TreeKDE: clustering multivariate data based on decision tree and using one-dimensional kernel density estimation.

In this paper, we present an algorithm for clustering multidimensional data, which we named TreeKDE. It is based on a tree structure decision associated with the optimization of the one-dimensional kernel density estimator function constructed from the orthogonal projections of the data on the coordinate axes. Among the main features of the proposed algorithm, we highlight the automatic determination of the number of clusters and their insertion in a rectangular region. Comparative numerical experiments are presented to illustrate the performance of the proposed algorithm and the results indicate that the TreeKDE is efficient and competitive when compared to other algorithms from the literature. Features such as simplicity and efficiency make the proposed algorithm an attractive and promising research field, which can be used as a basis for its improvement, and also for the development of new clustering algorithms based on the association between decision tree and kernel density estimator.

Patrones de actividad de mamíferos alrededor de la línea transportadora de gas natural de Camisea en la Reserva Comunal Machiguenga, Cusco, Perú

En el presente trabajo se estudia la actividad horaria de los mamíferos que habitan el área circundante a la línea transportadora de gas de Camisea que atraviesa la Reserva Comunal Machiguenga. Desde febrero del 2020 hasta enero del 2021, se realizó un registro fotográfico mediante cámaras trampa dispuestas a lo largo de la tubería de gas. Los patrones de actividad se estimaron mediante la función de densidad de Kernel. Durante el periodo de estudio, se registraron 25 especies de mamíferos. Se encontró que Dasyprocta kalinowskii y Eira barbara presentan un patrón de actividad diurno; mientras que Cuniculus paca, Tapirus terrestris, Dasypus spp. y Mazama spp. presentan un patrón predominantemente nocturno. Se sugiere que los patrones de actividad observados estarían influenciados por varios factores como la exclusión competitiva entre D. kalinowskii y C. paca, disponibilidad estacional del alimento para T. terrestris, variación de temperatura y precipitación para Dasypus spp., restricciones filogenéticas en Mazama spp., y segregación temporal con otros carnívoros para E. barbara. Se destaca la importancia de la colaboración entre las empresas del rubro energético, las comunidades nativas y las organizaciones gubernamentales.

The present study investigates the hourly activity patterns of mammals inhabiting the area surrounding the Camisea gas pipeline that crosses the Machiguenga Communal Reserve. From February 2020 to January 2021, a photographic record was conducted using camera traps placed along the gas pipeline. Activity patterns were estimated using Kernel density functions. During the study period, 25 mammal species were recorded. It was found that Dasyprocta kalinowskii and Eira barbara exhibit a diurnal activity pattern, whereas Cuniculus paca, Tapirus terrestris, Dasypus spp., and Mazama spp. display predominantly nocturnal behavior. It is suggested that observed activity patterns could be influenced by various factors such as competitive exclusion between D. kalinowskii and C. paca, seasonal food availability for T. terrestris, temperature and precipitation variations for Dasypus spp., phylogenetic constraints in Mazama spp., and temporal segregation with other carnivores for E. barbara. The significance of collaboration between energy industry companies, native communities, and governmental organizations is emphasized.

Spatial Analysis in Areas with High Occurrence of Accidents Caused by Tityus serrulatus and Tityus bahiensis (Scorpiones: Buthidae) in Brazil.

INTRODUCTION: In Brazil, scorpion stings are recorded in high numbers with an increasing epidemiological situation in most municipalities. In the present study, data between 1998 and 2018 in Americana, São Paulo, were analyzed. METHODS: In total, 4122 records on scorpion stings were georeferenced using a Garmin eTREX 30X global positioning system device, with WGS84 datum projection and Universal Transverse Mercator zone 23S. Multiple Poisson regression was used to explore the relationship between the incidence rates of stings and urban planning areas (UPAs). Eight quantitative variables were used to establish the environmental and anthropic characterization of UPAs associated or not associated with scorpionism. A spatial analysis was performed for geoprocessing maps of Americana using spatial statistics tools (optimized hotspot analysis and kernel density function) from cartographic clusters in the ArcMap software, version 10.5. RESULTS: The optimized hotspot analysis tool identified spatial clusters with high values of the incidence of scorpion stings in the surroundings of all UPAs in the municipality. The estimation of the kernel function of event intensity showed a wide distribution of stings across the area of the entire municipal territory, with UPA-02 and UPA-06 exhibiting the highest occurrence of scorpion stings. Six significant hotspots were established as highest-event-density areas (with occurrences of 160-270) and were contiguous to 4 environmental protection areas, located in more peripheral regions, and to 2 municipal cemeteries, which were located in urban central areas. CONCLUSIONS: This analysis showed that the risk of scorpion stings in different Americana's UPAs has increased occurrence and incidence intensity.

