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ObjectiveTo analyze the multimorbidity and comorbid disease patterns among middle-aged and older adults aged 50 years and above in China and to study the prevalence， regional distribution， and relationship with health-related outcomes of major comorbid disease patterns. MethodsThe fourth national follow-up data of the China Health and Retirement Longitudinal Study （CHARLS） 2018 was used， including 13 774 respondents aged 50 years and older from 28 provincial units. We analyzed 14 patient-reported physician-diagnosed chronic diseases and multimorbidity combinations， reported prevalence， composition ratio， and regional distribution. Differences in health loss and risk factors between high morbidity groups were analyzed using chi-square tests and logistic regression. ResultsThe prevalence of multimorbidities among participants was 57.3%. The single disease with high prevalence included arthritis/rheumatism （6.47%）， hypertension （5.41%）， and gastric and digestive disorders （4.17%）； the binary multimorbidity combinations were arthritis + digestive disorders （3.06%）， arthritis + hypertension （2.61%）， and hypertension + hyperlipidemia （1.39%）； the triadic combinations were hypertension + digestive disorders + joint disorders （1.00%）. The prevalence of multimorbidity varied greatly between provinces， showing the characteristics of high in the west and north but low in the east and south China. Significant differences in the health loss caused by different multimorbidity combinations were noted， with the highest ADL loss （28.51%） and depression （77.68%） caused by the arthritis multimorbidity combinations （P<0.01）. The number of chronic diseases （OR=6.71， P<0.01）， age （OR=1.96， P<0.01）， and heavy alcohol consumption were comorbid risk factors for physical and mental health； exercise （OR=0.44， P<0.01） and sleep （OR=0.89， P<0.01） were protective factors for physical and mental health， and smoking cessation （OR=0.76， P<0.01） contributed to the relief of anxiety. ConclusionsThe prevalence of comorbid patterns showed a high clustering trend， and the health loss caused by major patterns varied greatly. Relevant health intervention strategies should prioritize the major multimorbidity combinations for targeted disease management and rehabilitation services.
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En la sociedad de hoy los delitos vienen incrementándose y particularmente en la ciudad de Bogotá, lo que ha causado muchos inconvenientes a la Policía Nacional de Colombia, así como también a los centros de seguridad ciudadana. Ante esta situación, se ha propuesto una predicción de tiempo-espacio en los puntos críticos de crímenes y delitos, con la ayuda de inteligencia artificial. Por consiguiente, este trabajo tiene como objetivo analizar, resumir, interpretar y evaluar las distintas técnicas de predicción espacio-temporal de la delincuencia con un panorama inteligente. Por la propia naturaleza de la investigación, se utilizó una metodología de enfoque descriptivo-cualitativo, con la cual se diseñaron fichas de observación estructurada para sistematizar información de cinco bases de datos: Scopus, Web of Science, IEEE, ACM, Springer; dichas publicaciones comprenden desde 2019 hasta junio de 2021. En consecuencia, se encontraron en total 3015 estudios, después del proceso de cribado y verificación de los criterios de exclusión e inclusión, se seleccionaron 132 artículos, luego se aplicaron preguntas Psicólogo Interno Residente (PIR), quedando así 18 artículos. Los principales hallazgos encontrados indican que los algoritmos de redes neuronales resultaron ser uno de los métodos más eficaces para la detección de puntos críticos de delincuencia, dado que los grandes avances de la tecnología coadyuvarían en los próximos años a predecir de forma rápida y eficaz los actos delictivos y los crímenes ubicados en cualquier región del continente latinoamericano.
In today's society, crimes are increasing, particularly in the city of Bogota, which has caused many inconveniences to the National Police of Colombia, as well as to the citizen security centers. Given this situation, a time-space prediction of crime and crime hotspots has been proposed with the help of artificial intelligence. Therefore, this paper aims to analyze, summarize, interpret and evaluate the various techniques of space-time prediction of crime with an intelligent view. Due to the very nature of the research, a descriptive-qualitative approach methodology was used, with which structured observation sheets were designed to systematize information from five da-tabases: Scopus, Web of Science, IEEE, ACM, Springer; these publications span from 2019 to June 2021. Consequently, a total of 3015 studies were found, after the screening process and verification of exclusion and inclusion criteria, 132 articles were selected, then questions were applied Psychologist Internal Resident (PIR), thus leaving 18 articles. The main findings indicate that neural network algorithms proved to be one of the most effective methods for the detection of crime hotspots, given that the great advances in technology would help in the coming years to quickly and effectively predict criminal acts and crimes located in any region of the Latin American continent.
