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Giving the COVID-19 vaccine has many benefits, including increasing immunity from exposure to COVID-19 and preventing new mutations from COVID-19. In addition, the COVID-19 vaccine that has been injected into the community has gone through a series of strict tests, so that it is guaranteed to be safe, quality and efficacious. The research aims to cluster the spread of the corona virus in DKI Jakarta province which is displayed on a visual map using ArcGIS Technology. Based on the data on the spread of the corona virus which has been grouped using K-means clustering, it is hoped that it can help make the right decisions in vaccination and the priority of COVID-19 assistance that is determined and directed based on information cluster, so this research is expected to help the government in tackling the COVID-19 pandemic in Indonesia, especially DKI Jakarta. In addition, this research also aims to see the correlation between the COVID-19 vaccine and the number of positive cases of Covid-19. © 2022 IEEE.
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COVID-19 is caused by the novel coronavirus SARS-CoV-2. First started in Wuhan, COVID-19 has spread everywhere, including Indonesia. COVID-19 can cause severe pneumonia, severe acute respiratory distress syndrome (ARDS) symptoms, and multiple organ failure. According to the WHO, COVID-19 generally has an incubation period of 5-6 days, ranging from 1 to 14 days. However, in Jakarta, the cases have decreased significantly since the implementation of PPKM (Restrictions of Activity), running since early July 2021. The government claimed that the PPKM rule has significantly impacted COVID-19 cases, decreasing every day, especially in Jawa-Bali Region. In addition, the Vaccination rate in Indonesia also played a significant part in decreasing COVID-19 cases, with Jakarta currently standing with 9 million people fully vaccinated per December 2021. To monitor the development of COVID-19 in Jakarta and provide information to the public about health facilities, especially hospitals in Jakarta, in this study, the distribution area of COVID-19 cases will be mapped with CHIME using ArcGIS Online tools. The analysis results obtained based on the mapping results that most cases were in the Cengkareng area, and the area with the most hospitals werein East Jakarta. © 2022 IEEE.
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In Italy, there is a clear disparity between cities and villages located in marginal areas. The progressive depopulation of inland areas and the urban polarization represent consolidated dynamics difficult to adapt to the new paradigm of sustainable development. The post-Covid-19 pandemic scenario offers the opportunity to redefine new parameters of intervention and new visions for the regeneration of villages in accord with the new challenges of decentralization and distancing. The project «Renaissance of villages for the revitalization of marginal areas» (2021) aims to create the conditions to repopulate and rebalance shrinking territories by establishing new centres of attractiveness. This project envisages the active involvement of municipalities to implement multi-sectoral analysis and spatial assessment approaches in planning processes. It intends to develop an interactive web dashboard for local authorities and spatial planners to create both a learning environment and a participative spatial decision support system for future local policy actions toward sustainable local development. This study presents the project's preliminary phase which aims to create the general framework of the web dashboard. A reconstruction of the village definition and the spatial selection of villages throughout Italy are presented as innovative aspects since the absence of an agreed definition of the village in the national and international level documents. Moreover, this study provides a quantitative spatial multivariate analysis cluster that analyzes, and groups Italian territories based on socioeconomic dynamics. The result of this analysis allows us to divide the territory into archetypes and to structure a framework that supports the definition of future scenarios for the regeneration of small urban areas considering the diversified needs and potential of the villages belonging to specific archetypes analyzed in the study.In Italia esiste una netta disparità tra città e borghi situati in aree marginali. Il progressivo spopolamento delle aree interne e la polarizzazione urbana rappresentano dinamiche consolidate poco affini ai paradigmi dello sviluppo sostenibile. Lo scenario post pandemico offre oggi l'opportunità di ridefinire nuovi parametri di inter- vento e nuove visioni per la rigenerazione dei borghi in accordo con le sfide imposte dal decentramento e dal distanziamento fisico. Il progetto «Rinascimento dei borghi per la rivitalizzazione delle aree marginali» (2021) mira a creare le condizioni