Spatiotemporal Distribution of Leishmaniasis in an Endemic Area of Northeast Brazil: Implications for Intervention Actions.

This study aimed to analyze the spatiotemporal distribution of leishmaniases, and contribute to the knowledge of their epidemiological dynamics from 2007 to 2017 in the municipality of Caxias, Maranhão, Northeast Brazil. Data on American tegumentary leishmaniasis (ATL) and human visceral leishmaniasis (HVL) were obtained in the Epidemiological Surveillance Sector of Caxias, while data on canine visceral leishmaniasis (CVL) were obtained in the Zoonoses Surveillance Unit. For data analysis and spatial representation of leishmaniasis cases, the geoprocessing of the data was performed, and the geometric features of the state of Maranhão, Caxias, and the disease registration sites were obtained from the shapefile database of the Brazilian Institute of Geography and Statistics. Geostatistics was used to create maps based on the Kernel density method, starting from the points, producing a raster file for each case with several data frames, allowing the instantaneous comparison of the phenomena. During the study period, ATL, HVL, and CVL were reported in Caxias, accounting for 114,304 and 8,498 cases, respectively. The geoprocessing analysis showed that leishmaniasis is widely distributed in the urban area of Caxias. However, there are risk areas for the transmission of these diseases to humans and dogs, associated with deforestation and urban expansion, and may vary over time. Preventive measures must focus on risk areas, including conservation efforts and urban planning, in order to reduce the transmission of leishmaniases.

Investigating the Risk Factors Associated with Injury Severity in Pedestrian Crashes in Santiago, Chile.

Pedestrians are vulnerable road users that are directly exposed to road traffic crashes with high odds of resulting in serious injuries and fatalities. Therefore, there is a critical need to identify the risk factors associated with injury severity in pedestrian crashes to promote safe and friendly walking environments for pedestrians. This study investigates the risk factors related to pedestrian, crash, and built environment characteristics that contribute to different injury severity levels in pedestrian crashes in Santiago, Chile from a spatial and statistical perspective. First, a GIS kernel density technique was used to identify spatial clusters with high concentrations of pedestrian crash fatalities and severe injuries. Subsequently, partial proportional odds models were developed using the crash dataset for the whole city and the identified spatial clusters to examine and compare the risk factors that significantly affect pedestrian crash injury severity. The model results reveal higher increases in the fatality probability within the spatial clusters for statistically significant contributing factors related to drunk driving, traffic signage disobedience, and imprudence of the pedestrian. The findings may be utilized in the development and implementation of effective public policies and preventive measures to help improve pedestrian safety in Santiago.

MulticlusterKDE: a new algorithm for clustering based on multivariate kernel density estimation.

In this paper, we propose the MulticlusterKDE algorithm applied to classify elements of a database into categories based on their similarity. MulticlusterKDE is centered on the multiple optimization of the kernel density estimator function with multivariate Gaussian kernel. One of the main features of the proposed algorithm is that the number of clusters is an optional input parameter. Furthermore, it is very simple, easy to implement, well defined and stops at a finite number of steps and it always converges regardless of the data set. We illustrate our findings by implementing the algorithm in R software. The results indicate that the MulticlusterKDE algorithm is competitive when compared to K-means, K-medoids, CLARA, DBSCAN and PdfCluster algorithms. Features such as simplicity and efficiency make the proposed algorithm an attractive and promising research field that can be used as basis for its improvement and also for the development of new density-based clustering algorithms.

