RESUMO

Visceral leishmaniasis (VL) is a neglected tropical disease transmitted by Lutzomyia longipalpis, a sand fly widely distributed in Brazil. Despite efforts to strengthen national control programs reduction in incidence and geographical distribution of VL in Brazil has not yet been successful; VL is in fact expanding its range in newly urbanized areas. Ecological niche models (ENM) for use in surveillance and response systems may enable more effective operational VL control by mapping risk areas and elucidation of eco-epidemiologic risk factors. ENMs for VL and Lu. longipalpis were generated using monthly WorldClim 2.0 data (30-year climate normal, 1-km spatial resolution) and monthly soil moisture active passive (SMAP) satellite L4 soil moisture data. SMAP L4 Global 3-hourly 9-km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V004 were obtained for the first image of day 1 and day 15 (0:00-3:00 hour) of each month. ENM were developed using MaxEnt software to generate risk maps based on an algorithm for maximum entropy. The jack-knife procedure was used to identify the contribution of each variable to model performance. The three most meaningful components were used to generate ENM distribution maps by ArcGIS 10.6. Similar patterns of VL and vector distribution were observed using SMAP as compared to WorldClim 2.0 models based on temperature and precipitation data or water budget. Results indicate that direct Earth-observing satellite measurement of soil moisture by SMAP can be used in lieu of models calculated from classical temperature and precipitation climate station data to assess VL risk.

Assuntos

RESUMO

Leishmaniasis is a public health problem worldwide. We aimed to predict ecological niche models (ENMs) for visceral (VL) and cutaneous (CL) leishmaniasis and the sand flies involved in the transmission of leishmaniasis in São Paulo, Brazil. Phlebotomine sand flies were collected between 1985 and 2015. ENMs were created for each sand fly species using Maximum Entropy Species Distribution Modeling software, and 20 climatic variables were determined. Nyssomyia intermedia (Lutz & Neiva, 1912) and Lutzomyia longipalpis (Lutz & Neiva, 1912), the primary vectors involved in CL and VL, displayed the highest suitability across the various regions, climates, and topographies. L. longipalpis was found in the border of Paraná an area currently free of VL. The variables with the greatest impact were temperature seasonality, precipitation, and altitude. Co-presence of multiple sand fly species was observed in the cuestas and coastal areas along the border of Paraná and in the western basalt areas along the border of Mato Grosso do Sul. Human CL and VL were found in 475 of 546 (86.7%) and 106 of 645 (16.4%) of municipalities, respectively. Niche overlap between N. intermedia and L. longipalpis was found with 9208 human cases of CL and 2952 cases of VL. ENMs demonstrated that each phlebotomine sand fly species has a unique geographic distribution pattern, and the occurrence of the primary vectors of CL and VL overlapped. These data can be used by public authorities to monitor the dispersion and expansion of CL and VL vectors in São Paulo state.

Assuntos

RESUMO

NASA's Earth Observing Satellites (EOS) were used to calculate three vegetation indices, extract precipitation and elevation data, and then evaluate their applicability for assessing risk of visceral leishmaniasis (VL) and cutaneous leishmaniasis (CL) in Bahia State, Brazil. Regression models showed that either form of leishmaniasis can be predicted by NDVI, NDMI, NDWI data products and TRMM) precipitation data (R2= 0.370; p<0.001). Elevation was not significantly associated with the distribution of either VL or CL. In areas of high annual precipitation, CL was 3.6 times more likely to occur than VL. For vegetative moisture (NDMI), CL was 2.11 times more likely to occur than VL. Odds of CL occurrence increased to 5.5 times when vegetation (NDVI) and 13.5 times when liquid water content of vegetation canopies (NDWI) was considered. Areas at risk of CL and VL were mapped based on the selected explanatory variables. Accuracy of models were assessed using area under the receiver operating characteristic curve (AUC=0.72). We propose that statewide scale risk models based on use of EOS products will be a useful tool at 1 km2 spatial resolution to enable health workers to identify and target high risk areas to prevent transmission of leishmaniasis.(AU)