Na sociedade de hoje, a criminalidade está aumentando, particularmente na cidade de Bogotá, o que tem causado muitos inconvenientes para a Polícia Nacional Colombiana, bem como para os centros de segurança do cidadão. Diante desta situação, foi proposta uma previsão tempo-espacial de hotspots de crime com a ajuda da inteligência artificial. Portanto, este documento visa analisar, resumir, interpretar e avaliar as diversas técnicas de previsão espaço-temporal do crime com uma visão inteligente. Devido à própria natureza da pesquisa, foi utilizada uma metodologia de abordagem descritiva-qualitativa, com a qual foram elaboradas fichas de observação estrutura-das para sistematizar informações de cinco bancos de dados: Scopus, Web of Science, IEEE, ACM, Springer; estas publicações abrangem o período de 2019 a junho de 2021. Consequentemente, foi encontrado um total de 3015 estudos, após o processo de triagem e verificação dos critérios de exclusão e inclusão, 132 artigos foram selecionados, depois foram aplicadas perguntas ao Psicólogo em Residência (PIR), deixando 18 artigos. As principais descobertas indicam que os algoritmos de redes neurais provaram ser um dos métodos mais eficazes para a detecção de hotspots de crime, dado que os grandes avanços na tecnologia ajudarão nos próximos anos a prever rápida e efetivamente atos criminosos e crimes localizados em qualquer região do continente latino-americano.
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Humans , Artificial Intelligence , Crime , Criminal Behavior , Safety , Algorithms , Police , ColombiaABSTRACT
Introduction: The prediction of potential fishing areas is considered one of the most immediate and practical approaches in fisheries and is an essential technique for decision-making in managing fishery resources. It helps fishermen reduce their fuel costs and the uncertainty of their fish catches; this technique allows to contribute to national and international food security. In this study, we build different combinations of predictive statistical models such as Generalized Linear Models and Generalized Additive Models. Objective: To predict the spatial distribution of PFZs of the dolphinfish (Coryphaena hippurus L.) in the Colombian Pacific Ocean. Methods: We built different combinations of Generalized Linear Models and Generalized Additive Models to predict the Catch Per Unit Effort of C. hippurus captured from 2002 to 2015 as a function of sea surface temperature, chlorophyll-a concentration, sea level anomaly, and bathymetry. Results: A Generalized Additive Model with Gaussian error distribution obtained the best performance for predicting PFZs for C. hipurus. Model validation was performed by calculating the Root Mean Square Error through a cross-validation approach. The R2 of this model was 50 %, which was considered suitable for the type of data used. January and March were the months with the highest Catch per Unit Effort values, while November and December showed the lower values. Conclusion: The predicted PFZs of C. hippurus with Generalized Additive Models satisfactorily with the results of previous research, suggesting that our model can be explored as a tool for the assessment, decision making, and sustainable use of this species in the Colombian Pacific Ocean.
Introducción: La predicción de zonas potenciales de pesca se considera uno de los enfoques más inmediatos y efectivos en las pesquerías, es una técnica importante para la toma de decisiones en el manejo de los recursos pesqueros. Ayuda a los pescadores a reducir su costo de combustible y también a disminuir la incertidumbre de sus capturas, esta técnica permite contribuir a la seguridad alimentaria nacional e internacional. En este estudio, se construyeron diferentes combinaciones de modelos estadísticos predictivos como modelos lineales generalizados y modelos aditivos generalizados. Objetivo: predecir la distribución espacial de las zonas potenciales de pesca del pez dorado (Coryphaena hippurus L.) en el Pacífico colombiano. Métodos: La variable de respuesta se expresó en escala de captura por unidad de esfuerzo, es decir, el número de individuos de C. hippurus capturados por un número total de anzuelos disponibles entre 2002 y 2015. Temperatura de la superficie del mar, concentración de clorofila, anomalía del nivel del mar y batimetría, se utilizaron como variables explicativas para los meses de estacionalidad de C. hippurus (noviembre - marzo). Resultados: El modelo con mejor rendimiento para la predicción de zonas potenciales de pesca fue un modelo aditivo generalizado con distribución de error gaussiana y función de enlace de registro, que se seleccionó en función del criterio de información de Akaike, el R2 y la desviación explicada. La validación del modelo se realizó calculando el error cuadrático medio a través de un enfoque de validación cruzada. El ajuste de este modelo fue del 50 %, lo que puede considerarse adecuado para el tipo de datos utilizados. Enero y marzo fueron los meses con mayor captura por unidad de esfuerzo y noviembre-diciembre los meses con menor. Conclusión: Las zonas potenciales de pesca previstas coincidieron satisfactoriamente con investigaciones anteriores, lo que sugiere que nuestro modelo es una herramienta poderosa para la evaluación, toma de decisiones y uso sostenible de los recursos pesqueros de C. hippurus en el Pacífico colombiano.
