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[Estimating the basic reproduction number of COVID-19 in Wuhan, China]
1School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Insights
The basic reproduction number (R(0)) for COVID-19 in Hubei was estimated at 3.49. Control measures reduced this to 2.95, indicating their effectiveness in slowing the virus spread.
Area of Science:
- Epidemiology
- Infectious Disease Modeling
Background:
- COVID-19 cases were increasing in Hubei province.
- Estimates for the basic reproduction number (R(0)) of COVID-19 varied significantly across studies.
Purpose of the Study:
- To estimate the basic reproduction number (R(0)) of COVID-19.
- To assess the effectiveness of control interventions.
Main Methods:
- Daily confirmed COVID-19 cases in Hubei from January 17 to February 8, 2020, were analyzed.
- Four methods were used: exponential growth (EG), maximum likelihood estimation (ML), sequential Bayesian (SB), and time-dependent reproduction numbers (TD).
Main Results:
- The exponential growth (EG) method provided the best fit for the data.
- The estimated R(0) using EG was 3.49 (95% CI: 3.42-3.58).
- Following control measures, the estimated R(0) decreased to 2.95 (95% CI: 2.86-3.03).
Conclusions:
- The exponential growth (EG) method is suitable for estimating R(0) in the early stages of an epidemic.
- Timely and effective control measures are crucial for reducing COVID-19 transmission.
Abstract:
Objective: The number of confirmed and suspected cases of the COVID-19 in Hubei province is still increasing. However, the estimations of the basic reproduction number of COVID-19 varied greatly across studies. The objectives of this study are 1) to estimate the basic reproduction number (R(0)) of COVID-19 reflecting the infectiousness of the virus and 2) to assess the effectiveness of a range of controlling intervention. Methods: The reported number of daily confirmed cases from January 17 to February 8, 2020 in Hubei province were collected and used for model fit. Four methods, the exponential growth (EG), maximum likelihood estimation (ML), sequential Bayesian method (SB) and time dependent reproduction numbers (TD), were applied to estimate the R(0). Results: Among the four methods, the EG method fitted the data best. The estimated R(0) was 3.49 (95%CI: 3.42-3.58) by using EG method. The R(0) was estimated to be 2.95 (95%CI: 2.86-3.03) after taking control measures. Conclusions: In the early stage of the epidemic, it is appropriate to estimate R(0) using the EG method. Meanwhile, timely and effective control measures were warranted to further reduce the spread of COVID-19.
