From Severe Acute Respiratory Syndrome-Associated Coronavirus to 2019 Novel Coronavirus Outbreak: Similarities in the Early Epidemics and Prediction of Future Trends
In late 2019, a mysterious pneumonia outbreak in Wuhan, China, would soon echo the 2003 severe acute respiratory syndrome (SARS) epidemic—revealing striking parallels in how both viruses emerged, spread, and challenged public health systems. A 2020 study by researchers from Sun Yat-sen University, Shenyang Agricultural University, Boston University, and Columbia University examines these similarities, using firsthand SARS data to predict how the 2019 novel coronavirus (2019-nCoV, later named SARS-CoV-2) might evolve. The findings offer critical lessons for containing the ongoing outbreak—and preventing future ones.
The Viruses: Related but Distinct
Both 2019-nCoV and SARS-CoV belong to beta coronavirus group 2b, a subgroup of viruses known to jump from animals to humans. Genetic analysis shows they share 80% of their genome—but 2019-nCoV is a new, distinct virus. For 2019-nCoV, scientists identified the pathogen just 10 days after the first official report (December 31, 2019)—a major leap from the slower detection of SARS in 2003. By January 22, 2020, researchers confirmed 2019-nCoV originated in wild bats, mirroring SARS’s animal origin.
Yet key gaps remained: No vaccines or antiviral treatments existed for 2019-nCoV, and its transmission patterns were still unknown. Here, the study’s most urgent insight emerged: The early stages of 2019-nCoV closely mirrored SARS—right down to the worst possible timing.
The SARS Lesson: Early Spread and Super-Spreaders
The 2003 SARS outbreak began quietly. On November 16, 2002, a patient in Foshan, China, developed symptoms; five family members soon followed—signaling human-to-human transmission. By January 2003, two “strange pneumonia” cases in Heyuan spread to seven healthcare workers. Later investigations revealed a “super-spreader”: a woman in Guangzhou who infected 91 people (visitors and caregivers), with two deaths. Healthcare workers were especially vulnerable: In one Guangzhou hospital’s respiratory department, 61.7% of staff (29/47) got sick.
SARS also showed generational transmission: One original patient led to at least four “generations” of cases (e.g., Patient A infects B, who infects C, who infects D). These patterns confirmed SARS-CoV’s ability to spread rapidly—and quietly—before authorities could react.
2019-nCoV: A Familiar Pattern with New Challenges
2019-nCoV followed a nearly identical script—with a critical delay. The first Wuhan case was detected on December 12, 2019, but human-to-human transmission wasn’t confirmed until January 19, 2020—after 15 healthcare workers were infected by patients. Like SARS, 2019-nCoV caused family clusters: One family study confirmed person-to-person spread.
The delay was costly. Unrecognized cases could have become super-spreaders—individuals who infect far more people than average—because 2019-nCoV’s transmission was unacknowledged early on. These super-spreaders, the study warns, are “difficult to track” and could accelerate spread across regions.
Spring Festival: The World’s Largest Migration—And a Virus’s Best Friend
Both outbreaks struck during China’s Spring Festival, the country’s most important holiday and the world’s largest annual human migration. In 2003, 1.82 billion people traveled; in 2020, that number jumped to 3.11 billion—1.7 times higher. Wuhan, a city of 10 million, is a major travel hub—connecting to Beijing, Guangzhou, and Shanghai (China’s biggest cities).
The timing was catastrophic. For SARS, the peak (January 3–February 4, 2003) aligned with Spring Festival travel. For 2019-nCoV, the rapid rise in cases (January 10–22, 2020) overlapped with the 2020 Spring Festival migration (January 10–February 18). Winter weather in Wuhan and Guangzhou—cool, dry, and ideal for virus survival—added another layer of risk.
Predicting the Path: What SARS Tells Us About 2019-nCoV
Using daily 2019-nCoV case data and SARS’s epidemic curve, the team built a logistic model—a mathematical tool to predict how outbreaks grow and peak. The results were sobering:
- Daily 2019-nCoV cases were already higher than SARS’s peak (2003), suggesting a larger cumulative total.
- The model predicted 60,000–70,000 total cases, with peaks around March 6–12, 2020 (depending on containment efforts).
While models are not guarantees, they highlight a critical truth: The 2019-nCoV outbreak was far from its peak when the study was published.
Current Measures and the Super-Spreader Challenge
China’s response to 2019-nCoV was faster than SARS: shutting Wuhan’s public transport, limiting travel, and encouraging mask-wearing. These steps likely reduced case numbers—but the study warns of a lingering threat: unidentified super-spreaders. Because 2019-nCoV’s transmission was unrecognized early, some people may have spread the virus across China (or internationally) before symptoms appeared. Tracking these individuals remains one of the outbreak’s biggest challenges.
The Bottom Line: History Repeats—But We Can Learn
The 2019-nCoV outbreak is not a copy of SARS—but the similarities are impossible to ignore. Both viruses emerged from animals, spread rapidly during Spring Festival, infected healthcare workers at high rates, and had super-spreaders. The difference? We now have faster pathogen detection, better data, and hard-earned lessons from SARS.
As the study concludes: “The ongoing 2019-nCoV outbreak seems to be a repetition of the SARS situation. Fortunately, the Chinese government is implementing efficient measures. But super-spreaders—distributed in different places and difficult to track—remain the most important problem.”
The 2003 SARS epidemic taught the world to expect the unexpected. The 2019-nCoV outbreak reminds us: We must act on those lessons—fast.
Chen ZL, Zhang WJ, Lu Y, et al. From severe acute respiratory syndrome-associated coronavirus to 2019 novel coronavirus outbreak: similarities in the early epidemics and prediction of future trends. Chinese Medical Journal 2020;133:1112–1114. doi:10.1097/CM9.0000000000000776
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