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Health-Based Geographic Information Systems for Mapping and Risk Modeling of Infectious Diseases and COVID-19 to Support Spatial Decision-Making

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Translational Informatics

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1368))

Abstract

Infectious diseases remain an essential global challenge in public health. For instance, novel coronavirus (COVID-19) has resulted in significant negative impacts on public health, infecting more than 214 million people and causing 4.47 million deaths worldwide as of August 2021. Geographic Information Systems have played an essential role in managing, storing, analyzing, and mapping disease and related risk information. This article provides an overview of a broad topic on applications of GIS into infectious disease research. Our review follows the framework of human–environment interactions, focusing on the environmental and social factors that cause the disease outbreak and the role of humans in disease control, including public health policies and interventions such as social distancing/face covering practice and mobility modeling. The work identifies key spatial decision-making issues where GIS becomes valued in the agenda for infectious disease research and highlights the importance of adopting science-based policies to protect the public during the current and future pandemics.

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Acknowledgments

This work was supported by the COVID-19 Research Projects of West China Hospital Sichuan University (Grant no. HX-2019-nCoV-057), the Regional Innovation Cooperation between Sichuan and Guangxi Provinces (2020YFQ0019), and the National Natural Science Foundation of China (32070671).

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Authors and Affiliations

  1. Department of Geosciences, University of Arkansas, Fayetteville, AR, USA

    Xiao Huang

  2. Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA

    Renyi Zhang

  3. Texas A&M Transportation Institute, Texas A&M University, College Station, TX, USA

    Xiao Li & Bahar Dadashova

  4. Department of Remote Sensing and Photogrammetry, National Land Survey of Finland, Helsinki, Finland

    Lingli Zhu

  5. Department of Environmental Health Sciences, University at Albany, State University of New York, Albany, NY, USA

    Kai Zhang

  6. School of Hydraulic Engineering, Dalian University of Technology, Dalian, China

    Yu Li

  7. Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China

    Bairong Shen

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    Bairong Shen

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Huang, X. et al. (2022). Health-Based Geographic Information Systems for Mapping and Risk Modeling of Infectious Diseases and COVID-19 to Support Spatial Decision-Making. In: Shen, B. (eds) Translational Informatics. Advances in Experimental Medicine and Biology, vol 1368. Springer, Singapore. https://doi.org/10.1007/978-981-16-8969-7_8

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