Spatiotemporal Pattern of Thyroid Cancer Incidence in South Kerala: A Population-based Study

Background: Thyroid cancer (TC) is the most common endocrine cancer and has been increasing over the past decades worldwide. A notable finding is that Kerala’s capital Thiruvananthapuram ranks the first among men and the second highest among women in the incidence of TC in India. Reasons for this increase have not been established. Objectives: Here, we investigated the spatiotemporal pattern of TC incidence in Thiruvananthapuram. Materials and Methods: TC incidence data (n = 1937) of Population Based Cancer Registry Thiruvananthapuram, Kerala, India, between 2012 and 2016, were analyzed for identifying geographical patterns by spatial methods, temporal methods for studying spatial variation in TC incidence, distribution of age, gender, and histology in lowland (coastal), midland, and highland. Results: Spatial clustering of TC incidence was identified consistently near the coastal region based on all geospatial analyses. 56.9%, 23.9%, and 19.2% of TC cases were observed in the coastal, midland, and highland areas, respectively. A significant clustered pattern of TC incidence was revealed by Moran’s index I (0.49), high-high clusters by local Moran’s, hotspot by Getis-Ord-Gi* (P < 0.05), point pattern analysis by nearest neighbor ratio and kernel density estimation. The relative risk of the significant cluster was obtained as 1.60 (95% confidence interval: 1.03–1.84) by SaTScan analysis. Conclusion: This study identified spatial variations in the pattern of TC cases with significant clusters near the coastal region of Thiruvananthapuram. This would help to pinpoint the high-risk geographical areas of TC and for more effective cancer control programs.

Factores asociados a la distribución espacial de la tuberculosis en La Habana, 2015 / Factors associated with the spatial distribution of tuberculosis in Havana, 2015

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)

Geospatial analysis of severe road traffic accidents in Singapore in 2013-2014

INTRODUCTION@#Injury is a significant cause of mortality and morbidity. We aimed to investigate which areas in Singapore have a significantly higher incidence of road traffic accidents (RTA) resulting in severe injuries (Tier 1), which is defined as an Injury Severity Score (ISS) greater than 15, and to develop a spatiotemporal model.@*METHODS@#Data was obtained from the National Trauma Registry. The RTA locations were geomapped onto the Singapore map, and spatial statistical techniques were used to identify hotspots with the Getis-Ord Gi* algorithm.@*RESULTS@#From 1 January 2013 to 31 December 2014, there were 35,673 people who were injured as a result of RTAs and 976 Tier 1 RTA victims. A total of 920 people were included in the geospatial analysis. Another 56 were involved in RTAs that did not occur within Singapore or had missing location data and thus were not included. 745 (81.0%) were discharged alive, whereas 175 (19.0%) did not survive to discharge (median ISS 38.00, interquartile range 30.00-48.00). Most of the Tier 1 RTA victims were motorcycle riders (50.1%, n = 461), pedestrians (21.8%, n = 201) and cyclists (9.9%, n = 91). The majority were male and aged 20-40 years, and there was a peak occurrence at 0600-0759 hours. Nine hotspots were identified (p < 0.01).@*CONCLUSION@#Information from studying hotspots of RTAs, especially those resulting in severe injuries, can be used by multiple agencies to direct resources efficiently.

Assessment of TerraClass and MapBiomas data on legend and map agreement for the Brazilian Amazon biome

Reliable environmental monitoring and evaluation require high-quality maps of land use and land cover. For the Amazon biome, the TerraClass and MapBiomas projects apply different methodologies to create these maps. We evaluated the agreement between land cover and land use maps generated by TerraClass and MapBiomas (Collections 2 and 3) for the Brazilian Amazon biome, from 2004 to 2014. Specifically, we: (1) described both project legends based on the LCCS (Land Cover Classification System); (2) analyzed the differences between their classes; and (3) compared the mapping differences among the Brazilian states that are totally or partially covered by the Amazon biome. We compared the classifications with a per-pixel approach and performed an evaluation based on agreement matrices. The overall agreement between the projects was 87.4% (TerraClass x MapBiomas 2) and 92.0% (TerraClass x MapBiomas 3). We analyzed methodological differences to explain the disagreements in class identification. We conclude that using these maps together without a properly adapted legend is not recommended for the analysis of land use and land cover change. Depending on the application, one mapping system may be more suitable than the other. (AU)

Design, Characterization and Geospatial Analysis of Physical and Socio-economic Indicators of Anthropogenic Pressures on Protected Areas in Africa

In Africa, the important agro-pastoral activity and poverty in rural areas lead to strong anthropogenic pressures on protected areas and to their quick degradation. Therefore the efficient conservation and sustainable exploitation of protected areas require adaptive and dynamic management that integrates peripheral interactions with regard to their changing spatial and temporal dimensions. They call for the deployment of appropriate management indicators capable of translating all the issues raised into concrete and practical terms. To this end, a new conceptual and analytical approach to assess pressure indicators is needed to take into account the spatio-temporal oscillation or mobility of the area of ​​socio-economic dependence that must henceforth provide the basis for sustainable management in the context of adaptation to climate change. The study responds to this concern through rigorous conceptualization, characterization and validation of original peripheral pressure indicators focused on a global and dynamic socio-economic framework. The method used consisted of an interpretative analysis of theoretical bibliographic data, measurements and field observations using GPS, ArcGIS 10.1 and Envi 4.5 and semi-structured interviews for the characterization of defined pressure indicators and their field validation. The five pressure indicators designed and applied on the basis of the criteria of direct dependence on protected areas are the coefficient of asymmetry (Kc), the periphery (Ψ), the dependent population (Dπ), the distance-access time (DAT) and the field daily working time (FDWT). The approach and pressure indicators were successfully applied to the Rusizi National Park (Burundi) for the period 1984-2015. The results showed that the park has a coefficient of asymmetry of 2.64 which represents a three times higher level than its circular equivalent, a periphery of 13.23 km radius composed of 35 localities characterized by distance-access times comprise between 0 to 2 h 30 and field daily working times ranging from 7 to 11 hours. They revealed that nearly 70% of peripheral populations are concentrated within 6 km from the boundaries and have distance-access times of less than one hour. The peripheral dependence on Rusizi Park reaches 100% for woody resources, 97% for livestock products, 88% for agricultural resources and 83% for animal protein products. The modeling of potential pressures and field observations showed that peripheral localities are the more threatening that they are more dependent, more populated and closer to the park. As a consequence, the important anthropogenic pressures led to a very significant degradation of the park during the study period.