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We present an assessment of several geospatial layers proposed as models for detecting clandestine graves in Mexico. The analyses were based on adapting the classical ROC curves to geospatial data (gROC) using the fraction of the predicted area instead of the false positive rate. Grave locations were obtained for ten Mexican states that represent the most conflicting regions in Mexico, and 30 layers were computed to represent geospatial models for grave detection. The gROC analysis confirmed that the travel time from urban streets to grave locations was the most critical variable for detecting graves, followed by nighttime light brightness and population density, whereas, contrary to the rationale, a previously proposed visibility index is less correlated with grave locations. We were also able to deduce which variables are most relevant in each state and to determine optimal thresholds for the selected variables.
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Sepultamento , México , Humanos , Densidade Demográfica , Curva ROCRESUMO
OBJECTIVE: To characterize patterns in the geospatial distribution of pre- and postnatally diagnosed congenital heart disease (CHD) across 6 surgical centers. STUDY DESIGN: A retrospective, multicenter case series from the Fetal Heart Society identified patients at 6 centers from 2012 through 2016 with prenatally (PrND) or postnatally (PoND) diagnosed hypoplastic left heart syndrome (HLHS) or d-transposition of the great arteries (TGA). Geospatial analysis for clustering was done by the average nearest neighbor (ANN) tool or optimized hot spot tool, depending on spatial unit and data type. Both point location and county case rate per 10â000 live births were assessed for geographic clustering or dispersion. RESULTS: Of the 453 CHD cases, 26% were PoND (n = 117), and 74% were PrND (n = 336). PrND cases, in all but one center, displayed significant geographic clustering by the ANN. Conversely, PoND cases tended toward geographic dispersion. Dispersion of PoND HLHS occurred in 2 centers (ANN = 1.59, P < .001; and 1.47, P = .016), and PoND TGA occurred in 2 centers (ANN = 1.22, P < .05; and ANN = 1.73, P < .001). Hot spot analysis of all CHD cases (TGA and HLHS combined) revealed clustering near areas of high population density and the tertiary surgical center. Hot spot analysis of county-level case rate, accounting for population density, found variable clustering patterns. CONCLUSION: Geographic dispersion among postnatally detected CHD highlights the need for a wider reach of prenatal cardiac diagnosis tailored to the specific needs of a community. Geospatial analysis can support centers in improving the equitable delivery of prenatal care.
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Cardiopatias Congênitas , Síndrome do Coração Esquerdo Hipoplásico , Humanos , Estudos Retrospectivos , Feminino , Gravidez , Síndrome do Coração Esquerdo Hipoplásico/epidemiologia , Síndrome do Coração Esquerdo Hipoplásico/diagnóstico , Cardiopatias Congênitas/epidemiologia , Cardiopatias Congênitas/diagnóstico , Recém-Nascido , Diagnóstico Pré-Natal/estatística & dados numéricos , Diagnóstico Pré-Natal/métodos , Estados Unidos/epidemiologia , Transposição dos Grandes Vasos/epidemiologia , Transposição dos Grandes Vasos/diagnóstico , Masculino , Análise Espacial , Sociedades MédicasRESUMO
Discerning the impact of anthropogenic impacts requires the implementation of bioindicators that quantify the susceptibilities and vulnerabilities of natural terrestrial and aquatic ecosystems to perturbation and transformation. Although legal regulations in Brazil recognize the value of bioindicators in monitoring water quality, the depreciation of soil conditions has yet to receive adequate attention. Thus, our study aimed to evaluate the potential of odonates (dragonflies and damselflies) as amphibiotic bioindicators to reflect the correlation between the degradation of aquatic and terrestrial habitats in pasture-dominated landscapes. We assessed the relationship between the biotic indices of Odonata and the conservation status of preserved riparian landscapes adjacent to anthropogenically altered pastures in 40 streams in the Brazilian savannah. Our results support the hypothesis that Odonata species composition may be a surrogate indicator for soil and water integrity, making them promising sentinels for detecting environmental degradation and guiding conservation strategies in human-altered landscapes. Importantly, while the Zygoptera/Anisoptera species ratio is a useful bioindicator tool in Brazilian forest, it is less effective in the open savannah here, and so an alternative index is required. Importantly, while the Zygoptera/Anisoptera species ratio is a useful bioindicator tool in Brazilian forest, it is less effective in the open savannah here, and so an alternative index is required. On the other hand, our results showed the Dragonfly Biotic Index to be a suitable tool for assessing freshwater habitats in Brazilian savannah. We also identified certain bioindicator species at both ends of the environment intactness spectrum.
