logo
ResearchBunny Logo
Abstract
This paper proposes a novel stochastic model to predict the COVID-19 outbreak in China, accounting for unique transmission dynamics and intervention measures. The model reveals a significant asymptomatic carrier population, differing infection rates between symptomatic and asymptomatic individuals, and a substantial reduction in transmission rates following control measures. The model predicted epidemic containment by early March in the studied regions.
Publisher
Scientific Reports
Published On
Dec 09, 2020
Authors
Yuan Zhang, Chong You, Zhenhao Cai, Jiarui Sun, Wenjie Hu, Xiao-Hua Zhou
Tags
COVID-19
stochastic model
transmission dynamics
asymptomatic carriers
epidemic containment
intervention measures

Related Publications

Explore these studies to deepen your understanding of the subject.

The government intervention effects on panic buying behavior based on online comment data mining: a case study of COVID-19 in Hubei Province, China
Business

The government intervention effects on panic buying behavior based on online comment data mining: a case study of COVID-19 in Hubei Province, China

T. Chen, Y. Jin, et al.

A new scheme for low-carbon recycling of urban and rural organic waste based on carbon footprint assessment: A case study in China
Environmental Studies and Forestry

A new scheme for low-carbon recycling of urban and rural organic waste based on carbon footprint assessment: A case study in China

K. Zhou, Y. Li, et al.

Unveiling the origins of non-performance-oriented behavior in China's local governments: a game theory perspective on the performance-based promotion system
Political Science

Unveiling the origins of non-performance-oriented behavior in China's local governments: a game theory perspective on the performance-based promotion system

H. Shang, H. Liu, et al.

Online public opinion during the first epidemic wave of COVID-19 in China based on Weibo data
Social Work

Online public opinion during the first epidemic wave of COVID-19 in China based on Weibo data

W. Shi, F. Zeng, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs—just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny