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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1513) JMIR Theme Issue: COVID-19 Special Issue (2439) Web-based and Mobile Health Interventions (3247) Prevention and Health Promotion (955) Vaccination and Immunization in the Digital Age (365)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39166, first published .
Using Location Intelligence to Evaluate the COVID-19 Vaccination Campaign in the United States: Spatiotemporal Big Data Analysis

Using Location Intelligence to Evaluate the COVID-19 Vaccination Campaign in the United States: Spatiotemporal Big Data Analysis

Using Location Intelligence to Evaluate the COVID-19 Vaccination Campaign in the United States: Spatiotemporal Big Data Analysis

Authors of this article:

Qingfeng Li1 Author Orcid Image ;   James Cheng Peng2 Author Orcid Image ;   Diwakar Mohan1 Author Orcid Image ;   Brennan Lake3 Author Orcid Image ;   Alex Ruiz Euler3 Author Orcid Image ;   Brian Weir4 Author Orcid Image ;   Lena Kan1 Author Orcid Image ;   Cui Yang4 Author Orcid Image ;   Alain Labrique1 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Dong W, Miao Y, Shen Z, Zhang W, Bai J, Zhu D, Ren R, Zhang J, Wu J, Tarimo C, Ojangba T, Li Y. Quantifying Disparities in COVID-19 Vaccination Rates by Rural and Urban Areas: Cross-Sectional Observational Study. JMIR Public Health and Surveillance 2024;10:e50595 View
  2. Xu W, Wang Z, Attia N, Attia Y, Zhang Y, Zong H. An experienced racial-ethnic diversity dataset in the United States using human mobility data. Scientific Data 2024;11(1) View