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COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis.

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Participatory surveillance programs track COVID-19 symptoms for early outbreak detection. Improved coordination between these programs and public health authorities is needed for effective pandemic response.

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COVID-19coronavirusframework analysisinformation resourcesmonitoringpatient-reported outcome measuresself-reportedsurveillancesymptom trackingsynthesis

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Area of Science:

  • Public Health
  • Epidemiology
  • Health Informatics

Background:

  • The ongoing spread of COVID-19 necessitates early identification of potential outbreaks.
  • Participatory surveillance technologies enable individuals to report symptoms daily, aiding public health preparedness.

Purpose of the Study:

  • Evaluate existing self-reported symptom tracking programs for COVID-19 in the U.S. as an early-warning system.
  • Inform decision-makers and health planners on the utility of these technologies for pandemic response.

Main Methods:

  • Framework synthesis approach used to evaluate symptom tracking programs.
  • Programs identified via keyword searches and snowball sampling, followed by screening.
  • A comparative framework constructed by collating data from included programs.

Main Results:

  • Six out of eight screened programs were included in the final synthesis.
  • Common data elements included demographics (age, race, gender, affiliation).
  • Variations observed in data collection regarding smoking, mental well-being, and exposure.

Conclusions:

  • Multiple COVID-19 symptom tracking programs are operational.
  • A lack of coordination exists between research teams and public health authorities.
  • Collaboration opportunities identified to enhance knowledge dissemination and avoid duplicated efforts.