per ripopolare e rigenerare i territori in contrazione. L'efficacia del progetto si fonda sul coinvolgimento attivo dei comuni nei processi di pianificazione e sull'integrazione in essi di analisi multisettoriali sperimentando un approccio basato sulla va- lutazione territoriale. Nell'ambito del progetto s'intende sviluppare un cruscotto web interattivo indirizzato alla pubblica amministrazione e ai pianificatori territoriali, al fine di creare un sistema partecipativo di supporto alle decisioni spaziali propedeutico allo sviluppo di scenari di sviluppo locale sostenibile. Questo studio presenta la fase preliminare del progetto in cui viene predisposta la struttura generale del cruscotto web. La ricerca e la ricostruzione della definizione di borgo, seguita dalla se- lezione spaziale dei borghi in tutta Italia, sono presentati come aspetti innovativi data l'attuale assenza di una definizione a livello nazionale e internazionale. Inoltre, questo studio fornisce un'analisi spaziale quantitativa multivariata che analizza e riunisce in cluster i territori italiani in base alle dinamiche socioeconomiche. Il risultato di questa analisi permette di suddividere il territorio in archetipi e di strutturare un quadro di riferimento che supporti la definizione di scenari futuri per la rigenerazione delle piccole aree urbane, considerando le esigenze e le potenzialità diversificate di ogni singolo borgo.
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Adding to the already polarizing 2020 general election was the COVID-19 pandemic. One way in which this pandemic greatly affected the election was through an increased participation in by-mail, or mail-in, ballots. The state of North Carolina experienced a 316 percent increase in by-mail votes between 2016 and 2020, when approximately 977,186 votes were cast by mail. It is no surprise that this increase was due to the COVID-19 pandemic;however, these by-mail voting patterns are spatial in nature and vary across the state. This research measures to what degree COVID-19 rates affected by-mail voting rates. Using geographic information systems data developed from robust tabular files provided by the North Carolina State Board of Elections, by-mail votes were calculated and mapped at ZIP code scale and compared to COVID-19 rates measured at different dates. By-mail rates taken from final absentee tallies for the highest and lowest COVID-19 ZIP codes saw no significant differences across multiple dates (30 September 2020 and 31 October 2020) when COVID-19 data were collected. COVID-19 hot spots (high COVID-19 rates surrounded by other high COVID-19 rates) were extracted using geostatistical techniques and compared to COVID-19 cold spots (low COVID-19 rates surrounded by other low COVID-19 rates). It was found the lowest by-mail rates actually occurred in these COVID-19 hot spots across both dates, as well a metric that expressed percentage change in COVID-19 rates in the month before the 2020 election.Alternate :COVID-19使得已经两极分化的2020年美国大选, 变得更加雪上加霜。COVID-19影响选举的一种方式是邮寄选票的增加。2016年至2020年, 北卡罗来纳州的邮寄选票增加了316%, 共约977,186张。毫无疑问, COVID-19导致了邮寄选票的增加。然而, 邮寄选票在本质上是空间性的, 并且在北卡罗来纳州的各个地方具有差异性。本研究计算了COVID-19发病率对邮寄选票比例的影响程度。利用北卡罗来纳州选举委员会提供的准确的表格文件, 本文制作了地理信息系统数据, 在邮政编码尺度上对邮寄选票进行计算和制图, 并将这些邮寄选票与不同时间的COVID-19发病率进行了比较。在拥有最高和最低COVID-19发病率的邮政编码和不同时间（2020年9月30日和2020年10月31日）, 从缺失人数统计中得到的邮寄选票比例没有显著差异。利用地学统计方法提取COVID-19热点（COVID-19高发病率在空间上被其它高发病率所包围）, 并与COVID-19冷点（COVID-19低发病率在空间上被其它低发病率所包围）进行比较。结果发现, 在这两个时间内, 最低邮寄选票比例出现在COVID-19热点地区。本文还制定了一个指标, 可以表示2020年大选前一个月的COVID-19发病率百分比的变化。
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After the coronavirus outbreak, the disease known as COVID-19 has been infecting millions of people, and the number of deaths is pilling up to hundreds of thousands. In Indonesia, especially Jakarta, some of the deaths are caused by pandemic-related surges that strain hospital capacity. Besides, people had many obstacles in this pandemic condition because of the lack of knowledge about COVID-19. On that matter, several models emerged worldwide to help inform public decision making in this pandemic situation. With today's technological advances the CHIME (COVID-19 Hospital Impact Model for Epidemics) application is designed to assist hospitals and public health officials with understanding hospital capacity needs as they relate to the COVID pandemic. This paper aims to help inform public health decision making regarding the transmission of COVID-19 in Jakarta using CHIME. This work uses Jakarta COVID-19 data from November 24th, 2021 and its accumulation from 14 days before (November 10th, 2021) to predict the course of COVID-19 in 30 days. With ArcGIS Pro and ArcGIS Experience, this work successfully made a map that uses CHIME to inform about peak demand of each city in DKI Jakarta and the daily new admissions and hospitalization graph. In addition, a Jakarta COVID-19 dashboard is also made to inform more about the transmission of COVID-19. © 2022 IEEE.