SARS-CoV-2 Transmission Risk Model in an Urban Area of Mexico, Based on GIS Analysis and Viral Load.

The COVID-19 pandemic highlighted health systems vulnerabilities, as well as thoughtlessness by governments and society. Due to the nature of this contingency, the use of geographic information systems (GIS) is essential to understand the SARS-CoV-2 distribution dynamics within a defined geographic area. This work was performed in Tepic, a medium-sized city in Mexico. The residence of 834 COVID-19 infected individuals was georeferenced and categorized by viral load (Ct). The analysis took place during the maximum contagion of the first four waves of COVID-19 in Mexico, analyzing 158, 254, 143, and 279 cases in each wave respectively. Then heatmaps were built and categorized into five areas ranging from very low to very high risk of contagion, finding that the second wave exhibited a greater number of cases with a high viral load. Additionally, a spatial analysis was performed to measure urban areas with a higher risk of contagion, during this wave this area had 19,203.08 km2 (36.11% of the city). Therefore, a kernel density spatial model integrated by meaningful variables such as the number of infected subjects, viral load, and place of residence in cities, to establish geographic zones with different degrees of infection risk, could be useful for decision-making in future epidemic events.

Bayesian Multi-Targets Strategy to Track Apis mellifera Movements at Colony Level.

Interactive movements of bees facilitate the division and organization of collective tasks, notably when they need to face internal or external environmental challenges. Here, we present a Bayesian and computational approach to track the movement of several honey bee, Apis mellifera, workers at colony level. We applied algorithms that combined tracking and Kernel Density Estimation (KDE), allowing measurements of entropy and Probability Distribution Function (PDF) of the motion of tracked organisms. We placed approximately 200 recently emerged and labeled bees inside an experimental colony, which consists of a mated queen, approximately 1000 bees, and a naturally occurring beehive background. Before release, labeled bees were fed for one hour with uncontaminated diets or diets containing a commercial mixture of synthetic fungicides (thiophanate-methyl and chlorothalonil). The colonies were filmed (12 min) at the 1st hour, 5th and 10th days after the bees' release. Our results revealed that the algorithm tracked the labeled bees with great accuracy. Pesticide-contaminated colonies showed anticipated collective activities in peripheral hive areas, far from the brood area, and exhibited reduced swarm entropy and energy values when compared to uncontaminated colonies. Collectively, our approach opens novel possibilities to quantify and predict potential alterations mediated by pollutants (e.g., pesticides) at the bee colony-level.

Intra-urban differentials of congenital and acquired syphilis and syphilis in pregnant women in an urban area in northeastern Brazil.

BACKGROUND: Currently syphilis is considered an epidemic disease worldwide. The objective of this study was to identify intra-urban differentials in the occurrence of congenital and acquired syphilis and syphilis in pregnant women in the city of Natal, in northeast Brazil. METHODS: Cases of syphilis recorded by the municipal surveillance system from 1 January 2011 to 30 December 2018 were analysed. Spatial statistical analyses were performed using the kernel density estimator of the quadratic smoothing function (weighted). SaTScan software was applied for the calculation of risk based on a discrete Poisson model. RESULTS: There were 2163 cases of acquired syphilis, 738 cases of syphilis in pregnant women and 1279 cases of congenital syphilis. Kernel density maps showed that the occurrence of cases is more prevalent in peripheral areas and in areas with more precarious urban infrastructure. In 2011-2014 and 2015-2018, seven statistically significant clusters of acquired syphilis were identified. From 2011 to 2014, the most likely cluster had a relative risk of 3.54 (log likelihood ratio [LLR] 38 895; p<0.001) and from 2015 to 2018 the relative risk was 0.54 (LLR 69 955; p<0.001). CONCLUSIONS: In the municipality of Natal, there was a clustered pattern of spatial distribution of syphilis, with some areas presenting greater risk for the occurrence of new cases.

