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Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model
1Department of Disease Control, Center for Disease Control and Prevention in Northern Theater Command, Shenyang, China.
Insights
Early intervention in the coronavirus disease (COVID-19) epidemic significantly reduced cases. Implementing control measures just one day later could have increased confirmed patients by 32.1%.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- The initial outbreak of coronavirus disease (COVID-19) in Hubei Province, China, necessitated rapid understanding of its transmission dynamics.
- Estimating key epidemiological parameters and the impact of early travel was crucial for effective control strategies.
Purpose of the Study:
- To develop and validate a stochastic individual-based model simulating the COVID-19 epidemic in China.
- To estimate the basic reproduction number (R0) and the number of infected individuals who left Hubei before the lockdown.
- To assess the impact of delayed or advanced public health interventions on the epidemic's trajectory.
Main Methods:
- A stochastic individual-based model was established to simulate the epidemic's occurrence, development, and control.
- The coordinate descent algorithm was employed to estimate the basic reproduction number (R0) and the number of individuals who left Hubei.
- The model's accuracy was validated by fitting it to officially reported data.
Main Results:
- The median R0 at the epidemic's onset was estimated at 4.97.
- Approximately 2000 infected individuals left Hubei before the traffic lockdown.
- A one-day delay in control measures could have increased national cases by 32.1%; a one-day advance could have decreased cases in other provinces by 7.7%.
Conclusions:
- The developed stochastic model accurately simulates COVID-19 epidemic evolution and fits official data.
- Nationwide interventions effectively curbed human-to-human transmission of SARS-CoV-2.
- Timely implementation of public health measures is critical for controlling infectious disease outbreaks.
Abstract:
We established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82-5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982-2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.
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