Cargando…
COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis
BACKGROUND: With the continued spread of COVID-19 in the United States, identifying potential outbreaks before infected individuals cross the clinical threshold is key to allowing public health officials time to ensure local health care institutions are adequately prepared. In response to this need,...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584449/ https://www.ncbi.nlm.nih.gov/pubmed/33006943 http://dx.doi.org/10.2196/23297 |
_version_ | 1783599594214522880 |
---|---|
author | Koehlmoos, Tracey Pérez Janvrin, Miranda Lynn Korona-Bailey, Jessica Madsen, Cathaleen Sturdivant, Rodney |
author_facet | Koehlmoos, Tracey Pérez Janvrin, Miranda Lynn Korona-Bailey, Jessica Madsen, Cathaleen Sturdivant, Rodney |
author_sort | Koehlmoos, Tracey Pérez |
collection | PubMed |
description | BACKGROUND: With the continued spread of COVID-19 in the United States, identifying potential outbreaks before infected individuals cross the clinical threshold is key to allowing public health officials time to ensure local health care institutions are adequately prepared. In response to this need, researchers have developed participatory surveillance technologies that allow individuals to report emerging symptoms daily so that their data can be extrapolated and disseminated to local health care authorities. OBJECTIVE: This study uses a framework synthesis to evaluate existing self-reported symptom tracking programs in the United States for COVID-19 as an early-warning tool for probable clusters of infection. This in turn will inform decision makers and health care planners about these technologies and the usefulness of their information to aid in federal, state, and local efforts to mobilize effective current and future pandemic responses. METHODS: Programs were identified through keyword searches and snowball sampling, then screened for inclusion. A best fit framework was constructed for all programs that met the inclusion criteria by collating information collected from each into a table for easy comparison. RESULTS: We screened 8 programs; 6 were included in our final framework synthesis. We identified multiple common data elements, including demographic information like race, age, gender, and affiliation (all were associated with universities, medical schools, or schools of public health). Dissimilarities included collection of data regarding smoking status, mental well-being, and suspected exposure to COVID-19. CONCLUSIONS: Several programs currently exist that track COVID-19 symptoms from participants on a semiregular basis. Coordination between symptom tracking program research teams and local and state authorities is currently lacking, presenting an opportunity for collaboration to avoid duplication of efforts and more comprehensive knowledge dissemination. |
format | Online Article Text |
id | pubmed-7584449 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-75844492020-10-28 COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis Koehlmoos, Tracey Pérez Janvrin, Miranda Lynn Korona-Bailey, Jessica Madsen, Cathaleen Sturdivant, Rodney J Med Internet Res Original Paper BACKGROUND: With the continued spread of COVID-19 in the United States, identifying potential outbreaks before infected individuals cross the clinical threshold is key to allowing public health officials time to ensure local health care institutions are adequately prepared. In response to this need, researchers have developed participatory surveillance technologies that allow individuals to report emerging symptoms daily so that their data can be extrapolated and disseminated to local health care authorities. OBJECTIVE: This study uses a framework synthesis to evaluate existing self-reported symptom tracking programs in the United States for COVID-19 as an early-warning tool for probable clusters of infection. This in turn will inform decision makers and health care planners about these technologies and the usefulness of their information to aid in federal, state, and local efforts to mobilize effective current and future pandemic responses. METHODS: Programs were identified through keyword searches and snowball sampling, then screened for inclusion. A best fit framework was constructed for all programs that met the inclusion criteria by collating information collected from each into a table for easy comparison. RESULTS: We screened 8 programs; 6 were included in our final framework synthesis. We identified multiple common data elements, including demographic information like race, age, gender, and affiliation (all were associated with universities, medical schools, or schools of public health). Dissimilarities included collection of data regarding smoking status, mental well-being, and suspected exposure to COVID-19. CONCLUSIONS: Several programs currently exist that track COVID-19 symptoms from participants on a semiregular basis. Coordination between symptom tracking program research teams and local and state authorities is currently lacking, presenting an opportunity for collaboration to avoid duplication of efforts and more comprehensive knowledge dissemination. JMIR Publications 2020-10-22 /pmc/articles/PMC7584449/ /pubmed/33006943 http://dx.doi.org/10.2196/23297 Text en ©Tracey Pérez Koehlmoos, Miranda Lynn Janvrin, Jessica Korona-Bailey, Cathaleen Madsen, Rodney Sturdivant. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.10.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Koehlmoos, Tracey Pérez Janvrin, Miranda Lynn Korona-Bailey, Jessica Madsen, Cathaleen Sturdivant, Rodney COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |
title | COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |
title_full | COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |
title_fullStr | COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |
title_full_unstemmed | COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |
title_short | COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |
title_sort | covid-19 self-reported symptom tracking programs in the united states: framework synthesis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584449/ https://www.ncbi.nlm.nih.gov/pubmed/33006943 http://dx.doi.org/10.2196/23297 |
work_keys_str_mv | AT koehlmoostraceyperez covid19selfreportedsymptomtrackingprogramsintheunitedstatesframeworksynthesis AT janvrinmirandalynn covid19selfreportedsymptomtrackingprogramsintheunitedstatesframeworksynthesis AT koronabaileyjessica covid19selfreportedsymptomtrackingprogramsintheunitedstatesframeworksynthesis AT madsencathaleen covid19selfreportedsymptomtrackingprogramsintheunitedstatesframeworksynthesis AT sturdivantrodney covid19selfreportedsymptomtrackingprogramsintheunitedstatesframeworksynthesis |