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Special Issue "GIS in Public Health"

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (30 November 2013)

Special Issue Editor

Guest Editor
Dr. Stefania Bertazzon

Department Geography University of Calgary 2500 University Dr. NW T2N 1N4 Calgary, AB, Canada
Website | E-Mail
Phone: +1(403)220-7355
Fax: +1(403)282-6561
Interests: geography of health; spatial analysis; Quantitative analysis in the social sciences

Special Issue Information

Dear Colleagues,

Sharing one world is no easy task. Living on a planet afflicted by aging populations, massive migrations, climate change and environmental degradation, public health has significant obstacles to overcome in providing for over 7 billion people. Thankfully, our ability to employ science and technology to solve public health issues is also increasing rapidly. Many of the challenges are geographical, hence part of the solutions can be sought with the use of Geographical Information Systems (GIS).
For a long time public health has recognized that GIS provides powerful tools to map and visually summarize large amounts of spatial information. At the same time, geographers have recognized that the benefits of GIS in public heath extend well beyond these traditional tasks. Public health, like many other fields, can now count on virtually endless streams of data ("Big Data"), acquired from diverse sources, ranging from satellite imagery to mobile telematics and volunteered geographic information. This wealth of data is paralleled by accessible and inexpensive computational power, which allows for easy processing. Thus, the challenges of GIS have shifted to analysis, including concepts, representation, modeling and reliability. Further challenges are posed by GIS implementation in public health: ethical issues concerning the analysis of personal data; social and cultural spaces; and individual mobility. Today’s increasingly data rich environment offers a host of opportunities, and addressing these challenges can truly develop the potential of GIS in providing effective solutions in public health research and practice.
We welcome paper submissions addressing the opportunities and challenges of GIS implementation in public health research and practice. Topics include, but are not limited to:
•Geographical analysis of health telematics data;
•Spatial data mining of large amounts of health data;
•Environmental health risks analysis;
•Novel methods for spatio-temporal analysis of disease;
•Representations of spaces and places of public health;
•Ethical issues and the balance between individual privacy and spatial aggregation;
•Integrating qualitative analysis in public health GIS research

Dr. Stefania Bertazzon
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 900 CHF (Swiss Francs).


Keywords

•GIS
•public health
•spatial analysis
•big data
•health geography
•disease mapping
•medical geography
•health care

Published Papers (5 papers)

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Editorial

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Open AccessEditorial GIS and Public Health
ISPRS Int. J. Geo-Inf. 2014, 3(3), 868-870; doi:10.3390/ijgi3030868
Received: 19 June 2014 / Accepted: 26 June 2014 / Published: 30 June 2014
PDF Full-text (78 KB) | HTML Full-text | XML Full-text
Abstract
This Special Issue on GIS and public health is the result of a highly selective process, which saw the participation of some 20 expert peer-reviewers and led to the acceptance of one half of the high-quality submissions received over the past year. Many threads
[...] Read more.
This Special Issue on GIS and public health is the result of a highly selective process, which saw the participation of some 20 expert peer-reviewers and led to the acceptance of one half of the high-quality submissions received over the past year. Many threads link these papers to each other and, indeed, to our original call for papers, but the element that most clearly emerges from these works is the inextricable connection between public health and the environment. Indeed, GIS analysis of public health simply cannot disregard the geospatial dimension of environmental resources and risks. What consistently emerges from these analyses is that current geospatial research can only scratch the surface of the complex interactions of spatial resources, risks, and public health. In today’s world, or at least in the developed world, researchers and practitioners can count on virtually endless data, on inexpensive computational power, and on seamless connectivity. In this research environment, these papers point to the need for improved analytical tools, covering concepts, representation, modeling and reliability. These works are important contributions that help us to identify what advances in geospatial analysis can better address the complex interactions of public health with our physical and cultural environment, and bridge research and practice, so that geospatial analyses can inform public health policy making. [...] Full article
(This article belongs to the Special Issue GIS in Public Health)

