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

Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (161) JMIR Theme Issue: COVID-19 Special Issue (2553) Prevention and Health Promotion (1360) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1542) Outbreak and Pandemic Preparedness and Management (1826) Infectious Diseases (non-STD/STI) (1725) Hygiene and Infection Prevention (374)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36538, first published .
A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis

A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis

A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis

Authors of this article:

Chengzhuo Tong1 Author Orcid Image ;   Wenzhong Shi1 Author Orcid Image ;   Anshu Zhang1 Author Orcid Image ;   Zhicheng Shi2 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

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  1. Kost G, Eng M, Zadran A. Geospatial Point-of-Care Testing Strategies for COVID-19 Resilience in Resource-Poor Settings: Rural Cambodia Field Study. JMIR Public Health and Surveillance 2024;10:e47416 View
  2. Moore H, Turner C, Rawlinson C, Chen C, Verlander N, Anderson C, Hughes G. Risk factors for COVID-19 transmission in England: a multilevel modelling study using routine contact tracing data. Epidemiology and Infection 2024;152 View
  3. Li J, Tseng Y, Chen S, Chen K. Artificial Intelligence in Infection Surveillance: Data Integration, Applications and Future Directions. Biomedical Journal 2025:100929 View