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Animals , Fishing Industry , Forecasting , Colombia , Geographic Information SystemsABSTRACT
Problem: Bird migration (eye): Georeferencing procedure with clues, rules, functionalities, and restrictions, for avian navigation and nest nidification.Literature Knowledge: Computer vision (sensor): Robot self-referencing with the Perspective-n- Point pose estimation technique.Aim: Hypothesis introduction and proving (“The birds also follow the same georeferencing procedure like robots in avian navigation and nest nidification”).Methodology: (a) Reference data, images, and photography acquisition and 4-means layering (eBird dataset, Flickr imagery, CORINE land covering, and Volunteered Geographic Information);(b) Image processing; and (c) GIS spatial overlay analysis.Results: Statistical spatial analysis using data of the GIS overlays (the 4 layers). Correlation matrix (Avian navigation and nest nidification in low-density urban areas as these are affected by spatial linear geometries and land cover types).Conclusion: A statistically satisfactory approach to the introduced hypothesis.Potential Applications: Human spatial cognition and movement behavior; Children’s motor control and coordination.
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Modifications of land use and vegetation cover are proceeding faster than ever before in human history, with a considerable reduction in forest cover in biodiversity hotspots. We investigated the land use and vegetation cover changes, their impact on biodiversity in the Kurram District, Pakistan, for 27 years (1989 to 2015). Temporal satellite imagery was processed using a supervised maximum likelihood classification algorithm in ARCGIS 10.1 to elucidate information regarding land use/land cover changes,with conducted structured interviews to obtain the inhabitants' perspectives on their dependence on ecosystems in Kurram, and how their environment is changing. We found that the land under forest cover and rangeland showed a remarkable decrease over the study period. This decline in rangeland and forest cover was a result of the increased of farmland, barren land. The study area is part of a biodiversity, with important medicinal, rare and unique plant species.
Las modificaciones del uso de la tierra y la cobertura vegetal están avanzando más rápido que nunca en la historia de la humanidad, con una reducción considerable de la cobertura forestal en los puntos críticos de biodiversidad. Investigamos el uso de la tierra y los cambios en la cobertura vegetal, su impacto en la biodiversidad en el distrito de Kurram, Pakistán, durante 27 años (1989 a 2015). Las imágenes satelitales temporales se procesaron utilizando un algoritmo de clasificación de máxima verosimilitud supervisada en ARCGIS 10.1 para dilucidar información sobre los cambios en el uso del suelo/cobertura del suelo, con entrevistas estructuradas realizadas para obtener las perspectivas de los habitantes sobre su dependencia de los ecosistemas en Kurram y cómo está cambiando su entorno. Descubrimos que la tierra cubierta por bosques y pastizales mostró una disminución notable durante el período de estudio. Esta disminución en los pastizales y la cubierta forestal fue el resultado del aumento de las tierras de cultivo, tierras estériles. El área de estudio es parte de una biodiversidad, con importantes especies de plantas medicinales, raras y únicas.
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Land Use , Natural Resources Exploitation , Biodiversity , Pakistan , Pasture , Ecosystem , Agriculture , Satellite ImageryABSTRACT
ABSTRACT Biomethane can readily replace fossil fuels including natural gas, which has similar physical and chemical properties. In Brazil, municipal solid waste is predominantly disposed of in landfills. Landfill gas is mostly employed for electricity generation, but still at low levels when compared to the existing potential. Production of biomethane from landfill gas may be an alternative to exploit the existing potential, but Brazil's pipeline network is rather limited and concentrated along the country's coast. In this context, the research sought to identify the locational viability of using landfill gas to produce biomethane and injecting it into pipelines, considering the available potential and its proximity to Brazil's existing pipeline network. The QGis software was used to integrate the information. Territorial arrangements with a biomethane production capacity of more than 15,000 Nm3 day−1 and located up to 50 km from the pipeline network were considered feasible. The research estimated a potential production equivalent to 3,407,027 Nm3 day−1 of biomethane from landfills in Brazil. This potential corresponds to 6% of country's natural gas consumption in 2019 and is almost 32 times greater than current production of biomethane from all substrates used with this purpose in that year. The results indicate the suitability of using geographic information systems to identify regions that can benefit from the production of biomethane from landfill gas using the existing natural gas pipelines as an alternative to the electricity generation and provides relevant subsidies to the formulation of more efficient public policies in both the sanitation and energy sectors.
