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您的检索式：作者名="Jiting Tang"
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| 1 | Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide显示文摘The first phase of the novel coronavirus disease(COVID-19)that emerged at the end of 2019 has been brought under control in the mainland of China in March,while it is still spreading globally.When the pandemic will end is a question of great concern.A logistic model that depicts the growth rules of infected and recovered cases in China’s mainland may shed some light on this question.This model well explained the data by 13 April from 31 countries that have been experiencing serious COVID-2019 outbreaks(R2≥0.95).Based on this model,the semi-saturation period(SSP)of infected cases in those countries ranges from 3 March to 18 June.According to the linear relationship between the growth rules for infected and for recovered cases identified from the Chinese data,we predicted that the SSP of the recovered cases outside China ranges from 22 March to 8 July.More importantly,we found a strong positive correlation between the SSP of infected cases and the timing of a government’s response.Finally,this model was also applied to four regions that went through other coronavirus or Ebola virus epidemics(R2≥0.95).There is a negative correlation between the death rate and the logistic growth rate.These findings provide strong evidence for the effectiveness of rapid epidemic control measures in various countries. | Chuanliang Han Yimeng Liu Jiting Tang Yuyao Zhu Carlo Jaeger Saini Yang | 2020 | International Journal of Disaster Risk Science2020，11，4： | 2 |
| 2 | Fast diagnosis of transient plasma by Langmuir probe显示文摘 | Tang Enling Zhang Qingming Ouyang Jiting | 2007 | Journal of Beijing Institute of Technology (English Edition)2007，16，3： | 1 |
| 3 | Typhoon Risk Perception: A Case Study of Typhoon Lekima in China显示文摘The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies.However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that:(1)Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors,including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts;(2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster;and(3)Descriptions of rainfall intensity by females are closer to the meteorological observation data. | Jiting Tang Saini Yang Yimeng Liu Kezhen Yao Guofu Wang | 2022 | International Journal of Disaster Risk Science2022，13，2： | 1 |
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