Research

Jump to: Editorial, Review

Open AccessArticle Spatial and Semantic Validation of Secondary Food Source Data
ISPRS Int. J. Geo-Inf. 2014, 3(1), 236-253; doi:10.3390/ijgi3010236
Received: 28 November 2013 / Revised: 6 February 2014 / Accepted: 12 February 2014 / Published: 28 February 2014
Cited by 3 | PDF Full-text (933 KB) | HTML Full-text | XML Full-text
Abstract
Governmental and commercial lists of food retailers are often used to measure food environments and foodscapes for health and nutritional research. Information about the validity of such secondary food source data is relevant to understanding the potential and limitations of its application. This
[...] Read more.
Governmental and commercial lists of food retailers are often used to measure food environments and foodscapes for health and nutritional research. Information about the validity of such secondary food source data is relevant to understanding the potential and limitations of its application. This study assesses the validity of two government lists of food retailer locations and types by comparing them to direct field observations, including an assessment of whether pre-classification of the directories can reduce the need for field observation. Lists of food retailers were obtained from the Central Business Register (CVR) and the Smiley directory. For each directory, the positive prediction value (PPV) and sensitivity were calculated as measures of completeness and thematic accuracy, respectively. Standard deviation was calculated as a measure of geographic accuracy. The effect of the pre-classification was measured through the calculation of PPV, sensitivity and negative prediction value (NPV). The application of either CVR or Smiley as a measure of the food environment would result in a misrepresentation. The pre-classification based on the food retailer names was found to be a valid method for identifying approximately 80% of the food retailers and limiting the need for field observation. Full article
(This article belongs to the Special Issue GIS in Public Health)
Open AccessArticle Spatio-Temporal Occurrence Modeling of Highly Pathogenic Avian Influenza Subtype H5N1: A Case Study in the Red River Delta, Vietnam
ISPRS Int. J. Geo-Inf. 2013, 2(4), 1106-1121; doi:10.3390/ijgi2041106
Received: 27 September 2013 / Revised: 14 November 2013 / Accepted: 22 November 2013 / Published: 28 November 2013
Cited by 6 | PDF Full-text (897 KB) | HTML Full-text | XML Full-text
Abstract
Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 poses severe threats to both animals and humans. Investigating where, when and why the disease occurs is important to help animal health authorities develop effective control policies. This study takes into account spatial and temporal occurrence
[...] Read more.
Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 poses severe threats to both animals and humans. Investigating where, when and why the disease occurs is important to help animal health authorities develop effective control policies. This study takes into account spatial and temporal occurrence of HPAI H5N1 in the Red River Delta of Vietnam. A two-stage procedure was used: (1) logistic regression modeling to identify and quantify factors influencing the occurrence of HPAI H5N1; and (2) a geostatistical approach to develop monthly predictive maps. The results demonstrated that higher average monthly temperatures and poultry density in combination with lower average monthly precipitation, humidity in low elevation areas, roughly from November to January and April to June, contribute to the higher occurrence of HPAI H5N1. Provinces near the Gulf of Tonkin, including Hai Phong, Hai Duong, Thai Binh, Nam Dinh and Ninh Binh are areas with higher probability of occurrence of HPAI H5N1. Full article
(This article belongs to the Special Issue GIS in Public Health)
Open AccessArticle Mapping Ontario’s Wind Turbines: Challenges and Limitations
ISPRS Int. J. Geo-Inf. 2013, 2(4), 1092-1105; doi:10.3390/ijgi2041092
Received: 20 September 2013 / Revised: 19 October 2013 / Accepted: 22 November 2013 / Published: 27 November 2013
Cited by 3 | PDF Full-text (436 KB) | HTML Full-text | XML Full-text
Abstract
Despite rapid and vast development of wind turbines across the Canadian province of Ontario, there is no map available indicating the location of each wind turbine. A map of this nature is crucial for health and environmental risk research and has many applications
[...] Read more.
Despite rapid and vast development of wind turbines across the Canadian province of Ontario, there is no map available indicating the location of each wind turbine. A map of this nature is crucial for health and environmental risk research and has many applications in other fields. Research examining health and wind turbines is limited by the available maps showing the nearest community to a wind farm as opposed to each unique wind turbine. Data from provincial-level organizations, developers, and municipalities were collected using government development approval documents, planning documents, and data given directly from municipalities and developers. Wind turbines were mapped using Google Earth, coordinate lists, shapefiles, and translating data from other maps. In total, 1,420 wind turbines were mapped from 56 wind farms. The limitations of each data source and mapping method are discussed. There are numerous challenges in creating a map of this nature, for example incorrect inclusion of wind farms and inaccuracies in wind turbine locations. The resultant map is the first of its kind to be discussed in the literature, can be used for a variety of health and environmental risk studies to assess dose-response, wind turbine density, visibility, and to create sound and vibration models. Full article
(This article belongs to the Special Issue GIS in Public Health)

Review

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Open AccessReview Web GIS-Based Public Health Surveillance Systems: A Systematic Review
ISPRS Int. J. Geo-Inf. 2014, 3(2), 481-506; doi:10.3390/ijgi3020481
Received: 26 November 2013 / Revised: 14 January 2014 / Accepted: 20 March 2014 / Published: 1 April 2014
Cited by 3 | PDF Full-text (807 KB) | HTML Full-text | XML Full-text
Abstract
Web Geographic Information System (Web GIS) has been extensively and successfully exploited in various arenas. However, to date, the application of this technology in public health surveillance has yet to be systematically explored in the Web 2.0 era. We reviewed existing Web GIS-based
[...] Read more.
Web Geographic Information System (Web GIS) has been extensively and successfully exploited in various arenas. However, to date, the application of this technology in public health surveillance has yet to be systematically explored in the Web 2.0 era. We reviewed existing Web GIS-based Public Health Surveillance Systems (WGPHSSs) and assessed them based on 20 indicators adapted from previous studies. The indicators comprehensively cover various aspects of WGPHSS development, including metadata, data, cartography, data analysis, and technical aspects. Our literature search identified 58 relevant journal articles and 27 eligible WGPHSSs. Analyses of results revealed that WGPHSSs were frequently used for infectious-disease surveillance, and that geographical and performance inequalities existed in their development. The latest Web and Web GIS technologies have been used in developing WGPHSSs; however, significant deficiencies in data analysis, system compatibility, maintenance, and accessibility exist. A balance between public health surveillance and privacy concerns has yet to be struck. Use of news and social media as well as Web-user searching records as data sources, participatory public health surveillance, collaborations among health sectors at different spatial levels and among various disciplines, adaption or reuse of existing WGPHSSs, and adoption of geomashup and open-source development models were identified as the directions for advancing WGPHSSs. Full article
(This article belongs to the Special Issue GIS in Public Health)

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