Os satélites de observação da Terra (SOT) da NASA foram usados para calcular três índices de vegetação, extrair dados de precipitação e elevação e avaliar sua aplicabilidade para identificar o risco para leishmaniose visceral (LV) e leishmaniose tegumentar (LT) no Estado da Bahia, Brasil. Modelos de regressão mostraram que ambas as formas de leishmaniose podem ser preditas pelos NDVI, NDMI, NDWI e precipitação TRMM (R2 = 0,370; p<0,001). A elevação não foi significativamente associada à distribuição de LV ou LT. Em áreas de alta precipitação anual, a LT foi 3,6 vezes mais provável de ocorrer do que a LV. Para a umidade vegetativa (NDMI), a LT apresentou 2,11 maior probabilidade de ocorrer do que a LV. As chances de ocorrência de LT aumentaram para 5,5 vezes em relação com a vegetação (NDVI) e 13,5 vezes quando o conteúdo de água líquida dos dosséis da vegetação (NDWI) foi considerado. Áreas em risco de LT e LV foram mapeadas com base nas variáveis explicativas selecionadas. A precisão dos modelos foi avaliada usando a área sob curva característica de operação do receptor (Curva COR=0,72). Propusemos que os modelos de risco em escala estadual baseados no uso de produtos SOT são uma ferramenta útil na resolução espacial de 1 km2 por permitir que profissionais de saúde identifiquem e direcionem áreas de alto risco para evitar a transmissão da leishmaniose. (AU)

Assuntos

RESUMO

NASA’s Earth Observing Satellites (EOS) were used to calculate three vegetation indices, extract precipitation and elevation data, and then evaluate their applicability for assessing risk of visceral leishmaniasis (VL) and cutaneous leishmaniasis (CL) in Bahia State, Brazil. Regression models showed that either form of leishmaniasis can be predicted by NDVI, NDMI, NDWI data products and TRMM) precipitation data (R2 = 0.370; p<0.001). Elevation was not significantly associated with the distribution of either VL or CL. In areas of high annual precipitation, CL was 3.6 times more likely to occur than VL. For vegetative moisture (NDMI), CL was 2.11 times more likely to occur than VL. Odds of CL occurrence increased to 5.5 times when vegetation (NDVI) and 13.5 times when liquid water content of vegetation canopies (NDWI) was considered. Areas at risk of CL and VL were mapped based on the selected explanatory variables. Accuracy of models were assessed using area under the receiver operating characteristic curve (AUC=0.72). We propose that statewide scale risk models based on use of EOS products will be a useful tool at 1 km2 spatial resolution to enable health workers to identify and target high risk areas to prevent transmission of leishmaniasis.

Os satélites de observação da Terra (SOT) da NASA foram usados para calcular três índices de vegetação, extrair dados de precipitação e elevação e avaliar sua aplicabilidade para identificar o risco para leishmaniose visceral (LV) e leishmaniose tegumentar (LT) no Estado da Bahia, Brasil. Modelos de regressão mostraram que ambas as formas de leishmaniose podem ser preditas pelos NDVI, NDMI, NDWI e precipitação TRMM (R2 = 0,370; p<0,001). A elevação não foi significativamente associada à distribuição de LV ou LT. Em áreas de alta precipitação anual, a LT foi 3,6 vezes mais provável de ocorrer do que a LV. Para a umidade vegetativa (NDMI), a LT apresentou 2,11 maior probabilidade de ocorrer do que a LV. As chances de ocorrência de LT aumentaram para 5,5 vezes em relação com a vegetação (NDVI) e 13,5 vezes quando o conteúdo de água líquida dos dosséis da vegetação (NDWI) foi considerado. Áreas em risco de LT e LV foram mapeadas com base nas variáveis explicativas selecionadas. A precisão dos modelos foi avaliada usando a área sob curva característica de operação do receptor (Curva COR=0,72). Propusemos que os modelos de risco em escala estadual baseados no uso de produtos SOT são uma ferramenta útil na resolução espacial de 1 km2 por permitir que profissionais de saúde identifiquem e direcionem áreas de alto risco para evitar a transmissão da leishmaniose.

