Flu-Like Illness Surveillance Suggests Surge in Undetected US COVID-19 Cases


Existing surveillance networks can track influenza-like illness and lead to improved assessments on impact, prevalence, and severity of COVID-19.


A new study showing a large increase in flu-like infections in the United States during the month of March may unlock key supportive evidence that the number of coronavirus disease 2019 (COVID-19) cases is far larger than official estimates say.1

The study used surveillance networks for influenza-like cases, which had already been in place prior to the pandemic. Data reported a likely scenario, in which upwards of 8.6 million new SARS-CoV-2 infections occurred in March, and more than 80% of the cases have not been identified.1

The investigators also mentioned the study’s relevance in supporting the use of surveillance networks for flu-like infections, as they could be implemented as a tool that more effectively and efficiently estimates the prevalence of COVID-19, a goal that has largely fallen short in the United States. Disjointed testing efforts using real time Polymerase Chain Reaction (RT-PCR) testing have resulted in high false negative rates, the investigators wrote. That, along with COVID-19’s hard to detect or asymptomatic responses, have led to grand underestimates in US COVID-19 confirmed cases numbers.1,2

Low testing availability and challenges in detecting COVID-19 can be mitigated by an outpatient surveillance system for diseases that express symptoms similar to influenza – fever, cough, and sore throat. Existing surveillance networks can track influenza-like illness (ILI), and lead to improved assessments on the impact, prevalence, and severity of COVID-19.2

The study’s ILI data found that, starting in March 2020, states including Washington, New York, Oregon, Pennsylvania, Maryland, Colorado, New Jersey, and Louisiana saw surges in non-flu ILI cases that surpassed seasonal averages. During the last week of March, New York experienced 2 times higher non-influenza ILI cases, higher than any other season ILINet had recorded.2

Investigators estimated the proportion and magnitude of the surge of US ILI attributable to COVID-19 infections in March 2020 through 3 assumptions:

  1. That the patient population reported by sentinel providers is representative of their state each week
  2. That changes in care-seeking behavior in patients with ILI is occurring at a similar rate as that of other patients with non-ILI
  3. That the total number of patients in the United States who require medical care over the course of a year has not substantially changed since 2018

The study additionally incorporated surveys showing the average number of patients seen by providers, the number of providers in each state, and the total number of outpatient visits per year to estimate that, if outpatient clinics stayed open during the pandemic, there would have been about 2.8 million patient encounters with ILI due to COVID-19 between March 8 to March 28, 2020.2

Limitations included that the observed ILI increase may include a second epidemic other than SARS-CoV-2, but investigators qualified the unlikeliness of this phenomenon. The study may also have incorrectly assumed similarity between mild ILI and non-ILI in health care seeking behavior, though assumptions were made based on NYC emergency department surveillance data.2

“We found a clear, anomalous surge in ILI outpatients during the COVID-19 epidemic that correlated with the progression of the epidemic in multiple states across the US,” study investigators reported. “The surge of non-influenza ILI outpatients was much larger than the number of confirmed case in each state, providing evidence of large numbers of probable symptomatic COVID-19 cases that remained undetected.”


  1. Influenza-like Illness surveillance reveals spike in undetected COVID-19 cases in March. News Release. EurekAlert; June 22, 2020. Accessed June 23, 2020. https://www.eurekalert.org/pub_releases/2020-06/aaft-iis062220.php.
  2. Silverman JD, Hupert N, and Washburne AD. Using influena surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States. Science Translational Medicine. 2020; eabc1126. doi: 10.1126/scitranslmed.abc1126.

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