RESUMO O biometano pode substituir facilmente os combustíveis fósseis, incluindo o gás natural, que possui propriedades físicas e químicas similares. No Brasil, os resíduos sólidos urbanos são descartados predominantemente em aterros sanitários. O gás dos aterros sanitários é empregado principalmente na geração de eletricidade, mas ainda em níveis baixos quando comparado ao potencial existente. A produção de biometano a partir do gás de aterro pode ser uma alternativa para explorar o potencial existente, mas a rede de gasodutos do Brasil é bastante limitada e concentrada ao longo da costa do país. Nesse contexto, esta pesquisa buscou identificar a viabilidade locacional do uso de gás de aterro sanitário para produzir biometano e injetá-lo em dutos, considerando o potencial disponível e sua proximidade com a rede de dutos existente no Brasil. O software QGis foi utilizado para integrar as informações. Foram considerados viáveis arranjos territoriais com uma capacidade de produção de biometano maior que 15.000 Nm3 dia−1 e localizados a até 50 km da rede de gasodutos. A pesquisa estimou uma produção potencial equivalente a 3.407.027 Nm3 dia−1 de biometano a partir de aterros sanitários no Brasil. Esse potencial corresponde a 6% do consumo de gás natural do país em 2019 e é quase 32 vezes maior que a produção de biometano de todos os substratos utilizados com essa finalidade naquele ano. Os resultados indicam a adequação do uso de sistemas de informação geográfica para identificar regiões que podem se beneficiar da produção de biometano a partir de gás de aterro sanitário, utilizando os gasodutos de gás natural existentes como alternativa à geração de eletricidade e fornece subsídios relevantes para a formulação de políticas públicas mais eficientes, tanto no setor de saneamento quanto no de energia.
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ABSTRACT Knowledge about the spatial distribution of fruit flies (Diptera: Tephritidae) and tritrophic interactions (fruit-fruit fly parasitoid) contributes to the monitoring and maintenance of the numerical density at a level lower than economic damage. The purpose of this study was to identify the spatial distribution and associations of fruit flies with their parasitoids and host plants in the municipality of Bom Jesus-PI. The flies were obtained from fruit collection from July 2018 to May 2019. A total of 1,711 individuals were obtained, represented by six species: Anastrepha obliqua (Macquart, 1835), An. fraterculus (Wiedemann, 1830), An. alveata Stone, 1942, An. sororcula Zucchi, 1979, An. zenildae Zucchi, 1979 and Ceratitis capitata (Wiedemann, 1824). Anastrepha obliqua was the species with the widest distribution throughout the ecotone area. Ceratitis capitata is distributed only in the urban perimeter. A tritrophic relationship occurred between four species of parasitoids, Asobara anastrephae (Muesebeck, 1958) or Opius sp. associated with An. obliqua in Spondias mombin or S. tuberosa fruits. Opius sp. has also been associated with An. alveata in Ximenia americana. Pachycrepoideus vindemiae was obtained from C. capitata in Malpighia emarginata, in addition to An. obliqua in Averrhoa carambola. Therefore, fruit flies are associated with native fruit trees (S. tuberosa, S. mombin, S. purpurea, P. acutangulum, Inga laurina, X. americana) and exotic fruits (M. emarginata, A. carambola, P. guajava). Ceratitis capitata was recorded for the first time in the state of Piauí infesting I. laurina (Sw.) Willd. This is the first record of the parasitoid genus Spalangia. in An. obliqua in Piauí and in the semiarid region of Brazil.
