As COVID-19 cases surge and vaccinations lag, health authorities continue to seek additional ways to mitigate the spread of the novel coronavirus.
Now, a modeling study estimates that more than half of transmissions come from pre-, never-, and asymptomatic individuals, indicating that symptom-based screening will have little effect on spread.
The Centers for Disease Control and Prevention study, published online Jan. 7 in JAMA Network Open, concludes that for optimal control, protective measures such as masking and social distancing should be supplemented with strategic testing of potentially exposed but asymptomatic individuals .
“In the absence of effective and widespread use of therapeutics or vaccines that can shorten or eliminate infectivity, successful control of SARS-CoV-2 cannot rely solely on identifying and isolating symptomatic cases; even if implemented effectively, this strategy would be insufficient,” CDC biologist Michael J. Johansson, PhD, and colleagues warn. “Multiple measures that effectively address transmission risk in the absence of symptoms are imperative to control SARS-CoV-2.”
According to the authors, the effectiveness of some current transmission prevention efforts has been disputed and subject to mixed messaging. Therefore, they decided to model the proportion of COVID-19 infections that are likely the result of individuals who show no symptoms and may be unknowingly infecting others.
“Unfortunately, there continues to be some skepticism about the value of community-wide mitigation efforts for preventing transmission such as masking, distancing, and hand hygiene, particularly for people without symptoms,” corresponding author Jay C. Butler, MD, said in an interview. “So we wanted to have a base assumption about how much transmission occurs from asymptomatic people to underscore the importance of mitigation measures and of creating immunity through vaccine delivery.”
Such a yardstick is especially germane in the context of the new, more transmissible variant. “It really puts [things] in a bigger box and underscores, boldfaces, and italicizes the need to change people’s behaviors and the importance of mitigation,” Dr. Butler said. It also highlights the advisability of targeted strategic testing in congregate settings, schools, and universities, which is already underway.
Based on data from several COVID-19 studies from last year, the CDC’s analytical model assumes at baseline that infectiousness peaks at the median point of symptom onset, and that 30% of infected individuals never develop symptoms but are nevertheless 75% as infectious as those who develop overt symptoms.
The investigators then model multiple scenarios of transmission based pre- and never-symptomatic individuals, assuming different incubation and infectious periods, and varying numbers of days from point of infection to symptom onset.
When combined, the models predicts that 59% of all transmission would come from asymptomatic transmission – 35% from presymptomatic individuals and 24% from never-symptomatic individuals.
The findings complement those of an earlier CDC analysis, according to the authors.
The overall proportion of transmission from presymptomatic and never-symptomatic individuals is key to identifying mitigation measures that may be able to control SARS-CoV-2, the authors stated.
For example, they explain, if the infection reproduction number (R) in a particular setting is 2.0, a reduction in transmission of at least 50% is needed in order to reduce R to below 1.0. “Given that in some settings R is likely much greater than 2 and more than half of transmissions may come from individuals who are asymptomatic at the time of transmission, effective control must mitigate transmission risk from people without symptoms,” they wrote.
The authors acknowledge that the study applies a simplistic model to a complex and evolving phenomenon, and that the exact proportions of presymptomatic and never-symptomatic transmission and the incubation periods are not known. They also note symptoms and transmissions appear to vary across different population groups, with older individuals more likely than younger persons to experience symptoms, according to previous studies.