Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19

J Infect. 2020 Nov;81(5):793-796. doi: 10.1016/j.jinf.2020.08.046. Epub 2020 Sep 1.

Abstract

Although direct detection of SARS-CoV2 in symptomatic or asymptomatic individuals is the ideal epidemiological tool for determining the burden of disease, the lack of availability of testing can preclude its wider implementation as a robust surveillance system. We correlated the use of the derivative influenza-negative influenza-like illness (fnILI) z-score from the US Centers for Disease Control and Prevention as a proxy for incident cases and disease-specific deaths. For every unit increase of fnILI z-score, the number of cases increased by 376.5 (95% CI [202.5, 550.5]) and number of deaths increased by 10.2 (95% CI [5.4, 15.0]). FnILI data may serve as an accurate outcome measurement to track the spread of COVID-19 infection and disease, and allow for informed and timely decision-making on public health interventions.

Keywords: CDC; COVID-19; ILI; Influenza.

MeSH terms

  • Betacoronavirus*
  • COVID-19
  • Centers for Disease Control and Prevention, U.S.
  • Coronavirus Infections / epidemiology*
  • Coronavirus Infections / mortality*
  • Coronavirus Infections / virology
  • Databases, Factual
  • Humans
  • Incidence
  • Influenza, Human / epidemiology*
  • Influenza, Human / virology
  • Orthomyxoviridae*
  • Pandemics
  • Pneumonia, Viral / epidemiology*
  • Pneumonia, Viral / mortality*
  • Pneumonia, Viral / virology
  • SARS-CoV-2
  • Seasons
  • United States / epidemiology