Assuntos

RESUMO

Visceral leishmaniasis is a public health problem in Brazil. This disease is endemic in most of Bahia state, with increasing reports of cases in new areas. Ecological niche models (ENM) can be used as a tool for predicting potential distribution for disease, vectors, and to identify risk factors associated with their distribution. In this study, ecological niche models (ENMs) were developed for visceral leishmaniasis (VL) cases and 12 sand fly species captured in Bahia state. Sand fly data was collected monthly by CDC light traps from July 2009 to December 2012. MODIS satellite imagery was used to calculate NDVI, NDMI, and NDWI vegetation indices, MODIS day and night land surface temperature (LST), enhanced vegetation index (EVI), and 19 Bioclim variables were used to develop the ENM using the maximum entropy approach (Maxent). Mean diurnal range was the variable that most contributed to all the models for sand flies, followed by precipitation in wettest month. For Lutzomyia longipalpis (L. longipalpis), annual precipitation, precipitation in wettest quarter, precipitation in wettest month, and NDVI were the most contributing variables. For the VL model, the variables that contributed most were precipitation in wettest month, annual precipitation, LST day, and temperature seasonality. L. longipalpis was the species with the widest potential distribution in the state. The identification of risk areas and factors associated with this distribution is fundamental to prioritize resource allocation and to improve the efficacy of the state's program for surveillance and control of VL.

Assuntos

RESUMO

NASAs Earth Observing Satellites (EOS) were used to calculate three vegetation indices, extract precipitation and elevation data, and then evaluate their applicability for assessing risk of visceral leishmaniasis (VL) and cutaneous leishmaniasis (CL) in Bahia State, Brazil. Regression models showed that either form of leishmaniasis can be predicted by NDVI, NDMI, NDWI data products and TRMM) precipitation data (R2 = 0.370; p<0.001). Elevation was not significantly associated with the distribution of either VL or CL. In areas of high annual precipitation, CL was 3.6 times more likely to occur than VL. For vegetative moisture (NDMI), CL was 2.11 times more likely to occur than VL. Odds of CL occurrence increased to 5.5 times when vegetation (NDVI) and 13.5 times when liquid water content of vegetation canopies (NDWI) was considered. Areas at risk of CL and VL were mapped based on the selected explanatory variables. Accuracy of models were assessed using area under the receiver operating characteristic curve (AUC=0.72). We propose that statewide scale risk models based on use of EOS products will be a useful tool at 1 km2 spatial resolution to enable health workers to identify and target high risk areas to prevent transmission of leishmaniasis.(AU)

Os satélites de observação da Terra (SOT) da NASA foram usados para calcular três índices de vegetação, extrair dados de precipitação e elevação e avaliar sua aplicabilidade para identificar o risco para leishmaniose visceral (LV) e leishmaniose tegumentar (LT) no Estado da Bahia, Brasil. Modelos de regressão mostraram que ambas as formas de leishmaniose podem ser preditas pelos NDVI, NDMI, NDWI e precipitação TRMM (R2 = 0,370; p<0,001). A elevação não foi significativamente associada à distribuição de LV ou LT. Em áreas de alta precipitação anual, a LT foi 3,6 vezes mais provável de ocorrer do que a LV. Para a umidade vegetativa (NDMI), a LT apresentou 2,11 maior probabilidade de ocorrer do que a LV. As chances de ocorrência de LT aumentaram para 5,5 vezes em relação com a vegetação (NDVI) e 13,5 vezes quando o conteúdo de água líquida dos dosséis da vegetação (NDWI) foi considerado. Áreas em risco de LT e LV foram mapeadas com base nas variáveis explicativas selecionadas. A precisão dos modelos foi avaliada usando a área sob curva característica de operação do receptor (Curva COR=0,72). Propusemos que os modelos de risco em escala estadual baseados no uso de produtos SOT são uma ferramenta útil na resolução espacial de 1 km2 por permitir que profissionais de saúde identifiquem e direcionem áreas de alto risco para evitar a transmissão da leishmaniose.(AU)