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Monitoramento Ambiental , Água Doce , Odonatos , Solo , Animais , Brasil , Monitoramento Ambiental/métodos , Solo/química , EcossistemaRESUMO
Amid the surge in data volume generated across various fields of knowledge, there is an increasing necessity for advanced analytical methodologies to effectively process and utilize this information. Particularly in the field of animal health, this approach is pivotal for enhancing disease understanding, surveillance, and management. The main objective of the study was to conduct a comprehensive livestock and environmental characterization of Colombian municipalities and examine their relationship with the distribution of vesicular stomatitis (VS). Utilizing satellite imagery to delineate climatic and land use profiles, along with data from the Colombian Agricultural Institute (ICA) concerning animal populations and their movements, the research employed Principal Component Analysis (PCA) to explore the correlation between environmental and livestock-related variables. Additionally, municipalities were grouped through a Hierarchical Clustering process. The assessment of risk associated with VS was carried out using a Generalized Linear Model. This process resulted in the formation of four distinct clusters: three primarily characterized by climatic attributes and one predominantly defined by livestock characteristics. Cluster 1, identified as "Andino" due to its climatic and environmental features, exhibited the highest odds ratio for VS occurrence. The adopted methodology not only provides a deeper understanding of the local population and its context, but also offers valuable insights for enhancing disease surveillance and control programs.
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The dangerous chemical elements associated with nanoparticles (NPs) and ultra-fine sediment particles in hydrological bays have the capacity to move contaminants to large oceanic regions. The general objective of this study is to quantify the major chemical elements present in NPs and ultra-fine particles in aquatic sediments sampled from Guanabara Bay and compare these data to values determined through spectral optics using the Sentinel-3B Satellite OLCI (Ocean Land Color Instrument) during the winter and summer seasons of 2018, 2019, 2020, 2021, and 2022. This is done to highlight the impacts anthropogenic environmental hazards have on the marine ecosystem and human beings. Ten aquatic sediment field collection points were selected by triangulated irregular network (TIN). Samples were subjected to analysis by X-ray diffraction (XRD), scanning electron microscopy (SEM), electron dispersion spectroscopy (EDS), and transmission electron microscopy (TEM), which enabled a detailed analysis using scanning transmission electron microscopy (STEM). Geospatial analyses using Sentinel-3B OLCI Satellite images considered Water Full Resolution (WFR) at 300 m resolution, in neural network (NN), normalized at 0.83 µg/mg. A maximum average spectral error of 6.62% was utilized for the identification of the levels of Absorption Coefficient of Detritus and Gelbstoff (ADG443_NN) at 443 m-1, Chlorophyll-a (CHL_NN) (m-3), and Total Suspended Matter (TSM_NN) (g m-3) at 581 sample points. The results showed high levels of ADG443_NN, with average values as high as of 4444 m-1 (summer 2021). When related to the analyses of nanoparticulate sediments and ultrafine particles collected in the field, they showed the presence of major chemical elements such as Ge, As, Cr, and others, highly toxic to human health and the aquatic environment. The application of satellite and terrestrial surveys proved to be efficient, in addition to the possibility of this study being applied to other hydrological systems on a global scale.
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Monitoramento Ambiental , Sedimentos Geológicos , Nanopartículas , Rios , Sedimentos Geológicos/química , Rios/química , Imagens de SatélitesRESUMO
Cocaine trafficking threatens countries' national security and is a major public health challenge. Cocaine is transported from producer countries to consumer markets using various routes, methods, and transportation means. These routes develop in the geographical environment, are carefully planned and are geo-strategic objects that respond to the opportunities that drug trafficking organisations (DTOs) find to reduce the risks of interdiction. In this sense, individual drug seizure data (IDS) become essential indicators for identifying trends and understanding trafficking flows associated with drug trafficking routes. However, due to the illicit nature of DTOs, the availability of these data is considerably limited, hindering the ability to analyse and identify trends. This study presents a methodology for collecting and processing data from open-source information reported by Brazil's federal government news website. Using geospatial intelligence and natural language processing methods, we created a dataset with 939 records and 44 variables related to cocaine seizures in Brazil in 2022. We applied geospatial analysis techniques from this dataset to identify trends and potential cocaine trafficking flows. The results were broadly consistent with existing literature on drug trafficking. They demonstrated the potential of open-source information for environmental scanning and knowledge generation through geographic information science. The approach proposed in our research provides tools that can be used to complement drug trafficking monitoring and formulate public policies to strengthen prevention and enforcement strategies.
