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COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis
Tracey Pérez Koehlmoos1, Miranda Lynn Janvrin1,2, Jessica Korona-Bailey1,2
1Uniformed Services University, Bethesda, MD, United States.
Journal of Medical Internet Research
|October 2, 2020
Summary
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.
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.
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