Spatial Syndromic Surveillance and Covid-19 in the U.S

Local Cluster Mapping for Pandemic Preparedness

Bibliographic Data

ID17801111
AuthorsAndrew Curtis (0000-0001-6046-6476, Case Western Reserve University), Jayakrishnan Ajayakumar (0000-0001-9564-7728, Case Western Reserve University), Steven P Brown (0000-0003-1892-9275, University Hospitals of Cleveland), Sam Brown (0000-0002-2747-7859, University Hospitals, Cleveland, OH 44106, USA)
Year2022
Volume19
Issue15
Pages8931-8931
Publication date2022-07-22
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19158931
PMID35897298
OpenAlexW4286586931
LanguageEN
Citations received1
References cited41

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

Business · Computer security · Confidentiality · Data science · Disease · Geography · Health Insurance Portability and Accountability Act · Pandemic · Political science · Preparedness · Public health · Computer Science · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Medicine · Zoonotic diseases and public health