Environmental and anthropogenic factors affecting nesting site selection by sea turtles.

Understanding the environmental and anthropogenic factors that affect nesting site selection by sea turtles is key to maintaining priority conservation areas. The species Lepidochelys olivacea, Caretta caretta, and Eretmochelys imbricata nest annually on the island of Comandatuba (Una, northeastern Brazil), where this survey was conducted. We evaluated the temporal and spatial distribution of nests during the seasons 2008/2009 to 2014/2015 and 2017/2018. In the last season, we further examined the environmental and anthropogenic factors that influence different nesting performances. We selected six sample areas with different nesting events (high, medium, and low), and recorded the following characteristics: beach slope, sediment grain size, vegetation richness, type of dune, anthropization, and final nest condition. A significant occurrence of nesting was observed in November and December . The spatial distribution of the nests varied over the seasons, with a greater tendency to nest in the south of the island. Higher frequency of anthropization and low slope of the beach were significant factors for areas with a smaller number of nests. Predation of turtle nests may be associated with areas of greater anthropization. Our findings have implications for the conservation and monitoring of nesting sites during reproduction seasons and provide further insight into the nesting dynamics of marginal sea turtle populations.

Spatial analysis of the COVID-19 distribution pattern in São Paulo State, Brazil / Análise espacial do padrão de distribuição do COVID-19 no Estado de São Paulo, Brasil

Abstract At the end of 2019, the outbreak of COVID-19 was reported in Wuhan, China. The outbreak spread quickly to several countries, becoming a public health emergency of international interest. Without a vaccine or antiviral drugs, control measures are necessary to understand the evolution of cases. Here, we report through spatial analysis the spatial pattern of the COVID-19 outbreak. The study site was the State of São Paulo, Brazil, where the first case of the disease was confirmed. We applied the Kernel Density to generate surfaces that indicate where there is higher density of cases and, consequently, greater risk of confirming new cases. The spatial pattern of COVID-19 pandemic could be observed in São Paulo State, in which its metropolitan region standed out with the greatest cases, being classified as a hotspot. In addition, the main highways and airports that connect the capital to the cities with the highest population density were classified as medium density areas by the Kernel Density method.It indicates a gradual expansion from the capital to the interior. Therefore, spatial analyses are fundamental to understand the spread of the virus and its association with other spatial data can be essential to guide control measures.

Resumo No final de 2019, o surto de COVID-19 foi relatado em Wuhan, China. O surto se espalhou rapidamente para vários países, tornando-se uma emergência de saúde pública de interesse internacional. Sem uma vacina ou medicamentos antivirais, medidas de controle são necessárias para entender a evolução dos casos. Neste estudo, relatamos por análise espacial o padrão espacial do surto do COVID-19. Nosso local de estudo foi no estado de São Paulo, Brasil, onde o primeiro caso da doença foi confirmado. Aplicamos o método "Kernel Density" para gerar superfícies que indicam onde há maior densidade de casos e, consequentemente, maior risco de confirmação de novos casos. O padrão espacial da pandemia de COVID-19 foi observado no estado de São Paulo, em que a região metropolitana do estado foi a que apresentou a maior quantidade de casos, sendo classificada como um "hot spot". Além disso, as principais rodovias e aeroportos que conectam a capital às cidades com maior densidade populacional foram classificadas como áreas de média densidade pelo método "Kernel Density". Isso indica uma expansão gradual da capital para o interior. Portanto, as análises espaciais são fundamentais para entender a disseminação do vírus e sua associação com outros dados espaciais pode ser essencial para orientar as medidas de controle.