Assuntos

RESUMO

Amphibians inhabiting montane riparian zones in the Neotropics are particularly vulnerable to decline, but the reasons are poorly understood. Because environmental contaminants, endocrine disruption, and pathogens often figure prominently in amphibian declines it is imperative that we understand how these factors are potentially interrelated to affect montane populations. One possibility is that increased precipitation associated with global warming promotes the deposition of contaminants in montane regions. Increased exposure to contaminants, in turn, potentially elicits chronic elevations in circulating stress hormones that could contribute to montane population declines by compromising resistance to pathogens and/or production of sex steroids regulating reproduction. Here, we test this hypothesis by examining contaminant levels, stress and sex steroid levels, and nematode abundances in male drab treefrogs, Smilisca sordida, from lowland and montane populations in Costa Rica. We found no evidence that montane populations were more likely to possess contaminants (i.e., organochlorine, organophosphate and carbamate pesticides or benzidine and chlorophenoxy herbicides) than lowland populations. We also found no evidence of elevational differences in circulating levels of the stress hormone corticosterone, estradiol or progesterone. However, montane populations possessed lower androgen levels, hosted more nematode species, and had higher nematode abundances than lowland populations. Although these results suggested that nematodes contributed to lower androgens in montane populations, we were unable to detect a significant inverse relationship between nematode abundance and androgen level. Our results suggest that montane populations of this species are not at greater risk of exposure to contaminants or chronic stress, but implicate nematodes and compromised sex steroid levels as potential threats to montane populations.

Assuntos

RESUMO

Aspects of how geospatial technologies can be used on visceral leishmaniasis (VL) control programs are discussed. We reviewed a number of papers discussing the usage of those technologies, through a PubMed literature review. Additionally, we provided conceptual elements for a development of a hierarchical scale framework on VL for decision making in São Paulo State, using Geographical Information Systems. Supported by Geospatial Techniques, we developed a view of some instruments for helping communities to better manage their risk areas. We used a classification called Strengths of GIS and Spatial Analysis in Epidemiology (SGISSAE). This review identified 50 papers published in the PubMed. With respect to developing the theoretical perspective, this paper can help to identify points of deficiency in shortage in discussions and leishmaniasis control programs, which led us to recommend future to delimitation studies to at community-based level and to define local actions to identify and manage the disease. In the conceptual framework data at community-based level will allow us to understand more broadly the changing spatial distribution of the disease.(AU)

Aspectos sobre como as tecnologias geoespaciais podem ser usadas nos programas de controle da leishmaniose visceral (LV) são discutidos. Nós confrontamos uma série de artigos discutindo o uso dessas tecnologias, através de uma revisão da literatura no PudMed. Adicionalmente, fornecemos elementos conceituais para o desenvolvimento de uma estrutura hierárquica sobre a escala na tomada de decisão sobre a leishmaniose no Estado de São Paulo, utilizando Sistemas de Informação Geográfica. Com o apoio das técnicas geoespaciais, desenvolvemos alguns instrumentos para ajudar as comunidades a gerenciar melhor suas áreas de risco. Usamos uma classificação chamada Forças do SIG e da análise espacial em Epidemiologia (SGISSAE). A revisão nos permitiu selecionar 50 artigos publicados no PubMed. Com relação ao desenvolvimento da perspectiva teórica, este artigo pode ajudar a identificar pontos de deficiência em discussões e programas de controle da leishmaniose, o que nos levou a recomendar futuros estudos de delimitação a nível comunitário e a definir ações locais para identificar e gerenciar a doença. No quadro conceptual, os dados ao nível da comunidade permitirão compreender mais amplamente a evolução da distribuição espacial da doença. (AU)

