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Spatial Syndromic Surveillance and COVID-19 in the U.S.: Local Cluster Mapping for Pandemic Preparedness

Author

Listed:
  • Andrew J. Curtis

    (Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA)

  • Jayakrishnan Ajayakumar

    (Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA)

  • Jacqueline Curtis

    (Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA)

  • Sam Brown

    (University Hospitals, Cleveland, OH 44106, USA)

Abstract

Maps have become the de facto primary mode of visualizing the COVID-19 pandemic, from identifying local disease and vaccination patterns to understanding global trends. In addition to their widespread utilization for public communication, there have been a variety of advances in spatial methods created for localized operational needs. While broader dissemination of this more granular work is not commonplace due to the protections under Health Insurance Portability and Accountability Act (HIPAA), its role has been foundational to pandemic response for health systems, hospitals, and government agencies. In contrast to the retrospective views provided by the aggregated geographies found in the public domain, or those often utilized for academic research, operational response requires near real-time mapping based on continuously flowing address level data. This paper describes the opportunities and challenges presented in emergent disease mapping using dynamic patient data in the response to COVID-19 for northeast Ohio for the period 2020 to 2022. More specifically it shows how a new clustering tool developed by geographers in the initial phases of the pandemic to handle operational mapping continues to evolve with shifting pandemic needs, including new variant surges, vaccine targeting, and most recently, testing data shortfalls. This paper also demonstrates how the geographic approach applied provides the framework needed for future pandemic preparedness.

Suggested Citation

  • Andrew J. Curtis & Jayakrishnan Ajayakumar & Jacqueline Curtis & Sam Brown, 2022. "Spatial Syndromic Surveillance and COVID-19 in the U.S.: Local Cluster Mapping for Pandemic Preparedness," IJERPH, MDPI, vol. 19(15), pages 1-15, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:8931-:d:869321
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    References listed on IDEAS

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    1. Anna Kimberly Miller & Jennifer Catherine Gordon & Jacqueline W. Curtis & Jayakrishnan Ajayakumar & Fredrick R. Schumacher & Stefanie Avril, 2022. "The Geographic Context of Racial Disparities in Aggressive Endometrial Cancer Subtypes: Integrating Social and Environmental Aspects to Discern Biological Outcomes," IJERPH, MDPI, vol. 19(14), pages 1-12, July.
    2. Desmet, Klaus & Wacziarg, Romain, 2022. "JUE Insight: Understanding spatial variation in COVID-19 across the United States," Journal of Urban Economics, Elsevier, vol. 127(C).
    3. Jayson S. Jia & Xin Lu & Yun Yuan & Ge Xu & Jianmin Jia & Nicholas A. Christakis, 2020. "Population flow drives spatio-temporal distribution of COVID-19 in China," Nature, Nature, vol. 582(7812), pages 389-394, June.
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