Advances in Computational Approaches for Geospatial Health Applications III

Type: Paper
Theme: Geography, GIScience and Health: Building an International Geospatial Health Research Network (IGHRN)
Sponsor Groups: Spatial Analysis and Modeling Specialty Group, Cyberinfrastructure Specialty Group, Health and Medical Geography Specialty Group
Poster #:
Day: 4/5/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Marshall South, Marriott, Mezzanine Level
Organizers: Marco Helbich, Claudio Owusu, Alexander Hohl
Chairs: Marco Helbich

Description

Advanced computational capabilities that emerged through continuous technological and methodological developments have transformed many scientific disciplines, including the domain of health and medical geography. Today, scientists tackle computational challenges that used to be virtually impossible to solve, because 1) our ability to collect and store health-related data has improved substantially, and 2) analytical methods for solving scientific problems can now be applied on a massive scale. Therefore, the spatiotemporal analysis and modelling of health-related issues has experienced and driven fundamental changes.

The goal of this session is to create a platform for presenting and stimulate discussion of the accomplishments and remaining challenges of applying and developing computational methods that improve our understanding of health and medical geography. Session(s) organized via this CFP will be part of the AAG 2019 Special Theme on Geography, GIScience, and Health: Building an International Geospatial Health Research Network (IGHRN).

Topics may include, but are not limited to:

1. Disease mapping: spatial and/or spatiotemporal analysis and visualization;
2. Disparities in health care accessibility;
3. Stochastic methods for assessing the significance of observed disease patterns;
4. Spatially explicit and space-time disease modeling (retrospective or prospective);
5. The use of high-performance computing to analyze complex and massive spatiotemporal data for the discovery of relationships and patterns between health and environment;
6. Data science approaches, including statistics, data mining, and machine learning, to address issues within health and medical geography.

Sponsor Groups: Spatial Analysis and Modeling Specialty Group, Cyberinfrastructure Specialty Group, Health and Medical Geography Specialty Group

Discussants: Dr. Xun Shi (Dartmouth), Dr. Eric Delmelle (UNC-Charlotte)

If you are interested in joining this session, please email your PIN, title, abstract, and contact information to the following organizers: Michael R. Desjardins (UNC-Charlotte; mdesjar2@uncc.edu), Claudio Owusu (UNC-Charlotte; cowusu@uncc.edu), Alexander Hohl (Utica College; alhohl@utica.edu), and Marco Helbich (Utrecht University, m.helbich@uu.nl). Please note that we will not accept submissions after the AAG deadline.


Agenda

Type Details Minutes Start Time
Presenter Marco Helbich*, Utrecht University, Going beyond the mean and linearity: A better way to understand green space-mental health associations? 20 3:05 PM
Presenter Markku Tykkylainen*, University of Eastern Finland, Pasi Fränti, Univeristy of Eastern Finland, Tiina Laatikainen, National Institute for Health and Welfare, Geospatial health research and planning as interdisciplinary research and its evolutionary milestones 20 3:25 PM
Presenter Fahui Wang*, Lousiana State University, Tracy Onega, Geisel School of Medicine at Dartmouth, Automated Delineation of Cancer Service Areas in the Northeast Region of U.S. 20 3:45 PM
Presenter Alastair Munro*, University of Nottingham, Long-Term Spatiotemporal Changes in Endemic Threshold Populations in England & Wales – A Multi-Disease Study 20 4:05 PM
Discussant Xun Shi Dartmouth College 20 4:25 PM

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