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Cocaína , Tráfico de Drogas , Humanos , Brasil , Processamento de Linguagem NaturalRESUMO
Using renewable energies is a global strategy to mitigate the acceleration of global warming generated by industrial processes and is a sustainable way to diversify the energy matrix in all countries. Biomass is a renewable energy source that produces biofuels and generates electricity and heat. The primary purpose of this work is to identify the municipalities in Colombia where agricultural, livestock, and urban residual biomass could be suitable for energy generation in a sustainable and renewable way. To that end, we carried out a Geostatistical Multi-Criteria Decision Methodology using Analytical Hierarchy Processes such as Rank-Sum and Weighted Linear Combination, as well as considering a set of sustainable development indicators applied to official Colombian data. Two scenarios are considered for comparison purposes. The first one is according to expert criteria, and the second one considers The Sustainable Development Goals proposed by the United Nations. Under both proposed scenarios, 127 municipalities were found to be suitable for agricultural-urban residual biomass and 162 for livestock-urban residual biomass for energy generation. One of the main limitations for the use of urban biomass is that municipalities need to have sufficient production potential to fulfill their own energy needs. An additional comparison with previous works to evaluate the performance of the Multi-Criteria Decision Methodologies MCDM is also proposed.
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Objetivo: Realizar un análisis geoespacial del comportamiENTo de sobrepeso y obesidad basado en la "Encuesta Nacional de Situación Nutricional" de 2015. Metodología: Se aplica un modelo de análisis geoespacial de distribución espacial trasversal a partir de la Encuesta, a escala departamENTal. Para lograrlo, se calculan las prevalencias de sobrepeso, obesidad clase i, ii y iii según el índice de masa corporal y la obesidad abdominal en mujeres y hombres de acuerdo con la circunferencia de cintura. Se utilizan herramiENTas de sistemas de información geográfica, como el índice de Moran Global, el índice local de autocorrelación espacial (lisa) y el G* Getis Ord, para determinar los patrones de agrupaciones altas y bajas prevalencias. Resultados: Los conglomerados locales ilustrados en los mapas demuestran que sus residuales están distribuidos normalmENTe en el espacio. Se observa una aleatoriedad en el modelo de la autocorrelación espacial. Las agrupaciones de lisa alta-alta se presENTan en diez departamENTos con estas condiciones (La Guajira, Magdalena, Atlántico, Sucre, Cesar, Norte de Santander, Córdoba, Antioquia, Chocó y Cundinamarca). Según el índice de masa corporal, el 38,5 por cada 100 habitantes tienen sobrepeso; el 20,9 por cada 100 habitantes presENTa obesidad, y según la circunferencia de cintura, 53,2 por cada 100 habitantes tiene obesidad abdominal. Conclusiones: La distribución espacial del sobrepeso y la obesidad puede estar condicionada con variables sociodemográficas tratadas en el estudio. El país tiene el reto de continuar implemENTando acciones poblacionales en salud pública para disminuir estas condiciones.
Objective: To carry out a geospatial analysis of the behavior of overweight and obesity based on the "National Survey of Nutritional Situation" of 2015. Methodology: A geospatial analysis model of transversal spatial distribution is applied from the Survey, on a departmENTal scale. To achieve this, the prevalence of overweight, class I, II and III obesity according to body mass index and abdominal obesity in women and men according to waist circumference are calculated. Geographic information system tools, such as the Global Moran Index, Local Spatial Autocorrelation Index (LISA), and G* Getis Ord, are used to determine patterns of high clustering and low prevalence. Results: The local clusters illustrated on the maps demonstrate that their residuals are normally distributed in space. A randomness is observed in the spatial autocorrelation model. High-high LISA clusters occur in ten departmENTs with these conditions (La Guajira, Magdalena, Atlántico, Sucre, Cesar, Norte de Santander, Córdoba, Antioquia, Chocó and Cundinamarca). According to the body mass index, 38.5 per 100 inhabitants are overweight; 20.9 per 100 inhabitants are obese, and according to waist circumference, 53.2 per 100 inhabitants have abdominal obesity. Conclusions: The spatial distribution of overweight and obesity may be conditioned by the sociodemographic variables treated in the study. The country has the challenge of continuing to implemENT population actions in public health to reduce these conditions.
