scholarly journals COVID-19 in Toronto: A Spatial Exploratory Analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 498
Author(s):  
Eric Vaz
Keyword(s):  
Geographical Information Systems ◽  
Spatial Regression ◽  
Open Data ◽  
Global Scale ◽  
Geographical Information ◽  
Disease Spread ◽  
Modeling Framework ◽  
Large Cities ◽  
Monitoring Strategies ◽  
Global And Local

COVID-19 has had a significant impact on a global scale. Evident signs of spatial-explicit characteristics have been noted. Nevertheless, publicly available data are scarce, impeding a complete picture of the locational impacts of COVID-19. This paper aimed to assess, confirm, and validate several geographical attributes of the geography of the pandemic. A spatial modeling framework defined whether there was a clear spatial profile to COVID-19 and the key socio-economic characteristics of the distribution in Toronto. A stepwise backward regression model was generated within a geographical information systems framework to establish the key variables influencing the spread of COVID-19 in Toronto. Further to this analysis, spatial autocorrelation was performed at the global and local levels, followed by an error and lag spatial regression to understand which explanatory framework best explained disease spread. The findings support that COVID-19 is strongly spatially explicit and that geography matters in preventing spread. Social injustice, infrastructure, and neighborhood cohesion are evident characteristics of the increasing spread and incidence of COVID-19. Mitigation of incidents can be carried out by intertwining local policies with spatial monitoring strategies at the neighborhood level throughout large cities, ensuring open data and adequacy of information management within the knowledge chain.

scholarly journals Diagnostic approaches to malaria in Zambia, 2009-2014

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Victor M. Mukonka ◽  
Emmanuel Chanda ◽  
Mulakwa Kamuliwo ◽  
Maha A. Elbadry ◽  
Pauline K. Wamulume ◽  
...  
Keyword(s):  
Risk Factors ◽  
Geographical Information Systems ◽  
Temporal Dynamics ◽  
Health Workers ◽  
Clinical Symptoms ◽  
Spatial Regression ◽  
Geographical Information ◽  
Diagnostic Tools ◽  
Control Center ◽  
Spatio Temporal

Malaria is an important health burden in Zambia with proper diagnosis remaining as one of the biggest challenges. The need for reliable diagnostics is being addressed through the introduction of rapid diagnostic tests (RDTs). However, without sufficient laboratory amenities in many parts of the country, diagnosis often still relies on non-specific, clinical symptoms. In this study, geographical information systems were used to both visualize and analyze the spatial distribution and the risk factors related to the diagnosis of malaria. The monthly reported, district-level number of malaria cases from January 2009 to December 2014 were collected from the National Malaria Control Center (NMCC). Spatial statistics were used to reveal cluster tendencies that were subsequently linked to possible risk factors, using a non-spatial regression model. Significant, spatio-temporal clusters of malaria were spotted while the introduction of RDTs made the number of clinically diagnosed malaria cases decrease by 33% from 2009 to 2014. The limited access to road network(s) was found to be associated with higher levels of malaria, which can be traced by the expansion of health promotion interventions by the NMCC, indicating enhanced diagnostic capability. The capacity of health facilities has been strengthened with the increased availability of proper diagnostic tools and through retraining of community health workers. To further enhance spatial decision support systems, a multifaceted approach is required to ensure mobilization and availability of human, infrastructural and technological resources. Surveillance based on standardized geospatial or other analytical methods should be used by program managers to design, target, monitor and assess the spatio-temporal dynamics of malaria diagnostic resources country-wide.

scholarly journals Open Data for web-mapping the dynamic of population of Uzbekistan

2021 ◽  
Vol 27 (4) ◽  
pp. 388-401
Author(s):  
Lola Gulyamova ◽  
Dilshod Rakhmonov
Keyword(s):  
Geographical Information Systems ◽  
Conceptual Development ◽  
Open Data ◽  
Cloud Service ◽  
Geographical Information ◽  
State Agencies ◽  
Geospatial Information ◽  
Web Mapping ◽  
Server Side ◽  
Map Data

This paper covers issues related to using Open Data for web mapping of the dynamic of population of Uzbekistan. Several ways are suggested for performing an analysis of patterns of dynamic of population. The web mapping is recommended as the preferable way for study the spatial distribution of the population and its change. The methods are described from the perspective of their relevance to the technical and conceptual development of interactive dynamic maps. The Open sources that are maintained by state agencies, committees, private companies and other institutions are used for web mapping. The peculiarities of development of Open Data in this country are analyzed with the purpose of applying geoinformation technologies for capturing geospatial information (GI). The model has been developed for using web mapping tools for combining ICT, GIS, interactive cartography and socio-economic data for retrieving GI from existing open resources. Some tools are suggested to bring together Open Data of different official sources by means of Geographical Information Systems. The model of web service is used for uploading map data to a cloud account, while cloud service handles all server-side. ArcGIS Online and other open software are applied for interactive mapping. The interaction with datasets for online mapping and spatial analysis is performed with the help of the cloud service of ArcGIS Online

scholarly journals Geographical Information Systems: A Tool to Map and Analyze Disease Spread

