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

Mobile Health (mhealth) (2765) Public (e)Health, Digital Epidemiology and Public Health Informatics (641) mHealth for Data Collection and Research (914) Behavioural Surveillance for Public Health (205) Innovative Methods in Public Health and Surveillance (306)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46026, first published .
Predictors of COVID-19 From a Statewide Digital Symptom and Risk Assessment Tool: Cross-Sectional Study

Predictors of COVID-19 From a Statewide Digital Symptom and Risk Assessment Tool: Cross-Sectional Study

Predictors of COVID-19 From a Statewide Digital Symptom and Risk Assessment Tool: Cross-Sectional Study

Authors of this article:

Benjamin L Schooley1 Author Orcid Image ;   Abdulaziz Ahmed2 Author Orcid Image ;   Justine Maxwell2 Author Orcid Image ;   Sue S Feldman2 Author Orcid Image
Article Authors Cited by Tweetations (3) Metrics

Benjamin L Schooley   1 , MBA, PhD ;   Abdulaziz Ahmed   2 , PhD ;   Justine Maxwell   2 , MPH, DrPH ;   Sue S Feldman   2 , RN, MEd, PhD

1 Brigham Young University, Provo, UT, United States

2 University of Alabama at Birmingham, Birmingham, AL, United States

Corresponding Author:

  • Sue S Feldman, RN, MEd, PhD
  • University of Alabama at Birmingham
  • 1716 9th Street South
  • SHP 590K
  • Birmingham, AL, 35294
  • United States
  • Phone: 1 205-975-0809
  • Email: sfeldman@uab.edu