Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019-2020 Flu Season: A Retrospective Longitudinal Study

Viruses. 2022 Jan 20;14(2):200. doi: 10.3390/v14020200.

Abstract

Background: Previous studies examining the early spread of COVID-19 have used influenza-like illnesses (ILIs) to determine the early spread of COVID-19. We used COVID-19 case definition to identify COVID-like symptoms (CLS) independently of other influenza-like illnesses (ILIs).

Methods: Using data from Emergency Department (ED) visits at VA Medical Centers in CA, TX, and FL, we compared weekly rates of CLS, ILIs, and non-influenza ILIs encounters during five consecutive flu seasons (2015-2020) and estimated the risk of developing each illness during the first 23 weeks of the 2019-2020 season compared to previous seasons.

Results: Patients with CLS were significantly more likely to visit the ED during the first 23 weeks of the 2019-2020 compared to prior seasons, while ED visits for influenza and non-influenza ILIs did not differ substantially. Adjusted CLS risk was significantly lower for all seasons relative to the 2019-2020 season: RR15-16 = 0.72, 0.75, 0.72; RR16-17 = 0.81, 0.77, 0.79; RR17-18 = 0.80, 0.89, 0.83; RR18-19 = 0.82, 0.96, 0.81, in CA, TX, and FL, respectively.

Conclusions: The observed increase in ED visits for CLS indicates the likely spread of COVID-19 in the US earlier than previously reported. VA data could potentially help identify emerging infectious diseases and supplement existing syndromic surveillance systems.

Keywords: COVID-19 symptoms; Veterans; influenza-like illnesses.

MeSH terms

  • COVID-19 / epidemiology
  • COVID-19 / transmission*
  • Databases, Factual / statistics & numerical data*
  • Disease Outbreaks
  • Emergency Service, Hospital / statistics & numerical data
  • Humans
  • Influenza, Human / epidemiology*
  • Longitudinal Studies
  • Retrospective Studies
  • Sentinel Surveillance*
  • United States / epidemiology
  • Veterans / statistics & numerical data*