Objetivo: Realizar uma análise geoespacial do comportamENTo do sobrepeso e da obesidade com base na "Pesquisa Nacional de Situação Nutricional" de 2015. Metodologia: Aplica-se um modelo de análise geoespacial de distribuição espacial transversal da Pesquisa, em escala departamENTal. Para isso, calcula-se a prevalência de sobrepeso, obesidade graus I, II e III segundo o índice de massa corporal e obesidade abdominal em mulheres e homens segundo a circunferência da cintura. As ferramENTas do sistema de informações geográficas, como o Índice de Moran Global, o Índice de Autocorrelação Espacial Local (Smooth) e o G* Getis Ord, são usadas para determinar padrões de alto agrupamENTo e baixa prevalência. Resultados: Os clusters locais ilustrados nos mapas demonstram que seus resíduos são normalmENTe distribuídos no espaço. Uma aleatoriedade é observada no modelo de autocorrelação espacial. Grupos de tainhas alto-alto ocorrem em dez departamENTos com essas condições (La Guajira, Magdalena, Atlântico, Sucre, Cesar, Norte de Santander, Córdoba, Antioquia, Chocó e Cundinamarca). De acordo com o índice de massa corporal, 38,5 por 100 habitantes estão acima do peso; 20,9 por 100 habitantes são obesos e, segundo a circunferência da cintura, 53,2 por 100 habitantes têm obesidade abdominal. Conclusões: A distribuição espacial do sobrepeso e da obesidade pode estar condicionada pelas variáveis sociodemográficas tratadas no estudo. O país tem o desafio de continuar implemENTando ações populacionais em saúde pública para reduzir esses agravos.
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Floods have caused socio-economic and environmental damage globally and, thus, require research. Several factors influence flooding events, such as extreme rainfall, physical characteristics, and local anthropogenic factors; therefore, such factors are essential for mapping flood risk areas and enabling measures that mitigate the damage they cause. This study aimed to map and analyze regions susceptible to flood risk in three different study areas belonging to the same Atlantic Forest biome, in which flood disasters are recurrent. Due to the presence of numerous factors, a multicriteria analysis using the Analytical Hierarchical Process was conducted. First, a geospatial database was composed of layers of elevation, slope, drainage distance, soil drainage, soil hydrological group, precipitation, relief, and land use and cover. Flood risk maps for the study area were then generated, and patterns in the study areas were verified, with the greatest influence being exerted by intense precipitation on consecutive days, elevation at the edges of the channel with low altimetric variation and a flat combination, densely built areas close to the banks of the main river, and an expressive water mass in the main watercourse. The results demonstrate that these characteristics together can indicate the occurrence of flooding events.
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Desastres , Inundações , Cidades , Brasil , EcossistemaRESUMO
Introducción: A finales de diciembre del 2019 comenzaron a ser reportados en la región asiática de Wuhan pacientes con una infección respiratoria aguda, de origen desconocido. Cuba no está exenta de esta situación. Los primeros casos de COVID-19 se diagnosticaron en el país el 11 de marzo del 2020. A partir de entonces se reportaron casos de la enfermedad en gran parte del país, La Habana fue una de las provincias más afectadas. Objetivo: Analizar la distribución geoespacial de la COVID-19 en La Habana. Método: Se realizó un estudio descriptivo en la provincia La Habana en el período marzo-julio del 2020. Resultados: Con la aparición de los primeros casos se observó un comportamiento homogéneo en todos los municipios de la capital, con mayor concentración en la zona central, siguió un patrón de distribución radial, respondiendo a dos variables que juegan un papel fundamental en el contexto actual: la densidad poblacional y el uso del suelo. Conclusiones: La vulnerabilidad al contagio en un territorio está dada por un grupo de variables y su interrelación, que hacen favorable a un territorio para la propagación y el contagio(AU)
Introduction: At the end of December 2019, patients with an acute respiratory infection, of unknown origin, began to be reported in the Asian region of Wuhan. Cuba was not exempt from this situation. The first cases of COVID-19 were diagnosed in the country on March 11, 2020. Since then, cases of the disease were reported in much of the country, with Havana being one of the hardest hit provinces. Objective: To analyze the geospatial distribution of COVID-19 in Havana. Method: A descriptive study was conducted in the province of Havana in the period March-July 2020. Results: With the appearance of the first cases, a homogeneous behavior was observed in all the municipalities of the capital, with a greater concentration in the central area, and it followed a radial distribution pattern, responding to two variables that play a fundamental role in the current context: population density and land use. Conclusions: The vulnerability to contagion in a territory is given by a group of variables and their interrelation, which make a territory favorable for the spread and contagion(AU)