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Air quality and environmental justice To introduce how socioeconomic status affects the physical aspects of exposure to differing air-quality levels, students used an anthropological technique of comparison to "make the strange familiar and the familiar strange." Students analyzed a New York Times story revealing the air-quality inequities of two teens residing in India: "Who Gets to Breathe Clean Air in New Delhi?" For 25 minutes, students interact with the website and reflect on paper: * One new and interesting fact that they encountered in the article about air quality, * How they think the information might relate to air quality in the United States, and * What, if anything, they think we could do to help increase awareness about these types of environmental disparities. For the next 35 minutes, students search online for articles about air quality and environmental justice in the area near our school's location. The data from real-time air quality index reports are available on every cell phone, and students decided to record it on a calendar to chart in Excel.
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Nowadays, spatial geographic data analysis and GIS related software are more and more applied to the planning of urban public facilities. Under the COVID-19, people pay more attention to the protection of medical facilities for people's health, and a reasonable distribution of hospital facilities is conducive to people's health. Taking Haikou City as an example, this research will optimize the location of hospital space layout according to the existing third-level first-class general hospitals in Haikou City by using GIS software, road analysis, spatial analysis, and other methods. The results show that the existing hospitals in Haikou are too concentrated in the central urban area, the overall distribution of medical facilities is lack of balance, and there is a serious lack of medical facilities in new urban development areas and suburbs. According to the comparison between population density analysis and traffic analysis and the service scope of existing hospitals, the author finds out the scope of hospitals that need to be supplemented, and then calculates the scope of service area after taking several random points within the scope, and finally finds the one with the largest service scope is the optimal location. The results obtained by optimizing the site selection can provide a scientific reference for the rational layout of medical facilities in Haikou City in the future. © 2023 SPIE.
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Data collection and large-scale urban audits are challenging and can be time consuming processes. Geographic information systems can extract and combine relevant data that can be used as input to calculation tools that provide results and quantify indicators with sufficient spatial analysis to facilitate the local decision-making process for building renovations and sustainability assessment. This work presents an open-access tool that offers an automated process that can be used to audit an urban area in order to extract relevant information about the characteristics of the built environment, analyze the building characteristics to evaluate energy performance, assess the potential for the installation of photovoltaics on available building rooftops, and quantify ground permeability. A case study is also presented to demonstrate data collection and processing for an urban city block, and the relevant results are elaborated upon. The method is easily replicable and is based on open data and non-commercial tools.
