti.

Vectors of arboviruses in the state of São Paulo: 30 years of Aedes aegypti and Aedes albopictus.

OBJECTIVE: To describe the infestation of the municipalities of São Paulo by the vectors Aedes aegypti and Aedes albopictus, characterize seasonality and analyze average temperatures and larval densities. METHODS: We used maps with information on the infestation of municipalities between 1986 and 2015. The analysis of larval density of the species by the Wilcoxon test used the Breteau index values for Ae. aegypti and Ae. albopictus obtained from the Superintendency for Endemic Diseases Control database. In the seasonal description, arithmetic means of each vector were calculated by month and year. Mean temperature analyses were presented on maps with color gradients. RESULTS: The state of São Paulo is currently almost totally infested, with co-occurrence of species in 93.64% of the municipalities. The seasonality analysis showed the first quarter as the most favorable period for larval abundance. The increase of mean temperatures in geographical areas coincided with the temporal trajectory of Ae. aegypti territorial expansion. The mean larval density found was higher for Ae. aegypti than for Ae. albopictus (p = 0.00). CONCLUSIONS: Initially, these Culicidae occupied distinct and opposing areas. Over time, however, co-occurrence showed how great their capacity for adaptation is, even in the face of different social and urban conjunctures. The increase of the mean temperature contributed to Ae. Aegypti 's geographic expansion, as well as to the clearly seasonal profile of both species. In general, larval infestation by Ae. aegypti prevailed, which evidenced its competitive superiority. These data provide a better understanding of the dynamics of arboviral transmission in the state of São Paulo and can be used in vector surveillance and control.

Influence of strategic points in the dispersion of Aedes aegypti in infested areas.

OBJECTIVE: To evaluate whether sites with large amount of potential breeding sites for immature forms of Aedes aegypti, called strategic points, influence in the active vector's dispersion into properties in their surroundings. METHODS: We selected four areas in the municipality of Campinas, three of them with strategic points classified as high, moderate, and low risk according to infestation and a control area, without strategic points. Between October 2015 and September 2016, we monthly installed oviposition traps and evaluated the infestation by Ae. aegypti in all properties of each selected area. To verify if there was vector dispersion from each strategic point, based on its location, we investigated the formation of clusters with excess of eggs or larvae or pupae containers, using the Gi spatial statistics. RESULTS: The amount of eggs collected in the ovitraps and the number of positive containers for Ae. aegypti did not show clusters of high values concerning its distance from the strategic point. Both presented random distribution not spatially associated with the positioning of strategic points in the area. CONCLUSIONS: Strategic points are not confirmed as responsible for the vector's dispersion for properties in their surroundings. We highlight the importance of reviewing the current strategy of the vector control program in Brazil, seeking a balance from the technical, operational, and economic point of view, without disregarding the role of strategic points as major producers of mosquitoes and their importance in the dissemination of arboviruses in periods of transmission.

Vectors of arboviruses in the state of São Paulo: 30 years of Aedes aegypti and Aedes albopictus / Vetores de arboviroses no estado de São Paulo: 30 anos de Aedes aegypti e Aedes albopictus

ABSTRACT OBJECTIVE To describe the infestation of the municipalities of São Paulo by the vectors Aedes aegypti and Aedes albopictus, characterize seasonality and analyze average temperatures and larval densities. METHODS We used maps with information on the infestation of municipalities between 1986 and 2015. The analysis of larval density of the species by the Wilcoxon test used the Breteau index values for Ae. aegypti and Ae. albopictus obtained from the Superintendency for Endemic Diseases Control database. In the seasonal description, arithmetic means of each vector were calculated by month and year. Mean temperature analyses were presented on maps with color gradients. RESULTS The state of São Paulo is currently almost totally infested, with co-occurrence of species in 93.64% of the municipalities. The seasonality analysis showed the first quarter as the most favorable period for larval abundance. The increase of mean temperatures in geographical areas coincided with the temporal trajectory of Ae. aegypti territorial expansion. The mean larval density found was higher for Ae. aegypti than for Ae. albopictus (p = 0.00). CONCLUSIONS Initially, these Culicidae occupied distinct and opposing areas. Over time, however, co-occurrence showed how great their capacity for adaptation is, even in the face of different social and urban conjunctures. The increase of the mean temperature contributed to Ae. Aegypti 's geographic expansion, as well as to the clearly seasonal profile of both species. In general, larval infestation by Ae. aegypti prevailed, which evidenced its competitive superiority. These data provide a better understanding of the dynamics of arboviral transmission in the state of São Paulo and can be used in vector surveillance and control.