2013 ◽  
Vol 5 (1) ◽  
Author(s):  
Indumathi Srinath ◽  
Barbara Szonyi ◽  
Maria Esteve-Gassent ◽  
Blanca Lupiani ◽  
Raju Gautam ◽  
...  
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Disease Spread

scholarly journals Geo-epidemiological reporting and spatial clustering of the 10 most prevalent cancers in Iran

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ebrahim Babaee ◽  
Gholamreza Roshandel ◽  
Meysam Olfatifar ◽  
Arash Tehrani-Banihashemi ◽  
Arezou Ashaari ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Geographical Information Systems ◽  
Spatial Clustering ◽  
Incidence Rates ◽  
Geographical Information ◽  
Breast Cancers ◽  
Contributing Factors ◽  
Index Method ◽  
The North ◽  
Global And Local

Cancer is a problem of both global and local concern. We determined the geo-epidemiological and spatial distribution of the 10 most common cancers in Iran. We used the data of the Iranian Cancer Registry for the year 2014 analysing the prevalence of 112,131 registered cancer cases with the aim of detecting potential geographical underlying causes. The geographic distribution of cancers is reported as standardized incidence rates at the provincial level considering risk with respect to sex and age. A geographical information systems (GIS) approach based on Anselin Local Moran’s index method was used to map clusters and spatial autocorrelation patterns. The mean age of the patients was 55.6 (±17.8) and 61.7 (±18.2) for females and males, respectively, in the database which showed 46.1% (n=51,665) of all cases to be female. Analysis of the spatial distribution of cancers showed significant differences among the different provinces. Stomach and breast cancers were the most prevalent cancers in men and females, respectively. The highest incidence rates of stomach cancer were found in Ardabil and Zanjan provinces, with 48.38 and 48.08 per 100,000 population, respectively, while Tehran and Yazd provinces had the highest incidences of breast cancer, 51.0 and 47.5 per 100,000 population, respectively. Strong clustering patterns for stomach and breast cancers were identified in the north-western provinces and in Semnan Province, respectively. These patterns indicate a diversity of geo-epidemiological contributing factors to cancer incidence in Iran.

scholarly journals Sistem Informasi Geografis Wisata Industri Berbasis Web Pada Dinas Pariwisata Kabupaten Bekasi

2021 ◽  
Vol 2 (1) ◽  
pp. 77-88
Author(s):  
Arman Andrian ◽  
Abrar Hiswara ◽  
Tyastuti Tri Lestari
Keyword(s):  
Information Technology ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Geographic Information ◽  
Tourism Industry ◽  
Geographical Information ◽  
Modeling Framework ◽  
Google Maps ◽  
Zachman Framework ◽  
Travel Industry

Abstract   Development of information technology can be used in various ways such as through design of Geographical Information Systems Tourism Industry Web Based On Tourism Office Bekasi, this can be used as a medium to inform the travel industry more broadly, Using methods based promotions information technology by using the website as an information access has the advantage that can be accessed by anyone, anywhere, anytime without the time and distance. So that the travel industry in Bekasi Regency can be informed quickly and accurately as well as the information can be combined with geographic information systems that can do the mapping industry where tourist sites are located. Design SIG Tourism industry is using the PHP programming language and on its use codeigneter with plugin Google Maps API, system development methods used methods Zachman framework by modeling framework and UML (Unifed Modeling Language), Through this design, it is hoped that it can contribute ideas to the Bekasi Regency Tourism Office in an effort to promote industrial tourism to the community.   Keywords: Geographic Information System, Tourism industry, Zachman Framework, the Google Maps API.   Abstrak   Berkembangnya teknologi informasi dapat dimanfaatkan dengan berbagai cara salah satunya melalui Perancangan Sistem Informasi Geografis Wisata Industri Berbasis Web Pada Dinas Pariwisata Kabupaten Bekasi, hal  ini  dapat  dimanfaatkan  sebagai media untuk menginformasikan wisata industri yang lebih luas lagi, Menggunakan metode promosi berbasis teknologi informasi dengan menggunakan website sebagai akses informasi mempunyai kelebihan yaitu dapat di akses siapa saja, dimana saja, kapan saja tanpa mengenal jarak dan waktu. Sehingga wisata industri yang ada di Kabupaten Bekasi dapat diinformasikan dengan cepat, tepat dan akurat serta informasi dapat digabungkan dengan sistem informasi geografis yang dapat melakukan pemetaan dimana lokasi wisata industri itu berada. Perancangan SIG Wisata Industri ini menggunakan bahasa pemograman PHP dan pada webnya menggunakan codeigneter dengan plugin Google Maps API, metode pengembangan sistem yang digunakan metode zachman framework dengan pemodelan kerangka pemikiran dan UML (Unifed Modelling Language), melalui perancangan ini diharapkan dapat memberikan sumbangan ide kepada Dinas Pariwisata Kabupaten Bekasi dalam upaya mempromosikan wisata industri kepada masyarakat.   Kata kunci: Google Maps API, Sistem Informasi Geografis, Wisata industri, Zachman Framework.

