Assessing Associations Between COVID-19 Symptomology and Adverse Outcomes After Piloting Crowdsourced Data Collection: Cross-sectional Survey Study.

Natalie Flaks-Manov Jiawei Bai Cindy Zhang Anand Malpani Stuart C Ray Casey Overby Taylor

Published in: JMIR formative research (2022)

We demonstrated that a crowdsourced approach was effective for collecting data to assess symptomology associated with COVID-19. Such a strategy may facilitate efficient assessments in a dynamic intersection between emerging infectious diseases, and societal and environmental changes.

Keyphrases

infectious diseases
coronavirus disease
sars cov
electronic health record
big data
respiratory syndrome coronavirus
data analysis
emergency department
machine learning
adverse drug