Identifying and Interrupting Superspreading Events

Implications for Control of Severe Acute Respiratory Syndrome Coronavirus 2

Thomas R. Frieden; Christopher T. Lee


Emerging Infectious Diseases. 2020;26(6):1059-1066. 

In This Article

Abstract and Introduction


It appears inevitable that severe acute respiratory syndrome coronavirus 2 will continue to spread. Although we still have limited information on the epidemiology of this virus, there have been multiple reports of superspreading events (SSEs), which are associated with both explosive growth early in an outbreak and sustained transmission in later stages. Although SSEs appear to be difficult to predict and therefore difficult to prevent, core public health actions can prevent and reduce the number and impact of SSEs. To prevent and control of SSEs, speed is essential. Prevention and mitigation of SSEs depends, first and foremost, on quickly recognizing and understanding these events, particularly within healthcare settings. Better understanding transmission dynamics associated with SSEs, identifying and mitigating high-risk settings, strict adherence to healthcare infection prevention and control measures, and timely implementation of nonpharmaceutical interventions can help prevent and control severe acute respiratory syndrome coronavirus 2, as well as future infectious disease outbreaks.


Severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) continues to spread.[1] Although we still have limited information on the epidemiology of coronavirus disease (COVID-19), there have been multiple reports of superspreading events (SSEs).[2–4] During recent severe outbreaks of SARS, Middle East respiratory syndrome (MERS), and Ebola virus disease, SSEs were associated with explosive growth early in an outbreak and sustained transmission in later stages.[5–7] Here, we review the factors that contribute to SSEs and implications for control of SARS-CoV-2.

SSEs are not limited to emerging infectious diseases. In the early 20th century, Mary Mallon (Typhoid Mary), an asymptomatic typhoid carrier who worked as a cook, infected ≥50 persons.[8–10] An ingenious and elegant but little-known study of tuberculosis demonstrated that many patients, even those with smear-positive, cavitary tuberculosis, were not highly infectious but that 3 of 77 patients accounted for 73% of the infectious burden.[11] In 1997, Woolhouse et al. observed that 20% of the population contributed to ≥80% of transmission and suggested targeting interventions to the core 20%.[12] SSEs have also caused explosive outbreaks of measles, including among vaccinated persons.[13]

During the 2003 SARS epidemic in Beijing, China, 1 hospitalized index patient was the source of 4 generations of transmission to 76 patients, visitors, and healthcare workers.[14] During the MERS outbreak in South Korea, 166 (89%) of 186 confirmed primary cases did not further transmit the disease, but 5 patients led to 154 secondary cases.[15] The index patient transmitted MERS to 28 other persons, and 3 of these secondary cases infected 84, 23, and 7 persons. During Ebola, SSEs played a key role sustaining the epidemic: 3% of cases were estimated to be responsible for 61% of infections.[6]

SSEs highlight a major limitation of the concept of R0. The basic reproductive number R0, when presented as a mean or median value, does not capture the heterogeneity of transmission among infected persons;[16] 2 pathogens with identical R0 estimates may have markedly different patterns of transmission. Furthermore, the goal of a public health response is to drive the reproductive number to a value <1, something that might not be possible in some situations without better prevention, recognition, and response to SSEs. A meta-analysis estimated that the initial median R0 for COVID-19 is 2.79 (meaning that 1 infected person will on average infect 2.79 others), although current estimates might be biased because of insufficient data.[17]

Countermeasures can substantially reduce the reproductive number; on the Diamond Princess cruise ship, an initial estimated R0 of 14.8 (≈4 times higher than the R0 in the epicenter of the outbreak in Wuhan, China) was reduced to an estimated effective reproductive number of 1.78 after on-board isolation and quarantine measures were implemented.[18] In Wuhan, aggressive implementation of nonpharmaceutical interventions (NPIs) in the community, including a cordon sanitaire of the city; suspension of public transport, school, and most work; and cancellation of all public events reduced the reproductive number from 3.86 to 0.32 over a 5-week period (C. Wang et al., unpub. data, However, these interventions might not be sustainable.