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This research examines the Modeling spatial relationships of the mortality of COVID-19 that were tested in 213 countries worldwide. The database used in the research included variables per 1000 population, as follows: the cumulative number of cases, hospital beds, and the unvaccinated population as health variables, the age population over 65 years, population number and population density as demographic variables for interpretation and prediction of mortality around the world. In total, it relied on 7 variables at the level of countries in the world based on the official COVID-19 data of the World Health Organization and World Bank indicators. Therefore, the aim of this research is to study whether the relationships between mortality rates and these variables differ spatially across different countries by means of applying modeling spatial relationships by Geographically Weighted Regression (GWR) and Ordinary Least Squares Rregression (OLS) available in statistical tools in a GIS environment. The results showed that there are spatially homogeneous relationships at the level of the countries to the variables of the cumulative number of cases, the number of the population over the age of 65 years, and the number of the unvaccinated population, which are statistically significant and collectively explained 97% of the variation in mortality of COVID-19. In conclusion, spatial information derived from this modeling provides valuable insights regarding the spatially varying relationship of COVID-19 mortality with these potential drivers to help establish preventive measures to reduce mortality around the world.
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Open source Geographic Information System (GIS) have been fostering spatial data research such as Earth observation and environmental monitoring for more than 30 years. More recently, globally available geospatial information combined with web technologies are providing new environments and tools for data handling. Thus, binding the mapping and processing capabilities of traditional GIS to the accessibility and reliability of web-based data providers can bring new opportunities for research. In this paper, we built a QGIS plugin to explore the integration of different public data providers in Brazil along with field data produced by the BONDS project. The biOdiversity conservatioN with Development in Amazon wetlandS project (BONDS) proposes to develop biodiversity scenarios for the Amazonian floodplains aiming to support solutions to preserve biodiversity and ecosystem services. The use of web services enabled dynamic and fast access to several products ranging from remote sensing images, land use and land cover, territorial cartography, water quality, to COVID-19 health data, and more. © 2022 National Institute for Space Research, INPE. All rights reserved.
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This study presents the findings from the literature review of 30 empirical research articles on the use of Geographic Information Systems (GIS) in Geographic and Environmental Education published in the last decade (2010-2020). Using systematic review methodology, we recorded and synthesized current knowledge from the literature on how the use of GIS in education is assessed. The findings show that over the past decade, the construct variables used to evaluate the use of GIS in education have focused on three thematic categories (Themes): Learning (44.4%), Affective Elements (40.7%), and Behavior (14.8%). A certified instrument had been used to evaluate the data of 30% of the research conducted in the articles, while three new measuring tools had been created by the original researchers. Analysis of the findings suggests that the use of GIS in Geographic and Environmental education is heterogeneous, sparse, and fragmented. We propose that a more systematic framework be implemented in order to make future studies more effective. The value of our study is that it provides an analytical framework which can be used when evaluating the use of GIS in education, and could also provide information on the development of new assessment methods and measuring tools. [ FROM AUTHOR] Copyright of International Research in Geographical & Environmental Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Spatial thinking is an integral skill for geography students to develop. Whilst many spatial competencies have been identified by researchers, and the merits of GIS seemingly ubiquitous in the published literature, little work has been done into how students' spatial thinking skills can be assessed. Therefore, further investigation into the relationship between spatial thinking and performance and attainment is needed. This research investigates the impact using a geographic information system (GIS) has on students' spatial thinking skills and attempts to assess the extent using a framework. This was done through the design and implementation of two GIS-based interventions. This small-scale evaluation used qualitative methods to investigate students' and teachers' views. Student work was also analysed using the framework developed for the assessment of spatial thinking skills. The findings suggest that the use of a GIS does enhance, and in most cases improves students' spatial thinking skills, but, that spatial thinking is hard to quantify and difficult to measure progress in. Another benefit that using a GIS affords is the creation of engaging, contemporary and interactive lessons, using real data, from which students derive a lot of geographical value. [ FROM AUTHOR] Copyright of International