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@#Introduction: Dengue fever (DF) is a prominent vector-borne disease spread by mosquitos of the Aedes genus (mainly Aedes aegypti, and even Aedes albopictus), a tropical regions vector. The purpose of this research was to establish the spatial and temporal distribution patterns of DF cases in the study area between 2010 and 2020. Methods: The correlation between the Kuantan sub-district and dengue haemorrhagic fever (DHF) incidence is examined in this study using spatial analysis. The correlation was calculated using spatial autocorrelation, Moran’s Index (Moran’s I) and Spatial Autocorrelation of Local Indicators (LISA). Moran’s index is a worldwide indicator used to determine whether or not disease transmission has geographical autocorrelation in disease transmission. Results: The results indicated that between 2011 and 2020, the monthly Moran’s I of dengue transmission in Kuantan was estimated to range between -0.685 and 0.338. The lowest reading of Moran’s index was -0.685 in May 2015, whereas the highest reading was 0.338 in May 2019. This reflects the strong spatial autocorrelation of dengue transmission in Kuantan over the last decade. The LISA analysis revealed significant spatial autocorrelations on DF cases in Kuantan for three (3) out of six (6) sub-districts (50%) with a significance level of 2%. This suggests that there are spatial autocorrelations in Kuala Kuantan, Beserah and Penor sub-district that influence the distribution of DHF transmission. Conclusion: The results reveal that the spatial autocorrelation analysis method can be a tool for relevant researchers to understand the pattern of DF transmission study and establish the direction for further study.
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【Objective】 To apply the spatial distribution analysis based on ArcGIS software, which has been applied widely in other fields, so as to analyze the intended locations for whole blood donation. 【Methods】 After a random stratified sampling was conducted among blood donors in the 17 donation sites during August 1st, 2021- July 30th, 2022, their intended blood donation locations were collected by an e-questionnaire. Addresses of donors′ intended donation locations were derived for GCJ-02 coordinates form and transformed by pandas module of Python to WGS84 coordinates, which further loaded to ArcGIS Arcmap module using Grouping Analysis for 17 median centers. The addresses of 17 blood donation sites in Guangzhou Blood Center were transformed to WGS84 coordinates and loaded to ArcGIS Arcmap module using the same methods for 3 ring buffer analysis. The criterion for judging whether the two were " matched" was whether the intended blood donation sites were covered by or adjacent to the 3 ring buffer zone of the existing blood donation sites. 【Results】 Of the 17 potential sites obtained from the spatial distribution analysis of 40 523 valid addresses of donors, 8 sites were covered or adjacent to the buffer of the existing donation sites, while the other 9 sites were far away from the existing donation sites. 【Conclusion】 By analyzing the spatial distribution of donors′ intended donation addresses, we can find out the service needs of donors for donating blood conveniently, which can provide basis for further blood donation service optimization.
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Introduction: To visualize the damage to primary care facilities in Miyazaki prefecture caused by the Nankai Trough earthquake by collating GIS data and to propose feasible countermeasures based on the estimated damage.Methods: The merged data of the estimated tsunami damage downloaded from the service for numerical information on national land use created by the Ministry of Land, Infrastructure, Transport and Tourism were combined with the data of medical institutions collected from the regional medical information system of the Japan Medical Association.Results: Of the 721 clinics and 140 hospitals, 139 clinics and 31 hospitals were affected, with 521 and 4,713 beds, respectively. By medical area, regions in which more than 50% of the clinics and hospitals were affected included the northern region of Nobeoka Nishi-usuki (clinics, 58.7%; hospitals, 60.0%) and Hyuga Irigo (clinics, 84.2%; hospitals, 61.5%), revealing a disproportionate estimate of damage.Conclusion: To deal with long-term damage, joint operation among regional facilities in neighboring prefectures is essential for a community continuity plan. Care facilities can take initiatives for cooperative disaster risk reduction planning with residents.
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@#Introduction: A cross-sectional study was conducted to determine the associations of socio-demographic factors, eating behaviours, fast food purchasing by parents for family meals, and availability of neighbourhood fast-food outlets with BMI-for-age z-score (BAZ) among adolescents. Methods: Through multi-stage stratified cluster sampling method, a total of 420 adolescents from five selected public secondary schools participated in the current study. Data on socio-demographic factors, eating behaviours, and parent’s purchases of fast food were obtained through selfadministered questionnaires. The availability of fast-food outlets was assessed using Geographic Information System (GIS). Body weight and height of the adolescents were measured. Results: The prevalence of overweight, obesity, thinness and severe thinness among adolescents in the present study were 17.6%, 15.5%, 3.1% and 0.7%, respectively. The current findings showed that a higher monthly household income (rs =0.12, p=0.02) and less purchases of fast food by parents for family meals (rs =-0.11, p=0.03) were significantly associated with higher BAZ of the adolescents. However, there were no significant associations between eating outside of home, eating at fast-food restaurants, buying delivery fast food, and availability of neighbourhood fast-food outlets with BAZ. Multiple linear regression showed that less purchases of fast food by parents for family meals significantly contributed towards higher BAZ (β=−0.25, p=0.02). Conclusion: A higher household income and less fast food purchasing by parents were associated with higher BAZ. Fast food purchasing of adolescents were not associated with BAZ. Therefore, an appropriate obesity intervention programme should focus on adolescents and their parents from middle- and high-income households in Labuan.
