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Tracking the burden, distribution, and impact of Post-COVID conditions in diverse populations for children, adolescents, and adults (Track PCC): passive and active surveillance protocols
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Author
Jones, Resa M.Andrews, Jennifer G.
Dalton, Alexandra F.
Dixon, Brian E.
Dzomba, Bari J.
Fernando, Shane I.
Pogreba-Brown, Kristen M.
Ortiz, Miguel Reina
Sharma, Vinita
Simmons, Nicole
Saydah, Sharon H.
Slen, Joshua
Smith, Lillian
McComack, Joanna
McCullough, Mac
Young, Brian
Arora, Megha Khatri
Epstein, Rebekah
Figueroa, Ralph
Mahotiere, Terry
Miller, Kathryn
Barrett, Lori
Dahlquist, McKenna
Busch, Dolores
Edinger, Tracy
Garcia, Pablo
Gibson, Richard
Hallvik, Sara
Sim, Emily
Flessner, Christian
Forsythe, Navina
Johnson, Maria
McLelland, Ryan
Sorenson, Joseph
Ayllon, Fatima
Feiler, Marina Oktapodas
Fukuhara, Matthew
Mishkin, Aaron
Phan, Thanh T. D.
Rajaeebaygi, Mehdi
Sinha, Radhika
Turella, John
Wang, Weiting
Wiedefeld, Lucie
Yucel, Recai
Robinson, Susan
Benavides, Argelia
Bessey, Kate
Brady, Shane
Catalfamo, Collin
Carr, Dametreea
Collins, Clancey
Cordova-Marks, Felina
Ernst, Kacey
Farland, Leslie
Gracia-Filion, Pamela
Frost, Scott
Heslin, Kelly
Jacobs, Elizabeth
Lauro, Priscilla
Nuno, Velia
Pettygrove, Sydney
Pilling, Vern
Robinson, Susan
Shilen, Alexandra
Subbian, Vignesh
Grannis, Shaun
Allen, Katie
Buelow, Lauren
Buck, Aaron
Duszynski, Tom
Fadel, William
Franks, Zamal
Griffith, Ashley
Myers, Laura J.
Price, John
Wiensch, Ashley
Xu, Hiping
Agedew, Abe
Edwards, Deja
Koumas, Emily
Slaughter, Douglas
Sullivan, Elizabeth
Wyche, Tracy
Brinkley, Jason
Brummer, Tana
Desale, Sameer
Devlin, Rebecca
Harpole, Charles
Hunt, Danielle Rentz
Jeddy, Zuha
Poe, Brandon
Pickett, Steve
Sewell, Erica
Sokol, Brian
Stein, Karen
Thomas, Joseph
Affiliation
Department of Pediatrics, University of ArizonaIssue Date
2024-08-29
Metadata
Show full item recordPublisher
Springer Science and Business Media LLCCitation
Jones, R.M., Andrews, J.G., Dalton, A.F. et al. Tracking the burden, distribution, and impact of Post-COVID conditions in diverse populations for children, adolescents, and adults (Track PCC): passive and active surveillance protocols. BMC Public Health 24, 2345 (2024). https://doi.org/10.1186/s12889-024-19772-4Journal
BMC Public HealthRights
© The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Background: Track PCC includes five geographic surveillance sites to conduct standardized population-based surveillance to estimate and track Post-COVID Conditions (PCC) by age, sex, race/ethnicity, geographic area, severity of initial infection, and risk factors among persons with evidence of SARS-CoV-2 infection (based on the Council of State and Territorial Epidemiologist [CSTE] case definitions for confirmed cases or laboratory-confirmed evidence of infection). Methods: The study will estimate the incidence, prevalence, including temporal trends, and duration and severity of PCC symptoms, among children, adolescents, and adults. PCCs include a broad range of symptoms and conditions that continue or develop after acute SARS-CoV-2 infection or COVID-19 illness. Surveillance includes both passive and active components for diverse populations in Arizona, Indiana, and Utah as well as the Bronx Borough, NY, and part of Philadelphia County, PA. Passive surveillance will utilize electronic health records and health information exchanges within each site catchment area to longitudinally follow persons with COVID-19 to estimate PCC occurring at least 30 days after acute COVID-19 illness. Active surveillance will utilize self-report of PCCs from detailed surveys of persons ages 7 years and older with evidence of SARS-CoV-2 infection in the past 3 months. Respondents will complete follow-up surveys at 6-, 12- and 18-months post-infection. Discussion: These data can help identify which groups are most affected by PCC, and what health differences among demographic groups exist, as well as indicate potential barriers to care. These additional levels of granularity can inform public health action and help direct needed clinical care for patients.Note
Open access journalEISSN
1471-2458Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1186/s12889-024-19772-4
Scopus Count
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Except where otherwise noted, this item's license is described as © The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License.