Spatial patterns and interactions of dominant tree species in an Amazon tropical rainforest / Patrones e interacciones espaciales de especies arbóreas dominantes en un bosque tropical en la Amazonia

Abstract Knowledge of spatial patterns and interactions of tree species allows for understanding the ecological processes of spatiotemporal structures of tropical forests, becoming essential for the establishment of strategies for the conservation and management of their resources in the long term. The aim of this study was to investigate the spatial patterns and interactions of Astronium lecointei, Dinizia excelsa and Peltogyne paniculata, three dominant timber tree species in the Jamari National Forest, Rondônia, Brazilian Amazon. The Kernel estimator was used aiming to verify the possible influence of first-order factors on species distributions. Inhomogeneous K-functions were applied to analyze species spatial patterns and interactions by means of second-order factors. Univariate analyses revealed different scale-dependent spatial patterns for the species. Aggregation related to ecological characteristics, such as habitat preference and dispersal limitation, was verified for A. lecointei and P. paniculata. D. excelsa presented a random spatial pattern, explained by specific features of its establishment, such as the need for clearings due to light requirements. Interspecific associations were evidenced by bivariate analyses, in which spatial attraction of species resulted from the same preference for microhabitats and the repulsion was a result of niche segregation. Rev. Biol. Trop. 66(3): 1009-1017. Epub 2018 September 01.

Resumen El conocimiento de los patrones e interacciones espaciales de las especies arbóreas permite la comprensión de los procesos ecológicos de estructuración espacio-temporal de los bosques tropicales, tornándose imprescindible para el establecimiento de estrategias de conservación y manejo de sus recursos a largo plazo. El objetivo de este estudio fue investigar los patrones y las interacciones espaciales de Astronium lecointei, Dinizia excelsa y Peltogyne paniculata, tres especies arbóreas madereras dominantes en la Selva Nacional del Jamari, Rondônia, Amazonia Brasileña. Para ello, se utilizó el estimador Kernel, con el objetivo de verificar la posible influencia de factores de primer orden en la distribución de las especies. Para el análisis de los patrones e interacciones espaciales de las especies por medio de los factores de segundo orden, se empleó la función K no homogénea. Los análisis univariados revelaron diferentes patrones espaciales dependientes de la escala para las especies. Agregación relacionada a características ecológicas, como preferencia de hábitat y limitación de la dispersión, fue constatada para A. lecointei y P. paniculata. Dinizia excelsa presentó un patrón espacial aleatorio, explicado por características particulares de su establecimiento, como la necesidad de claros debido a sus requisitos lumínicos. Las asociaciones interespecíficas fueron evidenciadas por los análisis bivariados, en que la atracción espacial de las especies resultó de la misma preferencia por micro hábitats y la repulsión fue resultado de la segregación de nichos.

Health facility readiness and facility-based birth in Haiti: a maximum likelihood approach to linking household and facility data.

BACKGROUND: Haiti has one of the world's highest maternal mortality ratios. Comprehensive obstetric services could prevent many of these deaths, though most births in Haiti occur outside health facilities. Demand-side factors like a mother's socioeconomic status are understood to affect her access or choice to deliver in a health facility. However, analyses of the role of supply-side factors like health facility readiness have been constrained by limited data and methodological challenges. We sought to address these challenges and determine whether Haiti could increase rates of facility-based birth by improving facility readiness to provide delivery services. METHODS: Our task was to characterize facility delivery readiness and link it to nearby births. We used birth data from the 2012 Haiti DHS and facility data from the 2013 Haiti SPA. Our outcome of interest was facility-based birth. Our predictor of interest was delivery readiness at the DHS sampling cluster level. We derived a novel likelihood function that used Kernel Density Estimation to estimate cluster-level readiness alongside the coefficients of a logistic regression. RESULTS: We analyzed data from 389 facilities and 1,991 births. Rural facilities were less ready than urban facilities to provide delivery services. Women delivering in health facilities were younger, more educated, wealthier, less likely to live in rural areas, and had fewer previous children. Our model estimated that rural facilities (σ = 12.28, standard error [SE] = 0.16) spread their readiness over larger areas than urban facilities (σ = 7.14, SE = 0.016). Cluster-level readiness was strongly associated with facility-based birth (adjusted log-odds = 0.031; p = 0.005), as was socioeconomic status (adjusted log-odds = 0.78; p < 0.001). CONCLUSIONS: Health system policymakers in Haiti could increase rates of facility-based birth by supporting targeted interventions to improve facility readiness to provide delivery-related services, alongside efforts to reduce poverty and increase educational attainment among women.