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Humanos , Masculino , Feminino , COVID-19/epidemiologia , Epidemiologia Descritiva , Cuba , COVID-19/prevenção & controleRESUMO
Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review the existing evidence on the application of those geospatial techniques, tools, and methods in the coronavirus pandemic. We reviewed and retrieved nine research studies that directly used geospatial techniques, remote sensing, or satellite imaging as part of their research analysis. Articles included studies from Europe, Somalia, the USA, Indonesia, Iran, Ecuador, China, and India. Two papers used only satellite imaging data, three papers used remote sensing, three papers used a combination of both satellite imaging and remote sensing. One paper mentioned the use of spatiotemporal data. Many studies used reports from healthcare facilities and geospatial agencies to collect the type of data. The aim of this review was to show the use of remote sensing, satellite imaging, and geospatial data in defining features and relationships that are related to the spread and mortality rate of COVID-19 around the world. This review should ensure that these innovations and technologies are instantly available to assist decision-making and robust scientific research that will improve the population health diseases outcomes around the globe.
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COVID-19 , Tecnologia de Sensoriamento Remoto , Humanos , Tecnologia de Sensoriamento Remoto/métodos , Índia , China , EquadorRESUMO
INTRODUCTION: To optimize the early care of burned patients, protocols were developed that guide pre-hospital care and the need to transfer to a specialized burn treatment unit. Burn disasters are an important public health concern in developed and developing nations. Among the early steps in disaster preparedness is the understanding of geographic locations and capacity of burn care facilities. We aimed to map and classify medical facilities that provide burn care in Brazil and to undertake a location-allocation analysis to identify which could be targeted to increase capacity. METHODS: A review of burn hospitalizations was conducted using Brazilian Ministry of Health data. Capacity was defined by number of burn patients admitted each year and bed type. Spatial population data per one-square kilometer were obtained from World Pop as a raster dataset. A road network dataset using Open Street Map data was created to conduct the drive time analysis. Location/allocation analysis was conducted to identify the proportion of Brazil's population living within 2- and 6-hours' drive time of a burn care capable hospital, stratified by the level of hospital capacity. Hospitals were ranked according to number of additional people served. RESULTS: We found 26.471 burn admissions. Of these, 3.508(13,2 %) were ICU admissions. A total of 735(2,7 %) hospital deaths occurred under the selected burn codes. In all, 1.273 facilities admitted burn patients, and 263(20,7 %) reported ICU admissions of burn patients. Seventeen hospitals were classified as maximum capacity facilities. Additional 23 hospitals were identified as potential targets for capacity building. Most maximum capacity hospitals are clustered in the Southeast of Brazil. Currently, 40.8 % of the Brazilian population live within 2 h of a maximum capacity facility. A large part of the population lives farther than 6 h away from a maximum capacity hospital. Most of the potential targets for capacity building are located near the coast of Brazil. DISCUSSION: We mapped and classified facilities that provide public burn care in Brazil. We identified public facilities that could be targeted to increase capacity to improve access for patients in the event of a burn disaster. Mapping, planning, and coordinating response is key for optimal outcomes in Mass Casualties Incidents. Cataloging and understanding local resources is a crucial first step in disaster management. Inequality in profiles can determine specific regional needs. Specialized burn centers are rare in regions other than the southeast. Health equity should be considered when planning disaster preparedness initiatives. Location-allocation modelling may assist in universal and equitable burn care service offerings. CONCLUSION: This study proposes an initial step in the classification and mapping of available burn treatment centers and population coverage in Brazil.
