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10.2196/23297 http://scihub22266oqcxt.onion/10.2196/23297 33006943!7584449!33006943     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Internet+Res 2020 ; 22 (10): e23297 Nephropedia Template TP {{tp|p=33006943|t=2020. COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis |pdf=|usr=}}{{33006943}} gab.com Text COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis JO: J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=33006943 #FOAvip 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. Twit Text FOAVip COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis ????J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=33006943 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33006943 #FOAvip English Wikipedia <ref>{{Cite pmid|33006943}}</ref> COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis #MMPMID33006943 Koehlmoos TP; Janvrin ML; Korona-Bailey J; Madsen C; Sturdivant R J Med Internet Res 2020[Oct]; 22 (10): e23297 PMID33006943show ga 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. |*Self Report[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*diagnosis/*physiopathology[MESH] |Delivery of Health Care[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Pandemics[MESH] |Pneumonia, Viral/*diagnosis/*physiopathology[MESH] |Public Health Surveillance/*methods[MESH] |SARS-CoV-2[MESH]COVID-19 Self-Reported Symptom Tracking Programs in the United States:(epmc).pdf DeepDyve Pubget Overpricing