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Sanyi Tang

Researcher at Shaanxi Normal University

Publications -  164
Citations -  5562

Sanyi Tang is an academic researcher from Shaanxi Normal University. The author has contributed to research in topics: Population & Integrated pest management. The author has an hindex of 30, co-authored 139 publications receiving 4064 citations.

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Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions

TL;DR: Sensitivity analyses show that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction adopted by Wuhan on 2019-nCoV infection in Beijing being almost equivalent to increasing quarantine by a 100 thousand baseline value.
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An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)

TL;DR: The previously proposed dynamics transmission model is refit to the data available until January 29th, 2020 and the effective daily reproduction ratio is re-estimated that better quantifies the evolution of the interventions.
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Estimation of the Transmission Risk of 2019-nCov and Its Implication for Public Health Interventions (2019-nCov的传播风险估计及其对公共卫生干预的意义)

TL;DR: Sensitivity analyses reveal that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction of Wuhan on 2019-nCov infection in Beijing being almost equivalent to increasing quarantine by 100-thousand baseline value.
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The effectiveness of quarantine and isolation determine the trend of the COVID-19 epidemics in the final phase of the current outbreak in China

TL;DR: The uncertainty analyses reveal that the epidemics is still uncertain and it is important to continue enhancing the quarantine and isolation strategy and improving the detection rate in mainland China.
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Media impact switching surface during an infectious disease outbreak

TL;DR: It is observed that media impact switched off almost as the epidemic peaked, implies that media coverage significantly delayed the epidemic's peak and decreased the severity of the outbreak, and draws the attention to the important role of informing the public about ‘the rate of change of case numbers' to alter behavioral changes.