Research in Geographical & Environmental Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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International Conference on Geospatial Science for Digital Earth Observation (GSDEO 2021)The international conference on "Geospatial Science for Digital Earth Observation” (GSDEO) 2021 was successfully held on a virtual platform of Zoom on March 26th and 27th, 2021. The conference was jointly organized by the Indian Society of Remote Sensing (ISRS), Kolkata chapter, and the Department of Geography, School of Basic and Applied Sciences, Adamas University. Due to the non-predictable behaviour of the COVID-19 second wave, which imposed restrictions on organizing offline events, the GSDEO (2021) organizing committee decided to organize the conference online, instead of postponing the event.Remotely sensed data and geographic information systems have been increasingly used together for a vast range of applications, which include land use/land cover mapping, water resource management, weather forecasting, environmental monitoring, agriculture, disaster management, etc. Currently, intensive research is being carried out using remotely sensed data on the geoinformatics platform. New developments have led to dynamic advances in recent years. The objective of the international conference on Geospatial Science for Digital Earth Observation (GSDEO 2021) was to bring the scientists, academicians, and researchers, in the field of geo-environmental sciences on a common platform to exchange ideas and their recent findings related to the latest advances and applications of geospatial science. The call for papers received an enthusiastic response from the academic community, and over 100+ participants from 50+ colleges, universities, and institutions participated in the conference. In total 50+ research papers had been presented through the virtual Zoom conference platform in GSDEO 2021.The conference witnessed the presentation of research papers from diverse applied fields of geospatial sciences, which include the application of geoinformatics in geomorphology, hydrology, urban science, land use planning, climate, and environmental studies. There were four sessions namely, TS 1: Geomorphology and Hydrology, TS 2: Urban Science, TS 3: Social Sustainability and Land Use Planning, and TS 4: Climate and Environment. Each session was further subdivided, into two parts, namely Technical Session 1-A and 1-B. Each sub-session had been designed with one keynote speech and 5 oral presentations. Oral sessions were organized in two parts and offered through live and pre-recorded components based on the preference of the presenters. The presentation session was followed by a live Q&A session. The session chairs moderated the discussions. Similarly, poster sessions were organized in three parts and offered e-poster, live, and pre-recorded components. The best presenter of each sub-session received the best paper award.Dr. Prithvish Nag, Ex-Director of NATMO & Ex Surveyor General of India delivered the inaugural speech, and Dr. P. Chakrabarti, Former Chief Scientist of the DST&B, Govt. of West Bengal delivered a special lecture after the inaugural session. Eight eminent keynote speakers, Prof. S.P. Agarwal from the Indian Institute of Remote Sensing, Prof. Ashis Kumar Paul from Vidyasagar University, Prof. Soumya Kanti Ghosh from the Indian Institute of Technology, Kharagpur, Prof. L. N. Satpati from the University of Calcutta, Prof. R.B. Singh from the University of Delhi, Dr. A.K. Raha, IFS (Retd), Prof. Gerald Mills from the University College Dublin and Prof. Sugata Hazra from Jadavpur University enriched the knowledge of participants in the field of geoinformatics by their informative lectures. The presentations and discussions widely covered the various spectrums of geoinformatics and its application in monitoring natural resources like vegetation mapping, agricultural resource monitoring, forest health assessment, water, and ocean resource management, disaster management, land resource management, water and climate studies, drought vulnerability assessment, groundwater quality monitoring, accretion mapping and the use of geospatial sci nce in studying morphological, hydrological, and other biophysical characteristics of a region etc. Application of geoinformatics in predicting urban expansion, urban climate, disaster management, healthcare accessibility, anthropogenic resource monitoring, spatial-interaction mapping, and, sustainable regional planning were well-discussed topics of the conference.List of Committees, photos are available in the pdf.
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In this study, we proposed a GIS-based approach to analyzing hospital visitors from January to June 2019 and January to June 2020 with the goal of revealing significant changes in the visitor demographics. The target dates were chosen to observe the effect of the first wave of COVID-19 on the visitor count in hospitals. The results indicated that American Indian and Pacific Islander groups were the only ones that sometimes showed no shift in visitor levels between the studied years. For 19 of the 28 hospitals in Austin, TX, the average distance traveled to those hospitals from home increased in 2020 compared with 2019. A hospital desert index was devised to identify the areas in which the demand for hospitals is greater than the current hospital supply. The hospital desert index considers the travel time, location, bed supply, and population. The cities located along the outskirts of metropolitan regions and rural towns showed more hospital deserts than dense city centers.