Assuntos

RESUMO

Implementation of a geospatial surveillance and response system data resource for vector borne disease in the Americas (GeoHealth) will be tested using NASA satellite data, geographic information systems and ecological niche modeling to characterize the environmental suitability and potential for spread of endemic and epizootic vector borne diseases. The initial focus is on developing prototype geospatial models for visceral leishmaniasis, an expanding endemic disease in Latin America, and geospatial models for dengue and other Aedes aegypti borne arboviruses (zika, chikungunya), emerging arboviruses with potential for epizootic spread from Latin America and the Caribbean and establishment in North America. Geospatial surveillance and response system open resource data bases and models will be made available, with training courses, to other investigators interested in mapping and modeling other vector borne diseases in the western hemisphere and contributing brokered data to an expanding GeoHealth data resource as part of the NASA AmeriGEOSS initiative.(AU)

A implementação de uma fonte de dados de vigilância e um sistema de resposta geoespacial para doenças transmitidas por vetores nas Américas (GeoHealth) será testada utilizando dados provenientes de satélites da NASA, sistemas de informações geográficas e modelagem do nicho ecológico, para caracterizar a suceptibilidade ambiental e o potencial de dispersão de doenças endêmicas e epizooticas transmitidas por vetores vetores. O foco inicial será o desenvolvimento de protótipos de modelos geoespaciais para a leishmaniose visceral, uma doença endêmica e em expansão na América Latina, e modelos geoespaciais para dengue e outros transmitidos pelo Aedes aegypti (zika, chikungunya), arbovírus emergentes com potencial para disseminação epizoótica pela América Latina e Caribe e estabelecimento na América do Norte. Sistemas de vigilância e resposta geoespacial e modelos de recursos em bases de dados abertas serão diponibilizados, com cursos de treinamento, para outros pesquisadores interessados em mapear e modelar outras doenças transmitidas por vetores no hemisfério ocidental e contribuir intermediando dados para uma fonte de dados GeoHealth em expansão, como parte da Iniciativa AmeriGEOSS, da NASA. (AU)

Assuntos

RESUMO

Aspects of how geospatial technologies can be used on visceral leishmaniasis (VL) control programs are discussed. We reviewed a number of papers discussing the usage of those technologies, through a PubMed literature review. Additionally, we provided conceptual elements for a development of a hierarchical scale framework on VL for decision making in São Paulo State, using Geographical Information Systems. Supported by Geospatial Techniques, we developed a view of some instruments for helping communities to better manage their risk areas. We used a classification called Strengths of GIS and Spatial Analysis in Epidemiology (SGISSAE). This review identified 50 papers published in the PubMed. With respect to developing the theoretical perspective, this paper can help to identify points of deficiency in shortage in discussions and leishmaniasis control programs, which led us to recommend future to delimitation studies to at community-based level and to define local actions to identify and manage the disease. In the conceptual framework data at community-based level will allow us to understand more broadly the changing spatial distribution of the disease.

Aspectos sobre como as tecnologias geoespaciais podem ser usadas nos programas de controle da leishmaniose visceral (LV) são discutidos. Nós confrontamos uma série de artigos discutindo o uso dessas tecnologias, através de uma revisão da literatura no PudMed. Adicionalmente, fornecemos elementos conceituais para o desenvolvimento de uma estrutura hierárquica sobre a escala na tomada de decisão sobre a leishmaniose no Estado de São Paulo, utilizando Sistemas de Informação Geográfica. Com o apoio das técnicas geoespaciais, desenvolvemos alguns instrumentos para ajudar as comunidades a gerenciar melhor suas áreas de risco. Usamos uma classificação chamada Forças do SIG e da análise espacial em Epidemiologia (SGISSAE). A revisão nos permitiu selecionar 50 artigos publicados no PubMed. Com relação ao desenvolvimento da perspectiva teórica, este artigo pode ajudar a identificar pontos de deficiência em discussões e programas de controle da leishmaniose, o que nos levou a recomendar futuros estudos de delimitação a nível comunitário e a definir ações locais para identificar e gerenciar a doença. No quadro conceptual, os dados ao nível da comunidade permitirão compreender mais amplamente a evolução da distribuição espacial da doença.

Assuntos