scholarly journals Geo-online explanatory data visualization tools as crisis management and communication instruments

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
Silvia Grandi ◽  
Anna Bernasconi
Keyword(s):  
Data Visualization ◽  
Geographical Information Systems ◽  
Online Communication ◽  
Spatial Dimension ◽  
Decision Makers ◽  
Geographical Information ◽  
Disease Spread ◽  
Geospatial Information ◽  
Online Tools ◽  
Available Information

Abstract. Communication during emergency and crises times is a critical aspect. When available information contains a spatial dimension, maps and interactive localization features may help conveying strong messages to audiences that are otherwise difficult to reach. The COVID-19 pandemic has prompted the design and implementation of a great number of online tools to communicate data of the disease spread and its dynamics that are helpful to support informed decisions for both people in their everyday life and decision makers. Observing this phenomenon has inspired this conceptualization of the geo-Online Explanatory Data Visualization (geo-OEDV) tools, set in the context of available geospatial information, of statistical visualisation tools and of the solid tradition of Geographical Information Systems. Blending classical statistical tools, digital cartography, and the confluence of many elements into a single screen, has produced the currently most spread geo-OEDV instance, i.e., the geo-dashboard and geo-infographics. In particular this paper conceptualises geo-OEDV as a category of meta-cartography that blends online communication with cartographic representation and management principles.

scholarly journals Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Carlos Mena ◽  
Cesar Sepúlveda ◽  
Eduardo Fuentes ◽  
Yony Ormazábal ◽  
Iván Palomo
Keyword(s):  
Spatial Analysis ◽  
Cardiovascular Diseases ◽  
Geographical Information Systems ◽  
Spatial Regression ◽  
Glycated Haemoglobin ◽  
Statistical Weight ◽  
Cluster Detection ◽  
Geographical Information ◽  
Local Cluster ◽  
Populations At Risk

Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study (e.g., rural, deprived neighbourhoods, etc.), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources.

Discovering Requirements for the Technology Design to Support Disaster Resilience Analytics

2019 ◽  
Vol 11 (2) ◽  
pp. 20-37
Author(s):  
Kathleen Moore ◽  
Hemant Purohit
Keyword(s):  
Crisis Management ◽  
Information And Communication Technologies ◽  
Geographical Information Systems ◽  
Semantic Network ◽  
Open Data ◽  
Holistic Approach ◽  
Geographical Information ◽  
Disaster Resilience ◽  
Technology Design ◽  
Information And Communication

Research on technology-assisted crisis management have been centered on tools to assist the response phase of a disaster. Through a semantic network analysis of concept relations in the titles of the publications, the authors found that many theoretical tools exist for disaster management but have not been operationalized to take a holistic approach toward technology for resilience. There is a lack of emphasis on the design of information and communication technologies, besides geographical information systems, to assist other phases of the crisis management cycle, particularly the preparedness and mitigation phases for resilience. By operationalizing the MOVE framework in a case study, the authors discover factors critical to the design of informatics and visualization tools to support resilience. This study concludes with a conceptual design framework “Digital Crow's Nest” to show feasibility of technology design for disaster resilience analytics using open data sources.

scholarly journals Datos, patrones y narrativas: Nuevas perspectivas sobre la Guerra Civil y la represión franquista a partir de la visualización de datos abiertos

2020 ◽  
Author(s):  
Xavier Rubio-Campillo ◽  
Maria Feliu Torruella ◽  
Tania González Cantera
Keyword(s):  
Spanish Civil War ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Open Data ◽  
Geographical Information ◽  
Digital Tools ◽  
Scientific Practices ◽  
Mass Graves ◽  
Online Databases ◽  
Datos Abiertos

Recent years have seen a substantial increase on the number of online databases and websites providing information about the Spanish Civil War and Francoist repression. These resources can be used to find information about individuals, but the data they provide has seldom been used to develop research on large-scale historical dynamics.This paper introduces new Digital Humanities-based approaches to the information provided by these databases. The work discusses the challenges posed by the use of the current websites in relation to current scientific practices and particularly to the adoption of open data policies. Next, we propose the use of quantitative analytical methods as a way to generate new perspectives for historical research. This approach is exemplified on two case studies where different digital tools have been applied: a) the spatial distribution of mass-graves using Geographical Information Systems and b) the scale of Francoist repression in Catalonia with Data Visualization.

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