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

JMIR Theme Issue: COVID-19 Special Issue (2243) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1386) Infectious Diseases (non-STD/STI) (1289) Hygiene and Infection Prevention (260) Surveillance Systems (391) Outbreak and Pandemic Preparedness and Management (1530) Innovative Methods in Public Health and Surveillance (266) Infodemiology and Infoveillance (1128)

Published on in Vol 23 , No 4 (2021) :April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27045, first published .
Spatial-Temporal Relationship Between Population Mobility and COVID-19 Outbreaks in South Carolina: Time Series Forecasting Analysis

Spatial-Temporal Relationship Between Population Mobility and COVID-19 Outbreaks in South Carolina: Time Series Forecasting Analysis

Spatial-Temporal Relationship Between Population Mobility and COVID-19 Outbreaks in South Carolina: Time Series Forecasting Analysis

Authors of this article:

Chengbo Zeng 1, 2, 3 Author Orcid Image ;   Jiajia Zhang 1, 3, 4 Author Orcid Image ;   Zhenlong Li 1, 3, 5 Author Orcid Image ;   Xiaowen Sun 1, 3, 4 Author Orcid Image ;   Bankole Olatosi 1, 3, 6 Author Orcid Image ;   Sharon Weissman 1, 3, 7 Author Orcid Image ;   Xiaoming Li 1, 2, 3 Author Orcid Image
Article Authors Cited by (15) Tweetations (6) Metrics

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  5. Ensoy-Musoro C, Nguyen M, Hens N, Molenberghs G, Faes C. Spatio-temporal model to investigate COVID-19 spread accounting for the mobility amongst municipalities. Spatial and Spatio-temporal Epidemiology 2023;45:100568 View
  6. Jin W, Dong S, Yu C, Luo Q. A data-driven hybrid ensemble AI model for COVID-19 infection forecast using multiple neural networks and reinforced learning. Computers in Biology and Medicine 2022;146:105560 View
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