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Queimaduras , Planejamento em Desastres , Incidentes com Feridos em Massa , Humanos , Brasil/epidemiologia , Queimaduras/epidemiologia , Queimaduras/terapia , Unidades de QueimadosRESUMO
Microbialites provide a record of the interaction of microorganisms with their environment constituting a record of microbial life and environments through geologic time. Our capacity to interpret this record is limited by an incomplete understanding of the microbial, geochemical, and physical processes that influence microbialite formation and morphogenesis. The modern system Laguna Negra in Catamarca Province, Argentina contains microbialites in a zone of carbonate precipitation associated with physico-chemical gradients and variable microbial community structure, making it an ideal location to study how these processes interact to drive microbialite formation. In this study, we investigated the geospatial relationships between carbonate morphology, geochemistry, and microbial community at the macro- (decimeter) to mega- (meter) scale by combining high-resolution imagery with field observations. We mapped the distribution of carbonate morphologies and allochtonously-derived volcaniclasts and correlated these with sedimentary matrices and geochemical parameters. Our work shows that the macroscale distribution of different carbonate morphologies spatially correlates with microbial mat distributions-a result consistent with previous microscale observations. Specifically, microbialitic carbonate morphologies more commonly occur associated with microbial mats while abiotically derived carbonate morphologies were less commonly associated with microbial mats. Spatial variability in the size and abundance of mineralized structures was also observed, however, the processes controlling this variability remains unclear and likely represent a combination of microbial, geochemical, and physical processes. Likewise, the processes controlling the spatial distribution of microbial mats at Laguna Negra are also unresolved. Our results suggest that in addition to the physical drivers observed in other modern environments, variability in the spatial distribution of microbialites and other carbonate morphologies at the macro- to megascale can be controlled by microbial processes. Overall, this study provides insight into the interpretation of microbialite occurrence and distributions in the geologic record and highlights the utility of geospatial statistics to probe the controls of microbialite formation in other environments.
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Sedimentos Geológicos , Microbiota , Sedimentos Geológicos/química , Argentina , CarbonatosRESUMO
BACKGROUND: The composite coverage index (CCI) provides an integrated perspective towards universal health coverage in the context of reproductive, maternal, newborn and child health. Given the sample design of most household surveys does not provide coverage estimates below the first administrative level, approaches for achieving more granular estimates are needed. We used a model-based geostatistical approach to estimate the CCI at multiple resolutions in Peru. METHODS: We generated estimates for the eight indicators on which the CCI is based for the departments, provinces, and areas of 5 × 5 km of Peru using data from two national household surveys carried out in 2018 and 2019 plus geospatial covariates. Bayesian geostatistical models were fit using the INLA-SPDE approach. We assessed model fit using cross-validation at the survey cluster level and by comparing modelled and direct survey estimates at the department-level. RESULTS: CCI coverage in the provinces along the coast was consistently higher than in the remainder of the country. Jungle areas in the north and east presented the lowest coverage levels and the largest gaps between and within provinces. The greatest inequalities were found, unsurprisingly, in the largest provinces where populations are scattered in jungle territory and are difficult to reach. CONCLUSIONS: Our study highlighted provinces with high levels of inequality in CCI coverage indicating areas, mostly low-populated jungle areas, where more attention is needed. We also uncovered other areas, such as the border with Bolivia, where coverage is lower than the coastal provinces and should receive increased efforts. More generally, our results make the case for high-resolution estimates to unveil geographic inequities otherwise hidden by the usual levels of survey representativeness.
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Serviços de Saúde da Criança , Criança , Recém-Nascido , Humanos , Peru , Teorema de Bayes , Saúde da Criança , Características da FamíliaRESUMO
Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and processing multi-source data to generate risk predictors and consuming significant time and computational resources to train and validate models locally. In this context, this study proposed a framework for dengue risk prediction by integrating big geospatial data cloud computing based on Google Earth Engine (GEE) platform and artificial intelligence modeling on the Google Colab platform. It enables defining the epidemiological calendar, delineating the predominant area of dengue transmission in cities, generating the data of risk predictors, and defining multi-date ahead prediction scenarios. We implemented the experiments based on weekly dengue cases during 2013-2020 in the Federal District and Fortaleza, Brazil to evaluate the performance of the proposed framework. Four predictors were considered, including total rainfall (Rsum), mean temperature (Tmean), mean relative humidity (RHmean), and mean normalized difference vegetation index (NDVImean). Three models (i.e., random forest (RF), long-short term memory (LSTM), and LSTM with attention mechanism (LSTM-ATT)), and two modeling scenarios (i.e., modeling with or without dengue cases) were set to implement 1- to 4-week ahead predictions. A total of 24 models were built, and the results showed in general that LSTM and LSTM-ATT models outperformed RF models; modeling could benefit from using historical dengue cases as one of the predictors, and it makes the predicted curve fluctuation more stable compared with that only using climate and environmental factors; attention mechanism could further improve the performance of LSTM models. This study provides implications for future dengue risk prediction in terms of the effectiveness of GEE-based big geospatial data processing for risk predictor generation and Google Colab-based risk modeling and presents the benefits of using historical dengue data as one of the input features and the attention mechanism for LSTM modeling.