Concentração intraurbana de população e empregos: os centros antigos das cidades brasileiras perderam primazia? / Intraurban concentration of people and jobs: have Brazilian inner cities lost their primacy? / ¿Concentración intraurbana de población y puestos de trabajo: los centros antiguos de las ciudades brasileñas perdieron primacía?

Os centros antigos das cidades são regiões internas às metrópoles que se destacam por seu valor simbólico e por estarem sujeitos à decadência e esvaziamento. Em geral, a configuração espacial da população e dos empregos determina a relevância locacional dos sítios urbanos, os fluxos de mobilidade e a própria vitalidade de cada porção urbana, inclusive o centro. Entretanto, informações de localização populacional intraurbana só são disponibilizadas a cada dez anos. Dados de localização de empregos, quando disponíveis, se encontram agregados e não estão georreferenciados. Nesse contexto, o presente trabalho analisa e identifica estruturas intraurbanas de população (1991, 2000 e 2010) e emprego (2002 e 2013), em 12 regiões metropolitanas brasileiras, utilizando áreas mínimas comparáveis para agregar dados populacionais censitários e geolocalização identificada de empregos. Os resultados indicam que há perda populacional nos centros metropolitanos no período 1991-2000, parcialmente recuperada no decênio seguinte. Constata-se ainda desconcentração de empregos com migração para novas áreas centrais, em relação aos centros urbanos tradicionais. Todavia, o comportamento não é linear para cada uma das 12 RMs analisadas e o resultado espacial final é específico para cada uma. O artigo contribui com a construção inédita da espacialização dos empregos para as 12 RMs. Ademais, a metodologia desenvolvida permite análise urbana quantitativa padronizada como apoio a pesquisadores com conhecimento local.

Historical city centers are those regions internal to a metropolis that deserve special attention since, despite their symbolic value, they are prone to fall into decadence and become abandoned. The spatial pattern of metropolitan population and employment determines the locational importance of urban sites, displacement flows and even the vitality of each urban portion of the territory, including the city center. In spite of that, intraurban population location data are available only every ten years. Data on job location, when available, are aggregated and not geocoded. In that context, this article analyses and identifies intraurban population (1991, 2000 and 2010) and employment (2002 and 2013) structures, for 12 Brazilian metropolitan areas, using (a) Minimum comparable Areas to aggregate population Census data and (b) jobs location with identification. Results indicate that there is population loss in metropolitan centers for the 1991-2000 period, partly recovered in the following decade. It is also verified that jobs have spread from traditional city centers, with migration to new central areas. Moreover, the behavior is not linear for each of the 12 areas analyzed and the final spatial result is specific to each of them. This article contributes with the original finding of the spatial location of jobs for the 12 metro areas. Finally, the methodology developed enables a standardized quantitative urban analysis which may support researchers with local knowledge.

Los centros antiguos de las ciudades son regiones internas de las metrópolis que se destacan por su valor simbólico y por estar sometidas a procesos de deterioro y abandono. En general, la configuración espacial de la población y de los empleos determina la relevancia de la ubicación de los sitios urbanos, los flujos de movilidad y la vitalidad propia de cada porción urbana, incluso para el análisis del centro. Asimismo, datos de ubicación poblacional intraurbana solamente están disponibles a cada diez años. Datos de ubicación de puestos de trabajo, de estar disponibles, se encuentran agregados y no están georreferenciados. En este contexto, este trabajo analiza e identifica estructuras intraurbanas de población (1991, 2000 y 2010) y empleo (2002 y 2013) en 12 regiones metropolitanas brasileñas, utilizando a) áreas mínimas comparables para agregar datos poblacionales censitarios y b) georreferenciación identificada de empleos. Los resultados indican que hay pérdida poblacional en los centros metropolitanos en el período 1991-2000, que se recupera parcialmente en el decenio siguiente. Además se constata la desconcentración de empleos con migración hacia nuevas áreas centrales en relación con los centros urbanos tradicionales. A su vez, el comportamiento de cada una de las 12 metrópolis analizadas no es lineal y el resultado espacial final es específico para cada una de ellas. El artículo contribuye con una construcción inédita de la espacialización de los puestos de trabajo para las 12 regiones metropolitanas. Por último, la metodología desarrollada permite el análisis urbano cuantitativo homogeneizado como apoyo a investigadores con conocimiento local.

