Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae

Emerg Infect Dis. 2023 Feb;29(2):389-392. doi: 10.3201/eid2902.220712. Epub 2022 Dec 23.

Abstract

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases.

Keywords: COVID-19; SARS-CoV-2; United States; coronavirus disease; coronaviruses; electronic health information sequelae; longitudinal analysis; respiratory infections; severe acute respiratory syndrome coronavirus 2; viruses; zoonoses.

MeSH terms

  • COVID-19*
  • Humans
  • Middle East Respiratory Syndrome Coronavirus*
  • SARS-CoV-2