Literature DB >> 33601984

Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response.

Jennifer D Runkle1, Maggie M Sugg2, Garrett Graham1, Bryan Hodge3, Terri March4, Jennifer Mullendore5, Fletcher Tove5, Martha Salyers6, Steve Valeika7, Ellis Vaughan5.   

Abstract

INTRODUCTION: Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia.
METHODS: A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution.
RESULTS: Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non-English-speaking groups. PRACTICAL IMPLICATIONS: This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.

Entities:  

Keywords:  COVID-19; digital epidemiology; internet data collection; longitudinal assessment; online data entry; participatory surveillance; symptom checker

Mesh:

Year:  2021        PMID: 33601984      PMCID: PMC8580398          DOI: 10.1177/0033354921990372

Source DB:  PubMed          Journal:  Public Health Rep        ISSN: 0033-3549            Impact factor:   2.792


  33 in total

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Journal:  BMC Public Health       Date:  2014-09-20       Impact factor: 3.295

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