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Aprendizado Profundo , Dengue , Humanos , Brasil/epidemiologia , Dengue/epidemiologia , Inteligência Artificial , Ferramenta de Busca , PrevisõesRESUMO
Introducción: El año 2015 es el marco de referencia temporal internacional para evaluar las acciones de la estrategia Fin a la tuberculosis. La eliminación de la enfermedad como problema de salud requiere de la identificación de poblaciones y territorios en mayor riesgo, y de los determinantes de su distribución geográfica. Objetivo: Determinar la influencia de factores socioeconómicos, demográficos y geoespaciales en la distribución espacial de la tuberculosis en La Habana en el año 2015. Métodos: Se realizó un estudio ecológico. Se describió la distribución espacial del total de casos de tuberculosis, la confección TB/VIH y los casos TB/reclusos a nivel de municipio; así como de variables socioeconómicas, demográficas y geoespaciales con datos disponibles de todos los municipios de la provincia. Se realizaron mapas temáticos para cada una de las variables. Posteriormente, se realizó un análisis de superposición de capas. Resultados: Se observó una mayor concentración de casos en el centro-sur de la provincia; principalmente en los municipios Centro Habana, Habana Vieja, Diez de Octubre y Boyeros, a excepción de este último, estos municipios son los más densamente poblados, los que tienen mayor ocupación del suelo y condiciones de vida más desfavorables. Conclusiones: La distribución espacial de la tuberculosis en La Habana está estrechamente relacionada al comportamiento de variables socioeconómicas, demográficas y geoespaciales en sus diferentes municipios. Estas variables deben ser tomadas en cuenta en intervenciones de salud dirigidas a la eliminación de la enfermedad en la provincia(AU)
Introduction: The year 2015 constitutes the international time frame of reference to evaluate the actions of the End tuberculosis strategy. The elimination of the disease as a health problem requires the identification of populations and territories at greatest risk, and the determinants of their geographical distribution. Objective: Determine the influence of socio-economic, demographic and geospatial factors on the spatial distribution of tuberculosis in Havana in 2015. Methods: An ecological study was conducted. The spatial distribution of total TB cases, TB/HIV and TB/inmate cases at the municipality level was described; as well as socio-economic, demographic and geospatial variables with data available from all municipalities in the province. Thematic maps were made for each of the variables. Subsequently, a layer overlap analysis was performed. Results: A higher concentration of cases was observed in the center-south of the province; mainly in the municipalities of Centro Habana, Habana Vieja, Diez de Octubre and Boyeros ; with the exception of the latter, these municipalities are the most densely populated, those with the highest land occupation and the most unfavorable living conditions. Conclusions: The spatial distribution of tuberculosis in Havana is closely related to the behavior of socio-economic, demographic and geospatial variables in its different municipalities. These variables should be taken into account in health interventions aimed at eliminating the disease in the province(AU)
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Humanos , Masculino , Feminino , Condições Sociais , Tuberculose/prevenção & controle , Sistemas de Informação Geográfica , Estudos EcológicosRESUMO
Yam (Dioscorea spp.) is an important crop for smallholder farmers in the Northeast region of Brazil. Wherever yam is grown, diseases caused by yam mosaic virus (YMV) are prevalent. In the present study, the diversity of YMV infecting Dioscorea cayennensis-rotundata was analyzed. In addition, five species of Dioscorea (D. alata, D. altissima, D. bulbifera, D. subhastata, and D. trifida) commonly found in Brazil were analyzed using ELISA and high-throughput sequencing (HTS). YMV was detected only in D. cayennensis-rotundata, of which 66.7% of the samples tested positive in ELISA. Three YMV genome sequences were assembled from HTS and one by Sanger sequencing to group the sequences in a clade phylogenetically distinct from YMV from other origins. Temporal phylogenetic analyses estimated the mean evolutionary rate for the CP gene of YMV as 1.76 × 10-3 substitutions per site per year, and the time to the most recent common ancestor as 168.68 years (95% Highest Posterior Density, HPD: 48.56-363.28 years), with a most likely geographic origin in the African continent. The data presented in this study contribute to reveal key aspects of the probable epidemiological history of YMV in Brazil.