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Objective: Determine the temporal and spatial structure of the severe acute respiratory syndrome virus (SARS-CoV-2) that causes coronavirus disease (COVID-19), in the cities of Cartagena and Barranquilla, Colombia, in order to take necessary actions to support contact tracing. Methods: Cross-sectional ecological study with spatial analysis based on kernel densities of variables, including cases, mobile application alerts, population vulnerability, multidimensional poverty index; inverse distance weighted spatial interpolation of active cases; and, finally, the spatial superposition technique as a final result. The database of the National Institute of Health of the cities of Cartagena and Barranquilla and the Department of National Statistics was used. Results: The analysis identified an upward epidemiological trend in cases in the two cities, and determined the spatial direction of disease spread in neighborhoods, through spatial interpolation. Intervention areas were detected in 15 neighborhoods in Cartagena and 13 in Barranquilla, 50 meters around active cases with fewer than 21 days of evolution and by geographical risk layers, as a mechanism to stop the spread of COVID-19. Conclusions: Spatial analysis proved to be a useful complementary methodology for contact tracing, by determining temporal and spatial structure and providing necessary scientific evidence for the application of direct intervention measures, where necessary, to reduce the spread of SARS-CoV-2.
Objetivo: Determinar a estrutura temporal e espacial do vírus da síndrome respiratória aguda grave (SARS-CoV-2, na sigla em inglês), causador da doença pelo coronavírus de 2019 (COVID-19, na sigla em inglês), nas cidades de Cartagena e Barranquilla, visando a tomar ações necessárias que apoiem o rastreamento de contatos. Métodos: Estudo ecológico transversal que inclui análise espacial baseada em densidade de Kernel de variáveis como casos, alertas de um aplicativo móvel, vulnerabilidade populacional, índice de pobreza multidimensional, aplicação de interpolação espacial (IDW, na sigla em inglês) de casos ativos e, por último, aplicação da técnica de sobreposição espacial como resultado final. Foram utilizadas as bases de dados do Instituto Nacional de Saúde para as cidades de Cartagena e Barranquilla e do Departamento Nacional de Estatística. Resultados: A análise determinou o comportamento epidemiológico ascendente dos casos nas duas cidades e identificou a direção espacial de propagação da doença nos bairros, por meio de interpolação espacial. Foram detectadas áreas para intervenção em 15 bairros de Cartagena e 13 de Barranquilla, em 50 metros ao redor dos casos ativos com menos de 21 dias de evolução e de acordo com as camadas de risco geográfico, como mecanismo para impedir a propagação da COVID-19. Conclusões: A análise espacial permitiu determinar a estrutura temporal e espacial como uma metodologia complementar útil para o rastreamento de contatos, e forneceu a evidência científica necessária para a aplicação de medidas de intervenção direta, quando necessário, visando a reduzir o contágio pelo SARS-CoV-2.
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Distance education at universities during the COVID-19 pandemic was implemented through various so-called learning management systems (LMSs). These environments are primarily used for teacher-student communication, assignment, and sharing of learning materials, testing, and assessment. This article aims to evaluate the Google Classroom environment's perception by university students of the courses Teaching Academic Subjects and Geography, forced to study through distance learning during the second half of the semester. Students filled out a questionnaire focused on the perception and evaluation of the Google Classroom environment at the end of the semester. The students were divided into two groups, depending on whether they worked in the Google Classroom environment for the first time or not. The results were evaluated using the Wilcoxon rank-sum test and the semantic differential method. The results show students' positive attitudes toward this environment, even though some were working with it for the first time. The perception and identification of the strengths and weaknesses of learning environments are essential in their future use in creating curricula and analysis of possible further use in other subjects or situations.
