High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2

Abstract

Severe acute respiratory syndrome coronavirus 2 is the causative agent of the ongoing coronavirus disease pandemic. Initial estimates of the early dynamics of the outbreak in Wuhan, China, suggested a doubling time of the number of infected persons of 6-7 days and a basic reproductive number (R₀) of 2.2-2.7. We collected extensive individual case reports across China and estimated key epidemiologic parameters, including the incubation period (4.2 days). We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2.3-3.3 days. Assuming a serial interval of 6-9 days, we calculated a median R₀ value of 5.7 (95% CI 3.8-8.9). We further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.

Keywords: 2019 novel coronavirus disease; COVID-19; China; SARS-CoV-2; Wuhan; modeling; respiratory infections; severe acute respiratory syndrome coronavirus 2; transmission potential; viruses; zoonoses.

Figure 1

Epidemiologic characteristics of early dynamics of coronavirus disease outbreak in China. Distributions of key epidemiologic parameters: durations from infection to symptom onset (A), from symptom onset to hospitalization (B), from hospitalization to discharge (C), and from hospitalization to death (D). Filled circles and bars on x-axes denote the estimated means and 95% CIs.

Figure 2

Extremely high level of travel from Wuhan, Hubei Province, to other provinces during January 2020, as estimated by using high-resolution and real-time travel data, China. A) A modified snapshot of the Baidu Migration online server interface showing the human migration pattern out of Wuhan (red dot) on January 19, 2020. Thickness of curved white lines denotes the size of the traveler population to each province. The names of most of the provinces are shown in white. B) Estimated daily population sizes of travelers from Wuhan to other provinces.

Figure 3

Estimates of the exponential growth rate and the date of exponential growth initiation of the 2019 novel coronavirus disease outbreak in China based on 2 different approaches. A) Schematic illustrating the export of infected persons from Wuhan. Travelers (dots) are assumed to be random samples from the total population (whole pie). Because of the growth of the infected population (orange pie) and the shrinking size of the total population in Wuhan over time, probability of infected persons traveling to other provinces increases (orange dots). B) The dates of documented first arrivals of infected persons in 26 provinces. C) Best fit of the case count model to daily counts of new cases (including only imported cases) in provinces other than Hubei. Error bars indicate SDs.

Figure 4

Marginalized likelihoods of growth rate (r) for 2 inference approaches to estimates the exponential growth rate of the coronavirus disease outbreak in China.

Figure 5

Estimation of the basic reproductive number (R₀), derived by integrating uncertainties in parameter values, during the coronavirus disease outbreak in China. A) Changes in R₀ based on different growth rates and serial intervals. Each dot represents a calculation with mean latent period (range 2.2–6 days) and mean infectious periods (range 4–14 days). Only those estimates falling within the range of serial intervals of interests were plotted. B) Histogram summarizing the estimated R₀ of all dots in panel A (i.e., serial interval ranges of 6–9 days). The median R₀ is 5.7 (95% CI 3.8–8.9).

Figure 6

Levels of minimum efforts of intervention strategies needed to control the spread of severe acute respiratory syndrome coronavirus 2, (i.e. reducing the reproductive number to <1), during the coronavirus disease outbreak in China. Strategies considered were quarantine of infected persons and persons who had contact with them (x-axis) and population-level efforts to reduce overall contact rates (y-axis). Percentages denote the percentages of transmissions driven by infected persons that were not detected by surveillance as a result of asymptomatic infection, mild-to-moderate illness or low surveillance intensity.