Does Plan B work? Home range estimations from stored on board and transmitted data sets produced by GPS-telemetry in the Colombian Amazon / ¿Funciona el plan B? Estimación de rango de hogar a partir de datos almacenados en instrumentos a bordo de animales y los obtenidos a partir de telemetría satelital de GPS en el Amazonas colombiano

Abstract:Telemetry based on Global Positioning Systems (GPS) makes possible to gather large quantities of information in a very fine scale and work with species that were impossible to study in the past. When working with GPS telemetry, the option of storing data on board could be more desirable than the sole satellite transmitted data, due to the increase in the amount of locations available for analysis. Nonetheless, the uncertainty in the retrieving of the collar unit makes satellite-transmitted technologies something to take into account. Therefore, differences between store-on-board (SoB) and satellite-transmitted (IT) data sets need to be considered. Differences between SoB and IT data collected from two lowland tapirs (Tapirus terrestris), were explored by means of the calculation of home range areas by three different methods: the Minimum Convex Polygon (MCP), the Fixed Kernel Density Estimator (KDE) and the Brownian Bridges (BB). Results showed that SoB and IT data sets for the same individual were similar, with fix ranging from 63 % to 85 % respectively, and 16 m to 17 m horizontal errors. Depending on the total number of locations available for each individual, the home ranges estimated showed differences between 2.7 % and 79.3 %, for the 50 % probability contour and between 9.9 % and 61.8 % for the 95 % probability contour. These differences imply variations in the spatial coincidence of the estimated home ranges. We concluded that the use of IT data is not a good option for the estimation of home range areas if the collar settings have not been designed specifically for this use. Nonetheless, geographical representations of the IT based estimators could be of great help to identify areas of use, besides its assistance to locate the collar for its retrieval at the end of the field season and as a proximate backup when collars disappear. Rev. Biol. Trop. 64 (4): 1441-1450. Epub 2016 December 01.

Resumen:La telemetría basada en los sistemas de geopocisionamiento global (GPS) hace posible recopilar gran cantidad de información a escalas muy finas, y trabajar con especies imposibles de estudiar en el pasado. Al trabajar con telemetría de GPS, la opción de guardar información en la memoria interna del instrumento puede ser más deseable que sólo tener acceso a la información enviada vía satélite, debido a la mayor cantidad de localizaciones disponibles para analizar. No obstante, la incertidumbre de recuperar el collar hace que las tecnología de trasmisión vía satélite deba ser tenida en cuenta. Diferencias entre las bases de datos almacenadas en el collar (SoB) y las trasmitidas vía satélite (IT), recolectadas de dos individuos de Tapir de tierras bajas (Tapirus terrestris), son consideradas, en términos de las áreas de los rangos de hogar calculados con cada uno y mediante el uso de tres metodologías diferentes: Mínimo Polígono Convexo (MCP), Estimador de Densidad de Kernel Fijo (KDE) y los Puentes Brownianos (BB). Las bases de datos SoB e IT son similares, con tasas de acierto de localizaciones que oscilan entre 63 % to 85 % y errores horizontales de 16 m y 17 m respectivamente. Dependiendo del número total de localizaciones disponibles para cada individuo, los rangos de hogar estimados muestran diferencias entre 2.7 % y 79.3 %, para el contorno del 50 % de probabilidades, y entre 9.9 % y 61.8 % para el contorno del 95 % de probabilidades. Estas diferencias implican variaciones en la coincidencia espacial de los rangos de hogar estimados. Concluimos que el uso de la información trasmitida vía satélite no es una buena opción para la estimación de rangos de hogar, si la programción de los collares no ha sido diseñada específicamente para tal fin. Sin embargo, las representaciones geográficas de los estimados a partir de las bases de datos IT pueden ser de gran ayuda para la identificación de áreas de uso, además de su utilidad para la localización y recuperación de collares tras su liberación de los individuos monitoreados y como una base de datos de soporte en caso de pérdida del collar.