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Introduction: Flood is one of the climate change induced hazards occurring in most parts of the world. It exposes humanity and many socio-ecological systems to various levels of risks. In Nigeria, extreme rainfall events and poor drainage system have caused inundation of several settlements to flooding. To contain the disaster, risk mapping were among the measures recommended. Aims: The aim of this paper is to highlight flood risk zones (FRZ) in Uhunmwonde Local Government Area (LGA), Edo State, Nigeria. Methodology: Flood risk (FR) was mapped using hazards and vulnerability and implemented using geographic information system (GIS)-based multi-criteria analysis analytic hierarchy process (MCA-AHP) framework by incorporating seven environmental and two socio-economic factors. Elevation, flow accumulation, soil water index of wettest quarter, normalized difference vegetation index, rainfall of wettest quarter, runoff of wettest quarter and distance from rivers constituted the hazard component while population density and area of agricultural land use was the vulnerability layer. The climate change induced flood risk was validated using the responses of 150 residents in high, moderate and low flood risk zones. Results: The resulting flood risk map indicated that about 40.4% of Uhunmwonde LGA fell within high flood risk zone, 35.3% was categorized under moderate flood risk zone whereas low flood risk zone extended up to about 24.3% of the LGA. The high number of respondents who reported occurrence of flooding with frequency being very often and the fact that flooding was a very serious environmental threat during on-the-spot field assessment validated the generated climate change induced flood risk. Conclusion: The utilitarian capabilities of GIS-based MCA-AHP framework in integrating remotely-sensed biophysical and climate change related flood inducing indicators with socio-economic vulnerabilities to arrive at composite flood risk was demonstrated.
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Introduction:Geographical Information System (GIS) has proven to be very useful for large scale mapping of ecosystems, land use and cover, disease prevalence, risk mapping and forecasting. GIS establish relationship or link between vector borne diseases and associated environmental factors thereby providing explanation for spatial distribution pattern, possible causes of diseases outbreak andimplications on the community.Aims and Objectives:Our approach in this study was to define and identify areas and places that are exposed to Malaria risk through proximity analysis and to compare geospatial risk with laboratory diagnosed malaria epidemiology. Methodology:Garmin GPS was used to capture the geographic coordinates of six (6) selected settlements and overlaid with georeferenced and processed satellite images in the study area. GIS modeling was performed on risk factors using weighted overlay technique to produce malaria risk map. A total of One hundred and thirty-five (135) vulnerable individuals were diagnosed for Malaria with light Olympus microscope and rapid diagnostic kit (RDT). Data were entered and analyzed using R-Package for Statistical Computing and Graphics.Results:Proximity to malaria risk follows relatively the order Apodu > Central Malete > Elemere > KWASU Campus > Gbugudu. Apodu being the largest place with proximity to malaria risk, within 500m radius. The risk index increases as one move away from the center of the settlement. The possible explanation for this high risk could be the presence of pond / lake in Apodu. This is a good breeding site for mosquito couple with dense vegetation as one move away from the centre of the settlements. Unlike Apodu, Gbugudu was at medium risk at 100m buffer (60%) but the risk index decreases as one move away from the settlement centre. The absence of thick vegetation and presence of numerous open farms and partly cultivated farmlands on the eastern part could have been responsible for reduction in risk index. Dense vegetation and ponds were observed within Apodu, while Central Malete was built up with dense vegetation are possible reasons for the high-risk index, while settlements within 1 km radius around KWASU campus recorded lower risk index possibly dueto low vegetation. The geospatial malaria risk analysis correlates with the laboratory-based test results. RDT kits and light microscopy results showed Apodu having the highest malaria prevalence with 46% and 58.7% followed by Elemere 41% and 30.3% respectively. When calculating prevalence by aggregating results across all communities, Apodu still had the highest malaria prevalence for the whole region. RDT and light microscopy results combined for all communities had Apodu with malaria prevalence of 21.48% and 27.4% followed by Elemere with 11.85% and 12.5% respectively. Gbugudu had the least malaria prevalence within the region with 3.7% and 7.4% respectively.Discussion and Conclusion:Findings of this study showed dense vegetation and ponds within Apodu, Elemere and Central Malete served as good breeding site for mosquitoes and were responsible for the high-risk index at these areas. Settlements within 1 km radius around KWASU campus recorded lower index possibly due to low vegetation. Results from this study indicate that the degree of malaria parasitaemia in the three major settlements correlates directly with the remote sensing data
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Supportive supervision is one of the most important tasks in health systems management. A baseline assessment conducted by the primary health care transformation initiative had shown that the Gurage Zone health department had been conducting regular supportive supervision every quarter for the last five years in Gurage Zone. The study proposed establishing a feedback auditing system as an intervention to routinely assess the progress of previous visit actions included in the written feedback. The finding showed the culture of working on previous supportive supervision action items by woreda (district) health offices were significantly improved