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INTRODUCTION: Eastern equine encephalitis virus (EEEV) and Venezuelan equine encephalitis virus (VEEV) viruses are zoonotic pathogens affecting humans, particularly equines. These neuroarboviruses compromise the central nervous system and can be fatal in different hosts. Both have significantly influenced Colombia; however, few studies analyse its behaviour, and none develop maps using geographic information systems to characterise it. OBJECTIVE: To describe the temporal-spatial distribution of those viruses in Colombia between 2008 and 2019. METHODS: Retrospective cross-sectional descriptive study, based on weekly reports by municipalities of the ICA, of the surveillance of both arboviruses in equines, in Colombia, from 2008 to 2019. The data were converted into databases in Microsoft Access 365®, and multiple epidemiological maps were generated with the Kosmo RC1®3.0 software coupled to shape files of all municipalities in the country. RESULTS: In the study period, 96 cases of EEE and 70 of VEE were reported, with 58% of EEE cases occurring in 2016 and 20% of EEV cases in 2013. The most affected municipalities for EEE corresponded to the department of Casanare: Yopal (20), Aguazul (16), and Tauramena (10). In total, 40 municipalities in the country reported ≥1 case of EEE. CONCLUSIONS: The maps allow a quick appreciation of groups of neighbouring municipalities in different departments (1° political division) and regions of the country affected by those viruses, which helps consider the expansion of the disease associated with mobility and transport of equines between other municipalities, also including international borders, such as is the case with Venezuela. In that country, especially for EEV, municipalities in the department of Cesar are bordering and at risk for that arboviral infection. there is a high risk of equine encephalitis outbreaks, especially for VEE. This poses a risk also, for municipalities in the department of Cesar, bordering with Venezuela.
Subject(s)
Encephalitis Virus, Venezuelan Equine , Encephalomyelitis, Venezuelan Equine , Horses , Animals , Colombia/epidemiology , Cross-Sectional Studies , Encephalomyelitis, Venezuelan Equine/epidemiology , Geographic Information Systems , Horses/virology , Retrospective StudiesABSTRACT
GIS Day was a small, local offering dependent on individual institutions, until the COVID-19 pandemic prompted a wealth of online events. After 3 years of successive development, 2022 saw this event span multiple days and reach beyond Western University to institutions across Canada. The planning process, events, and outcome are here described as inspiration for future events by interested parties, and to acknowledge the work of those involved while simultaneously promoting the current work in GIS being undertaken and potential future directions for event organizers. © 2023 Association of Canadian Map Libraries and Archives. All rights reserved.
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Greenspaces are argued to be one of the important features in the urban environment that impact the health of the population. Previous research suggested either positive, negative, or no associations between greenspaces and health-related outcomes. This paper takes a step backward to, first, explore different quantitative spatial measures of evaluating greenspace exposure, before attempting to investigate the relationship between those measures and health-related outcomes. The study uses self-reported health data from an online cross-sectional survey conducted for residents in the West of England. This yielded data of greenspace use, physical activity, wellbeing (ICECAP-A score), and connectedness to nature for 617 participants, divided into two sets: health outcomes for the period before versus during the 2020 lockdown. The study uses the participants' postcodes (provided in the survey) to calculate eleven spatial measures of greenspace exposure using the software ArcGIS Pro 2.9.5. A total of 88 multivariate regression models were run while controlling for eleven confounders of the participants' characteristics. Results inferred 57 significant associations such that six spatial measures of greenspace exposure (NDVI R200m, NDVI R300m, NDVI R500m, Network Distance to nearest greenspace access, Euclidean Distance to nearest greenspace access, and Euclidean Distance to nearest 0.5 ha doorstep greenspace access) have significant association to at least one of the four health-related outcomes, suggesting a positive impact on population health when living in greener areas or being closer to greenspaces. Moreover, there are further significant associations between the frequency of use of greenspaces and increasing physical activity or feeling more connected to nature. Still, the residents' patterns of using greenspaces significantly changed during versus before lockdown and has impacted the relationships between health outcomes and the greenspace exposure measures.