Spatial distribution of tuberculosis from 2002 to 2012 in a midsize city in Brazil.

BACKGROUND: Tuberculosis (TB) remains a major public health problem in many developing countries. Exploratory spatial analysis is a powerful instrument in spatial health research by virtue of its capacity to map disease distribution and associated risk factors at the population level. The aim of the present study was to describe the epidemiologic characteristics and spatial distribution of new cases of TB reported during the period 2002-2012 in Divinopolis, a midsized city located in the state of Minas Gerais, southeastern Brazil. METHODS: Sociodemographic and clinical data relating to the study cases were retrieved from the national Brazilian database and geocoded according to residential address. Choropleth and kernel density maps were constructed and a spatial-temporal analysis was performed. Tracts defined by the 2010 national census were classified as sectors with higher or lower densities of new TB cases based on the kernel density map. Multivariate logistic analysis was used to compare the two types of sectors according to income, level of literacy and population density. RESULTS: A total of 326 new cases of TB were reported during the study period. Residential addresses relating to 309 (94.8 %) of these were available in the SINAN database and the locations were geocoded and mapped. The average incidence of TB during the study period was 14.5/100,000 inhabitants. Pulmonary TB was the most predominant form (73.6 %) and 74.5 % of patients had been cured. The percentage of cases was highest in males (67.8 %) and individuals aged 25-44 years (41.1 %), and lowest in children aged less than 15 years (4.6 %). The disease was spatially distributed throughout the urban district. The incidence rate among urban census tracts ranged from 0.06 to 1.1 %, and the disease occurred predominantly in the downtown area (99.3 %). Higher population density was associated significantly with increased odds of living in a sector with a "higher density of cases", even after adjusting for income and education (odds ratio = 13.7). CONCLUSIONS: The highest density of cases was strongly associated with higher population density but not with lower income or level of literacy.

Foraging area fidelity for Kemp's ridleys in the Gulf of Mexico.

For many marine species, locations of key foraging areas are not well defined. We used satellite telemetry and switching state-space modeling (SSM) to identify distinct foraging areas used by Kemp's ridley turtles (Lepidochelys kempii) tagged after nesting during 1998-2011 at Padre Island National Seashore, Texas, USA (PAIS; N = 22), and Rancho Nuevo, Tamaulipas, Mexico (RN; N = 9). Overall, turtles traveled a mean distance of 793.1 km (±347.8 SD) to foraging sites, where 24 of 31 turtles showed foraging area fidelity (FAF) over time (N = 22 in USA, N = 2 in Mexico). Multiple turtles foraged along their migratory route, prior to arrival at their "final" foraging sites. We identified new foraging "hotspots" where adult female Kemp's ridley turtles spent 44% of their time during tracking (i.e., 2641/6009 tracking days in foraging mode). Nearshore Gulf of Mexico waters served as foraging habitat for all turtles tracked in this study; final foraging sites were located in water <68 m deep and a mean distance of 33.2 km (±25.3 SD) from the nearest mainland coast. Distance to release site, distance to mainland shore, annual mean sea surface temperature, bathymetry, and net primary production were significant predictors of sites where turtles spent large numbers of days in foraging mode. Spatial similarity of particular foraging sites selected by different turtles over the 13-year tracking period indicates that these areas represent critical foraging habitat, particularly in waters off Louisiana. Furthermore, the wide distribution of foraging sites indicates that a foraging corridor exists for Kemp's ridleys in the Gulf. Our results highlight the need for further study of environmental and bathymetric components of foraging sites and prey resources contained therein, as well as international cooperation to protect essential at-sea foraging habitats for this imperiled species.