CFP: IJGIS Special Issue on “GeoHealth Data Science”
Cai Jiannan
Call for Papers
Special Issue of International Journal of Geographical Information Science
Special Issue Editors
Jiannan Cai, The Chinese University of Hong Kong, jn...@cuhk.edu.hk
Mei-Po Kwan, The Chinese University of Hong Kong, mpk...@cuhk.edu.hk
Min Deng, Central South University, den...@csu.edu.cn
Shashi Shekhar, University of Minnesota, she...@umn.edu
Yiqun Xie, University of Maryland, x...@umd.edu
The Theme and Scope
Due to rapid advancements in location-aware technologies (e.g., global positioning system (GPS) trackers) and smart sensors (e.g., wearable environmental and biomedical sensors), we now have unprecedented access to vast amounts of highly accurate geospatial data relevant to human health and disease. These geospatial data promise new spatial insights into the health behaviors and outcomes of individuals, leading to a transformative shift towards spatially-informed health research. Meanwhile, the multimodal data sourced from different sensors also presents methodological challenges in health research due to the high heterogeneity of data in terms of spatial-temporal granularity, scale, structure, and semantics. The health data revolution thus calls for a geospatial data science paradigm to explore new forms of geographic knowledge underlying the complex formation and transmission processes of diseases and health risks, as well as their prediction and transfer involving space, time, and context.
The recent emerging geospatial data science techniques in artificial intelligence (GeoAI), machine learning, and data mining have demonstrated their ability to extract valuable geographic knowledge to support inferences and decision-making from geospatial big data. However, current health research largely applies existing data science methods without explicitly considering the unique characteristics of geospatial data (e.g., spatial autocorrelation and spatial heterogeneity). This oversight can limit or even bias health-related geographic understanding and undermine the effectiveness of health intervention policies. Furthermore, as human health and disease emerge as the intricate result of the interplay among human behaviors, natural environments, social contexts, and many other factors, the complex nature poses intrinsic methodological challenges and necessitates innovative geospatial data science methods.
This special issue seeks to promote leveraging the geospatial data science paradigm in advancing the geographic knowledge discovery, prediction, and transfer in health research (geohealth data science). In particular, we welcome submissions that focus on developing new spatially explicit data science methods or innovatively improving state-of-the-art methods with multimodal data sources to address methodological issues in existing health research or explore new spatially-informed health research topics.
Relevant Topics Include, But Are Not Limited To
Novel theories and methods in geohealth data science
Addressing methodological issues in geohealth research
Perception, assessment, and early warning of health risks with novel geospatial datasets
Spatiotemporal pattern detection of diseases and/or health risk factors
Spatiotemporal association analysis and causal inference among diseases, human behaviors and health risk factors
Spatiotemporal spread and prediction of infectious diseases
Effects of human mobility on disease transmission
Transferability of geohealth knowledge over space and time
Submission Procedure
This IJGIS special issue welcomes submissions by scholars from all disciplines. Interested authors should first submit a short abstract (250 words max) to Jiannan Cai (jn...@cuhk.edu.hk), Mei-Po Kwan (mpk...@cuhk.edu.hk) and Yiqun Xie (x...@umd.edu) before January 24, 2024. Guest editors will review the submitted abstracts and evaluate whether the submissions fit the themes of this SI. Authors of abstracts with suitable topics will be invited to submit full manuscripts, while the invitation does not guarantee acceptance to the SI.
Full manuscripts, including any supporting materials, should be submitted using the journal's submission portal by April 30, 2024, and the authors should specify this SI as the target during their submission.
Important Dates
Abstracts (no more than 250 words) Due: Jan. 24, 2024
Decisions on abstracts: Jan. 31, 2024
Full manuscripts Due: Apr. 30, 2024
Details
CFP website: https://bit.ly/GeoHealth_Data
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Dr. Jiannan Cai
RGC Postdoctoral Fellow
Institute of Space and Earth Information Science
The Chinese University of Hong Kong
Email: jn...@cuhk.edu.hk
https://sites.google.com/view/jiannancai
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