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Objective To explore the epidemic characteristics and spatial clustering of pulmonary tuberculosis in Wuhan from 2011 to 2019, and to provide a scientific basis for formulating intervention strategies and measures. Methods Descriptive statistical analysis was conducted on the epidemic characteristics of tuberculosis data in Wuhan registered in the national tuberculosis information management system in the last 9 years, and spatial autocorrelation analysis was performed on the incidence of tuberculosis in 155 communities or in the city using Arcgis10.5 software. Results From 2011 to 2019, there were 56,432 cases of tuberculosis reported in Wuhan, and the annual average reported incidence rate of tuberculosis was 59.24/100 000. The overall incidence rate showed a fluctuating downward trend, with an average annual decline rate of 1.99%. The ratio of the number of cases between men and women was 2.35:1, and the incidence rate in males was higher than that in females (χ2=285.36，P0,P<0.001), and the high-high aggregation areas of tuberculosis were mainly distributed in Erqi community, Baibuting community, Liujiaoting community, Yijiadun community, Heping Street, Changqian Street, Tonghu farm, Yuxian Town, Zhifang Town, Wulijie Town, Fenghuang Street, Liji Street, and Daoguanhe Street. Conclusion The overall epidemic situation of pulmonary tuberculosis in Wuhan showed a slow downward trend. The main population and the clustering time of cases were relatively fixed, and the overall epidemic showed a certain spatial clustering. Active screening should be carried out for high-risk populations and high-aggregation areas, and effective prevention and control strategies should be developed based on time and location classification.
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@#Introduction: The trend of several mosquito-borne diseases in Malaysia has shown an increasing pattern over the past few years despite close monitoring and continuous control initiatives by public health authority. The objective of this study is to determine the spatial and temporal epidemiology of mosquito-borne disease in Terengganu from the year 2009 to 2018. Terengganu has been selected because it is geographically unique and experiences two monsoon seasons per year. Methods: Weekly surveillance data of mosquito-borne diseases which include dengue fever, malaria, filariasis, Japanese Encephalitis (JE) and chikungunya from 2009 to 2018 were collected from the Terengganu State Health Department. The variables included in the dataset mainly comprises of disease onset, diagnosis, case category, area (district) and site of onset. The data has been monitored spatial and temporal in which to explore the distribution pattern of the disease. The annual average for each type of mosquito-borne disease was determined using time-series and is further analysed by using geographical information system (GIS) tools to form spatial statistical analysis. Results: Results indicate that the temporal distribution of the mosquito-borne disease in Terengganu increases slightly despite a fluctuating pattern from the year 2009 to 2018 and there are between each type of mosquito-borne disease. Spatial analysis showed different stratification between seasons as well as the areas that are more susceptible to each disease. Conclusion: The results obtained in this present study through spatial and temporal analysis revealed that mosquito-borne diseases show a dynamic pattern in distribution. It can be concluded that the occurrence of the diseases depends on the geographical area and the weather within the region. This study provides public health authorities with a comprehensive assessment that will be useful for surveillance and monitoring, as well as for predicting and managing mosquito-borne disease outbreaks effectively
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Zha-xun is widely used in Tibetan medicine and is also an international traditional medicine. This study believes that the black organic matter constituting Zha-xun is mainly stored in the rocks. The exudation points of Zha-xun mostly distribute on the cliffs of high mountains, which makes it difficult to evaluate its resource distribution and storage area. This paper was aimed at the exudation environment of Tibetan medicine Zha-xun in Sichuan province and 6 ecological environmental factors of the Zha-xun were determined via the field investigation. Combining with these 6 factors as well as the GIS data of Sichuan province, ArcGIS software was used to extract ideal environmental factors which are suitable for exudation of Zha-xun, including geology types, geomorphological types, altitude, slope, vegetation types, and mean annual temperature. The spatial overlay analyses on the extracted environmental factors were carried out to predict the distribution area of Zha-xun in Sichuan province. Afterwards, field investigation was conducted to verify the prediction. The prediction showed that the exudation spots of Zha-xun in Sichuan province mainly located in 29 counties including 12 in Aba Prefecture, 15 in Ganzi Prefecture, and Muli County and Dechang County in Liangshan Prefecture. The deposit areas of Zha-xun were located in the Triassic, Devonian and Silurian strata and were basically distributed in 9 basins, including Dingqu River, Yalong River, Xianshui River, Dadu River, Suomo River, Minjiang River and Baishui River, characterized by a fragmented patch-like distribution along the mountain ranges, and the exudation spots of Zha-xun were mainly scattered among the rain-free cliffs' concavities of river valleys at a certain altitude. The prediction was consistent with the field investigation results, which suggested that it is possible and feasible to predict distribution of Zha-xun resources based on GIS-analysis. The study may provide a scientific basis for comprehensive investigations into Zha-xun's distribution and formation mechanism, thus promoting rational development and utilization of Zha-xun resources.