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Dioscorea , Potyvirus , Brasil , Filogenia , Doenças das Plantas , Potyvirus/genéticaRESUMO
Background: Two-hour and 30 min travel times to a hospital capable of performing emergency general surgery and cesarean section are benchmarks for timely surgical access. This study aimed to estimate the population of Guatemala with timely access to surgical care and identify existing hospitals where the expansion of surgical services would increase access. Methods: The World Federation of Societies of Anaesthesiologists (WFSA) Anesthesia Facility Assessment Tool (AFAT) previously identified 37 public Guatemalan hospitals that provide surgical care. Nine additional public non-surgical hospitals were also identified. Geospatial analysis was performed to estimate walking and driving geographic access to all 46 hospitals. We calculated the potential increase in access that would accompany the expansion of surgical services at each of the nine non-surgical hospitals. Findings: The percentage of the population with walking access to a surgical hospital within 30 min, 1 h, and 2 h are 5·1%, 12·9%, and 27·3%, respectively. The percentage of people within 30 min, 1 h, and 2 h driving times are 27·3%, 41·1%, and 53·1%, respectively. The median percentage of the population within each of Guatemala's 22 administrative departments with 2 h walking access was 19·0% [IQR 14·1-30·7] and 2 h driving access was 52·4% [IQR 30·5-62·8]. Expansion of surgical care at existing public Guatemalan hospitals in Guatemala would result in a minimal increase in overall geographic access compared to current availability. Interpretation: While Guatemala provides universal health coverage, geographic access to surgical care remains inadequate. Geospatial mapping and survey data work synergistically to assess surgical system strength and identify gaps in geographic access to essential surgical care. Funding: None.
RESUMO
OBJECTIVE: To describe the use and frequency of use of mobile apps (internetand/ or smartphone-based geospatial networking apps) among men who have sex with men (MSM) and how these platforms are used to engage with sexual partners in PR. METHODS: A local module including questions regarding mobile apps and sexual engagement and derived from the 2017 Puerto Rico National HIV Behavioral Surveillance System, fifth MSM cycle, was used for this analysis. A subsample of 127 eligible participants was recruited through venue-based sampling and assented to participate. Univariate analysis was used to evaluate sociodemographic and behavioral characteristics, HIV testing, and the ways in which mobile apps are used to find sexual partners. RESULTS: The participants' median age was 35 years, with a standard deviation of ±11.37 years. Most of our sample (97%) had had anal sex with at least 1 partner in the last 12 months, and 76% of them had had condomless anal sex. Over three fourths (81%) reported using apps for sexual encounters, while 45% stated that the most frequently used app was Grindr. Of the participants who had used apps for sexual encounters, 57% had met 5 or more sexual partners through apps in their lifetime. CONCLUSION: This study shows that there is a need for further research to understand the habits of this population in PR regarding the use of apps to find sexual partners and, also, as a possible way to develop strategies for prevention and health promotion in this group.
Assuntos
Homossexualidade Masculina/psicologia , Aplicativos Móveis , Mídias Sociais , Rede Social , Adulto , Infecções por HIV/epidemiologia , Infecções por HIV/prevenção & controle , Humanos , Internet , Masculino , Porto Rico , Comportamento Sexual , Parceiros Sexuais , SmartphoneRESUMO
Towards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a campaign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts from 771 health facilities reporting from across the country throughout the 6-year period from January 2014 to December 2019. To this end, a novel hierarchical Bayesian modelling framework was developed in which a latent, pixel-level incidence surface with spatio-temporal innovations is linked to the observed case data via a flexible catchment sub-model designed to account for the absence of data on case household locations. These maps have focussed the delivery of indoor residual spraying and focal mass drug administration in the Grand'Anse Department in South-Western Haiti.