RESUMO OBJETIVO Descrever a infestação dos municípios paulistas pelos vetores Aedes aegypti e Aedes albopictus , caracterizar a sazonalidade e analisar as temperaturas médias e as densidades larvárias. MÉTODOS Foram empregados mapas com informações sobre a infestação dos municípios entre 1986 e 2015. A análise da densidade larvária das espécies pelo teste de Wilcoxon utilizou os valores do índice de Breteau para Ae. aegypti e Ae. albopictus obtidos no banco de dados da Superintendência de Controle de Endemias. Na descrição sazonal, foram calculadas as médias aritméticas de cada um por mês e ano. As análises de temperaturas médias foram apresentadas em mapas com gradientes de cores. RESULTADOS O estado de São Paulo apresenta-se na atualidade quase totalmente infestado, com coocorrência das espécies em 93,64% dos municípios. A análise da sazonalidade evidenciou o primeiro trimestre como o período mais favorável para a abundância larval. Observou-se elevação das temperaturas médias em áreas geográficas coincidentes com a trajetória temporal da expansão territorial de Ae. aegypti . O valor médio da densidade larvária de Ae. aegypti foi maior do que o verificado para Ae. albopictus (p = 0,00). CONCLUSÕES Esses culicídeos apresentaram, inicialmente, ocupação em áreas distintas e opostas. Entretanto, no decorrer do tempo, a coocorrência mostrou quão grande é a capacidade de adaptação, mesmo em face de conjunturas sociais e urbanas diferentes. A elevação da temperatura média contribuiu para a expansão geográfica de Ae. aegypti , assim como para o perfil nitidamente sazonal de ambas as espécies. No geral, a infestação larvária por Ae. aegypti foi predominante, o que evidenciou sua superioridade competitiva. Tais dados propiciam maior entendimento da dinâmica de transmissão de arboviroses no estado de São Paulo e são subsídios para a vigilância e o controle desses vetores.

Influence of strategic points in the dispersion of Aedes aegypti in infested areas / Influência de pontos estratégicos na dispersão de Aedes aegypti em áreas infestadas

ABSTRACT OBJECTIVE: To evaluate whether sites with large amount of potential breeding sites for immature forms of Aedes aegypti, called strategic points, influence in the active vector's dispersion into properties in their surroundings. METHODS: We selected four areas in the municipality of Campinas, three of them with strategic points classified as high, moderate, and low risk according to infestation and a control area, without strategic points. Between October 2015 and September 2016, we monthly installed oviposition traps and evaluated the infestation by Ae. aegypti in all properties of each selected area. To verify if there was vector dispersion from each strategic point, based on its location, we investigated the formation of clusters with excess of eggs or larvae or pupae containers, using the Gi spatial statistics. RESULTS: The amount of eggs collected in the ovitraps and the number of positive containers for Ae. aegypti did not show clusters of high values concerning its distance from the strategic point. Both presented random distribution not spatially associated with the positioning of strategic points in the area. CONCLUSIONS: Strategic points are not confirmed as responsible for the vector's dispersion for properties in their surroundings. We highlight the importance of reviewing the current strategy of the vector control program in Brazil, seeking a balance from the technical, operational, and economic point of view, without disregarding the role of strategic points as major producers of mosquitoes and their importance in the dissemination of arboviruses in periods of transmission.

RESUMO OBJETIVO: Avaliar se locais com grande quantidade de potenciais criadouros de formas imaturas de Aedes aegypti, denominados pontos estratégicos, influenciam a dispersão ativa do vetor aos imóveis no seu entorno. MÉTODOS: Foram selecionadas quatro áreas no município de Campinas, três delas com pontos estratégicos classificados como alto, médio e baixo risco segundo a infestação e uma área controle, sem ponto estratégico. Entre outubro de 2015 e setembro de 2016, instalaram-se mensalmente armadilhas de oviposição e avaliou-se a infestação por Ae. aegypti em todos os imóveis de cada área selecionada. Para verificar se houve dispersão do vetor a partir de cada ponto estratégico, com base em sua localização, investigou-se a formação de aglomerados com excesso de ovos ou de recipientes com larvas ou pupas, utilizando a estatística espacial Gi. RESULTADOS: o número de ovos coletados nas ovitrampas e o número de recipientes positivos para Ae. aegypti não apresentaram aglomerados de altos valores relativos à sua distância do ponto estratégico. Ambos apresentaram distribuição aleatória não associada espacialmente com o posicionamento dos pontos estratégicos na área. CONCLUSÕES: Pontos estratégicos não se confirmaram como responsáveis pela dispersão do vetor para os imóveis no seu entorno. Destaca-se a importância de rever a estratégia atual do programa de controle de vetores do Brasil, buscando um equilíbrio do ponto de vista técnico, operacional e econômico, sem desconsiderar o papel dos pontos estratégicos como grandes produtores de mosquitos e sua importância na disseminação de arboviroses em momentos de transmissão.