At least 50% of COVID-19 infections come from people who have no symptoms: study

A new study by the University of Chicago found that during the initial wave of the COVID-19 outbreak in New York City, only 1 in 5 to 1 in 7 cases of the virus was symptomatic. The research team found that non-symptomatic cases contribute substantially to transmission in the community, constituting at least 50% of the driving force of SARS-CoV-2 infection. The results were published on February 10 in the Proceedings of the National Academy of Sciences.

When the COVID-19 epidemic hit the United States, the researchers noted that it was very difficult to estimate the proportion of people infected with SARS-CoV-2 who would develop symptoms, partly due to the initial challenges with testing ability.

“Without testability data, it is very difficult to estimate the difference between cases that were not reported due to a lack of tests and cases that were really asymptomatic,” said first author Rahul Subramanian, a Ph.D. epidemiology student at UChicago. “We wanted to separate these two things, and since New York was one of the first cities to report the daily number of tests completed, we were able to use these numbers to estimate how many COVID-19 cases were symptomatic.”

While there are a number of existing models that use epidemiological data to estimate undetected case numbers and transmission rates, this is the first peer-reviewed model to incorporate data on daily testing capacity and changes in testing rates over time. to provide a more accurate picture of what proportion of SARS-CoV-2 infections are symptomatic in a large city in the United States.

“Incorporating this data into the model showed that the proportion of symptomatic individuals for COVID-19 is between 13% and 18%,” said senior author Mercedes Pascual, Ph.D., professor of ecology and evolution at Louis Block at UChicago. “And regardless of the uncertainty in all other parameters, we can say that more than 50% of the transmission that occurs in the community is from people without symptoms – those who are asymptomatic and pre-symptomatic.”

Although this data analysis does not indicate how infectious individuals are asymptomatic, nor does it explain the new variants of the virus currently spreading in the USA, the model provides additional support for the importance of following public health guidelines to reduce the transmission of the virus by community, whether individuals show symptoms.

“Even though asymptomatic people are not transmitting the virus at high rates, they make up about 80% of all infections,” said co-author Qixin He, now an assistant professor at Perdue University. “This proportion is quite surprising. It is crucial that everyone – including individuals who have no symptoms – follow public health guidelines, such as wearing masks and social distance, and that mass testing is easily accessible to everyone.”

The researchers say that these results also demonstrate that public health agencies need to make their test protocols and numbers publicly available to allow this data to be incorporated into existing transmission models.

“Making this information available is as important as reporting the number of cases,” said Pascual. “Otherwise, we have a discrepancy between the number and type of cases reported over time and the underlying transmission dynamics. These data are essential for epidemiological modeling ”.