Many epidemiologists believe that the initial COVID-19 infection rate was undercounted due to testing issues, asymptomatic and alternatively symptomatic individuals, and a failure to identify early cases.
Now, a new study from Penn State estimates that the number of early COVID-19 cases in the U.S. may have been more than 80 times greater and doubled nearly twice as fast as originally believed.
In a paper published today (June 22) in the journal Science Translational Medicine, researchers estimated the detection rate of symptomatic COVID-19 cases using the Centers for Disease Control and Prevention’s influenza-like illnesses (ILI) surveillance data over a three week period in March 2020.
“We analyzed each state’s ILI cases to estimate the number that could not be attributed to influenza and were in excess of seasonal baseline levels,” said Justin Silverman, assistant professor in Penn State’s College of Information Sciences and Technology and Department of Medicine. “When you subtract these out, you’re left with what we’re calling excess ILI—cases that can’t be explained by either influenza or the typical seasonal variation of respiratory pathogens.”
The researchers found that the excess ILI showed a nearly perfect correlation with the spread of COVID-19 around the country.
Said Silverman, “This suggests that ILI data is capturing COVID cases, and there appears to be a much greater undiagnosed population than originally thought.”
Remarkably, the size of the observed surge of excess ILI corresponds to more than 8.7 million new cases during the last three weeks of March, compared to the roughly 100,000 cases that were officially reported during the same time period.
“At first I couldn’t believe our estimates were correct,” said Silverman. “But we realized that deaths across the U.S. had been doubling every three days and that our estimate of the infection rate was consistent with three-day doubling since the first observed case was reported in Washington state on January 15.”
The researchers also used this process to estimate infection rates for each state, noting that states showing higher per capita rates of infection also had higher per capita rates of a surge in excess ILI. Their estimates showed rates much higher than initially reported but closer to those found once states began completing antibody testing.
In New York, for example, the researchers’ model suggested that at least 9% of the state’s entire population was infected by the end of March. After the state conducted antibody testing on 3,000 residents, they found a 13.9% infection rate, or 2.7 million New Yorkers.
Excess ILI appears to have peaked in mid-March as, the researchers suggest, fewer patients with mild symptoms sought care and states implemented interventions which led to lower transmission rates. Nearly half of U.S. states were under stay-at-home orders by March 28.
The findings suggest an alternative way of thinking about the COVID-19 pandemic.
“Our results suggest that the overwhelming effects of COVID-19 may have less to do with the virus’ lethality and more to do with how quickly it was able to spread through communities initially,” Silverman explained.
“A lower fatality rate coupled with a higher prevalence of disease and rapid growth of regional epidemics provides an alternative explanation of the large number of deaths and overcrowding of hospitals we have seen in certain areas of the world.”
What is the proportion of people with SARS-COV-2 who are asymptomatic?
To answer this we searched LitCovid (a subset of Pubmed), medRxiv, Trip, Scholar and Google. We retrieved 21 reports for analysis.
What did we learn (see the table for the analysis)
- That between 5% and 80% of people testing positive for SARS-CoV-2 may be asymptomatic
- That symptom-based screening will miss cases, perhaps a lot of them
- That some asymptomatic cases will become symptomatic over the next week (sometimes known as “pre-symptomatics”)
- That children and young adults can be asymptomatic
We also learnt that there is not a single reliable study to determine the number of asymptotics. It is likely we will only learn the true extent once population based antibody testing is undertaken.
Table of studies assessing asymptomatic cases
|Diamond Princess cruise ship, Yokohama, Japan (n=-634 tested positive). ||18%(95% credible interval 16%-20%).||Most infections occurred before the quarantine start.|
|Vo’Euganeo, 50 km west of Venice, Italian village ||50% to 75%—were asymptomatic||In an open letter to the authorities in the Tuscany region|
|MERS-CoV ||Increased from 0% to 29% over time||As the MERS-CoV progressed over time there was more identification of asymptomatic individuals due to increased surveillance and contacts testing.|
|328 adults in Shanghai ||13 (4%) patients were asymptomatic|
|Japanese nationals evacuated from Wuhan (n=565) ||31% (95% CI: 7.7% to 54%)||Based on temperature screening before disembarkation, interviews on symptoms including fever, cough, and non-specific symptoms|
|23 Residents of a Long-Term Care Nursing Facility King County, Washington||10 (43%) had symptoms, and 13 (57%) were asymptomatic.Seven days after testing, 10 of 13 asymptomatics developed symptoms||Symptom-based screening could fail to identify approximately half of nursing home residents with COVID-19.|
|Airport screening of travellers ||17% undetectable by typical screening procedures||Based on: A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: Lancet. 2020;0(0):S0140-6736(20)30154-9.|
|Hospitalised in Beijing, China (n=262)||13 (5.0%) asymptomatic cases|
|391 cases including 148 family index cases in Zhejiang Province ||54 (14%) asymptomatic||higher family secondary attack rate, the secondary attack rate of spouses is higher than other family members.|
|Chinese perspective ||Over the past few days, asymptomatic patients were found in many Chinese cities.||Whether asymptomatic people can transmit SARS‐CoV‐2 to others is unclear.Another uncertainty is whether those who are asymptomatic can cause large‐scale infections.|
|36 children, Zhejiang, China ||Asymptomatics, 10 (28%)||7 had acute upper respiratory symptoms (19%)|
|Data-based analysis, modelling and forecasting of the COVID-19 outbreak ||The number of asymptomatic and mild cases with subclinical manifestations that probably did not present to hospitals for treatment may be substantial; these cases, which possibly represent the bulk of the COVID-19 infections, remain unrecognized,|
|166 new infections in China ||four-fifths of cases are asymptomatic, China figures indicate||Numbers quoted not verifiable|
|Nanjing, China (n=24) ||5 (21%) developed symptoms (fever, cough, fatigue and etc.) during hospitalization.|
|450 case reports from 93 Chinese cities. ||estimate that people who had not yet developed symptoms transmitted around 10% of the cases they studied.|
|People’s Hospital of Daofu county. Tibetan population (n=83) ||Asymptomatic carriers 22%||median age of asymptomatic carriers was 31 years and 1/3rd were students, aged <20 years.|
|WHO Q&A: Similarities and differences – COVID-19 and influenza ||suggest that 80% of infections are mild or asymptomatic,|
|Iceland ||50% of the people who tested positive had no symptoms.”||See also: First results of the voluntary screening in Iceland|
|CDC ||A significant number of individuals that are infected actually remain asymptomatic. That may be as many as 25%.|
|Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease ||Among children in China, illness severity was lower with 94% having asymptomatic, mild or moderate disease,|
|Northern Italy, 60 volunteer blood donors ||40 (67%) tested positive|
Sir Basil’s “fog” is continuing to cover the topic and prevent us from seeing what lies on the other side of the hill.
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- Day M. Covid-19: identifying and isolating asymptomatic people helped eliminate virus in Italian village. BMJ 2020;368:m1165.
- Al-Tawfiq JA. Asymptomatic coronavirus infection: MERS-CoV and SARS-CoV-2 (COVID-19). Travel Med Infect Dis 2020;:101608.
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More information: Justin D. Silverman et al, Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States, 22 June 2020, Science Translational Medicine. DOI: 10.1126/scitranslmed.abc1126 , stm.sciencemag.org/content/ear … scitranslmed.abc1126