Characterizing COVID-19 and Influenza Illnesses in the Real World via Person-Generated Health Data.

Autor:	Shapiro A; Evidation Health, Inc., San Mateo, CA 94401, USA., Marinsek N; Evidation Health, Inc., San Mateo, CA 94401, USA., Clay I; Evidation Health, Inc., San Mateo, CA 94401, USA., Bradshaw B; Evidation Health, Inc., San Mateo, CA 94401, USA., Ramirez E; Evidation Health, Inc., San Mateo, CA 94401, USA., Min J; Evidation Health, Inc., San Mateo, CA 94401, USA., Trister A; Bill and Melinda Gates Foundation, Seattle, WA 98109, USA., Wang Y; Department of Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, CA 93106, USA., Althoff T; Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98115, USA., Foschini L; Evidation Health, Inc., San Mateo, CA 94401, USA.
Jazyk:	angličtina
Zdroj:	Patterns (New York, N.Y.) [Patterns (N Y)] 2020 Dec 13; Vol. 2 (1), pp. 100188. Date of Electronic Publication: 2020 Dec 13 (Print Publication: 2021).
DOI:	10.1016/j.patter.2020.100188
Abstrakt:	The fight against COVID-19 is hindered by similarly presenting viral infections that may confound detection and monitoring. We examined person-generated health data (PGHD), consisting of survey and commercial wearable data from individuals' everyday lives, for 230 people who reported a COVID-19 diagnosis between March 30, 2020, and April 27, 2020 (n = 41 with wearable data). Compared with self-reported diagnosed flu cases from the same time frame (n = 426, 85 with wearable data) or pre-pandemic (n = 6,270, 1,265 with wearable data), COVID-19 patients reported a distinct symptom constellation that lasted longer (median of 12 versus 9 and 7 days, respectively) and peaked later after illness onset. Wearable data showed significant changes in daily steps and prevalence of anomalous resting heart rate measurements, of similar magnitudes for both the flu and COVID-19 cohorts. Our findings highlight the need to include flu comparator arms when evaluating PGHD applications aimed to be highly specific for COVID-19. Competing Interests: A.S., N.M., I.C., B.B., E.R., J.M., and L.F. are employees of Evidation, a company that runs research studies using person-generated health data in several therapeutic areas, including COVID-19. All other authors declare no competing interests. (© 2021 The Authors.)
Databáze:	MEDLINE
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