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This paper is in the following e-collection/theme issue:

GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (227) Public (e)Health, Digital Epidemiology and Public Health Informatics (2221) Infectious Diseases (non-STD/STI) (1898) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (2028) Outbreak and Pandemic Preparedness and Management (1952) JMIR Theme Issue: COVID-19 Special Issue (4231) Geographic Information Systems (GIS) (27)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49871, first published .
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Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study

Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study

Authors of this article:

Rachel Martonik1 Author Orcid Image ;   Caitlin Oleson2 Author Orcid Image ;   Ellyn Marder2 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Saavedra R, Carvalho-Sauer R, Ichihara M, Costa M, Soares E, Teixeira M. Analysis of the Spatiotemporal Spread of COVID-19 in Bahia, Brazil: A Cluster-Based Study, 2020–2022. COVID 2025;5(7):109 View
  2. Lu P, Jain S, León T, White L. CalCORVID: a dynamic RShiny dashboard approach to visualize spatiotemporal clusters for public health surveillance. BMC Public Health 2026;26(1) View
  3. Li F, Zhu W, Pan J, Lee I. Spatiotemporal density peaks clustering algorithm based on local covariance and shared spatiotemporal nearest neighbors. Applied Soft Computing 2026;201:115727 View