'Stealth transmission' fuels fast spread of coronavirus outbreak

The researchers report:

• 86 percent of all infections were undocumented prior to the January 23 Wuhan travel shutdown
• Per person, these undocumented infections were half (52 percent) as contagious as documented infections yet were the source of two-thirds of documented infections
• Government control efforts and population awareness have reduced the rate of spread of the virus in China; after travel restrictions and control measures were imposed, it spread less quickly

"The explosion of COVID-19 cases in China was largely driven by individuals with mild, limited, or no symptoms who went undetected," says co-author Jeffrey Shaman, PhD, professor of environmental health sciences at Columbia University Mailman School. "Depending on their contagiousness and numbers, undetected cases can expose a far greater portion of the population to virus than would otherwise occur. We find for COVID-19 in China these undetected infected individuals are numerous and contagious. These stealth transmissions will continue to present a major challenge to the containment of this outbreak going forward."

The researchers used a computer model that draws on observations of reported infection and spread within China in conjunction with mobility data from January 10-23 and January 24-February 8. They caution that major changes to care-seeking or patient documentation practices, as well as rapid developments with regard to travel restrictions and control measures, may make predictions difficult.

"Heightened awareness of the outbreak, increased use of personal protective measures, and travel restriction have helped reduce the overall force of infection; however, it is unclear whether this reduction will be sufficient to fully stem the virus spread," says Shaman. "If the novel coronavirus follows the pattern of 2009 H1N1 pandemic influenza, it will also spread globally and become a fifth endemic coronavirus within the human population."

Additional co-authors include first author Ruiyun Li, Imperial College London, London; Bin Chen, University of California, Davis; Yimeng Song, University of Hong Kong; Tao Zhang, Tsinghua University, Beijing; and Sen Pei and Wan Yang at the Columbia Mailman School.

This research was supported by U.S. National Institutes of Health grants (GM110748, AI145883). Shaman and Columbia University report partial ownership of SK Analytics, a provider of influenza forecasting and analytics services. Shaman also reports receiving consulting fees from Merck.