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China , Geographic Information Systems , Geology , Medicine, Tibetan Traditional , Medicine, Traditional , TemperatureABSTRACT
Background: Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. In 2017, TB caused an estimated 1.3 million deaths (range, 1.2–1.4 million) among HIV-negative people, and there were an additional 300 000 deaths from TB (range, 266 000–335 000) among HIV-positive people. The current TB program reports are often compiled and reported at higher administrative units and there is limited information about the spatial distribution of the disease. Hence, we aimed to assess the spatial distribution and hot spot areas of the disease among the patients attending a tertiary care centre in Mysore over a period of 3 years.Methods: This is a taluk based study, the spatial analysis and hot spot area identification was done by collecting the demographic data from the smear positive pulmonary tuberculosis patients attending JSS a tertiary care centre from Mysore district. Hot spot areas and areas with TB transmission are identified and estimated using GIS software tool. Distribution of TB incidence was mapped with the population density from 2016-2018.Results: Spatial mapping of smear positive tuberculosis revealed that majority of cases were recorded from Mysore city followed by T. N. Pura and Hunsur taluk regions.Conclusions: This study emphasized on finding hot spot areas and local clusters involved in TB transmission.
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Background: Dengue is a significant public health problem in the mostly tropical country such as Indonesia. Even though many efforts have been established in Indonesia, in fact, dengue remains drawing attention from the health sector. Geographic Information System (GIS) is a powerful tool to support dengue surveillance on understanding the dengue pattern with the goal to give input for the decision maker. Accordingly, there is a need to providing the presence and the dynamic of dengue case particularly in Sleman district to establish evidence on building dengue control strategy.Methods: A descriptive study using GIS was performed to provide a spatial-temporal mapping of dengue case. Secondary data which sourced from Sleman district health office was collected for period 2014-2017. This data was grounded into subdistrict level. Quantum GIS and Microsoft Excel were used to analyse the data.Results: During 2014-2017 dengue spreads over the Sleman district. In 2016, found the increased of subdistrict with high dengue case. The high dengue case found in sub-district with an urban characteristic.Conclusions: Mapping of dengue using GIS is helpful to understanding the disease presence and dynamic disease over time.
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Aims: This paper investigates the spatial distribution of mosquito breeding sites within the Dakhla oasis of the Western Desert of Egypt. Study Design: GIS spatial analysis was used to map the area under risk of mosquito proliferation. Place and Duration of Study: Dakhla oases, during September 2009 to October 2010. Methodology: Landsat images, synchronized with mosquito larval survey, were processed to identify the vegetation status of the study area. Twenty-two locations distributed in Dakhla oasis were investigated as nine mosquito species were collected from drains, paddle fields, and waterlogged areas. Results: Results showed that the main vector of Malaria disease (Anopheles pharoensis and Anopheles sergentii), as well as the Culex pipiens, which is the main vector of filarial disease are abundant. Further, the geo-environmental setting and the discharge of increasing cultivated areas develop considerable waterlogging and pond areas, which are favorable breeding sites of mosquito. In Dakhla oases, the produced risk map showed that a large part of urban and cultivated regions were at risk of mosquito spread. Conclusion: It was concluded that mosquito larval populations fluctuated with the dynamics of vegetation cover in Dakhla. Multi-year data of mosquito collections are still required to provide a better characterization of the abundance of these insects from year to year which can potentially provide predictive capability of their population density based on remotely sensed ecological measurements.