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359 results on '"Lu, Zhenzhen"'

4. The effect mitigation measures for COVID-19 by a fractional-order SEIHRDP model with individuals migration

Author

Lu, Zhenzhen, Chen, YangQuan, Yu, Yongguang, Ren, Guojian, Xu, Conghui, Ma, Weiyuan, and Meng, Xiangyun

Subjects
Engineering, Electronics, Sensors and Digital Hardware, Humans, COVID-19, SARS-CoV-2, Epidemics, Basic Reproduction Number, Cities, Individual migration, Fractional-order epidemic model, Peak prediction, Sensitivity, Applied Mathematics, Electrical and Electronic Engineering, Manufacturing Engineering, Industrial Engineering & Automation, Electronics, sensors and digital hardware
Abstract

In this paper, the generalized SEIHRDP (susceptible-exposed-infective-hospitalized-recovered-death-insusceptible) fractional-order epidemic model is established with individual migration. Firstly, the global properties of the proposed system are studied. Particularly, the sensitivity of parameters to the basic reproduction number are analyzed both theoretically and numerically. Secondly, according to the real data in India and Brazil, it can all be concluded that the bilinear incidence rate has a better description of COVID-19 transmission. Meanwhile, multi-peak situation is considered in China, and it is shown that the proposed system can better predict the next peak. Finally, taking individual migration between Los Angeles and New York as an example, the spread of COVID-19 between cities can be effectively controlled by limiting individual movement, enhancing nucleic acid testing and reducing individual contact.

Published
2023

6. Stability analysis of a nonlocal SIHRDP epidemic model with memory effects

Author

Lu, Zhenzhen, Yu, Yongguang, Chen, YangQuan, Ren, Guojian, Xu, Conghui, and Wang, Shuhui

Subjects
Engineering, Maritime Engineering, Mathematical Sciences, Prevention, Immunization, Vaccine Related, 3.4 Vaccines, Prevention of disease and conditions, and promotion of well-being, Good Health and Well Being, COVID-19, Fractional-order integral, Nonlocal epidemic system, Adaptive impulsive vaccination, Acoustics, Mathematical sciences
Abstract

The prediction and control of COVID-19 is critical for ending this pandemic. In this paper, a nonlocal SIHRDP (S-susceptible class, I-infective class (infected but not hospitalized), H-hospitalized class, R-recovered class, D-death class and P-isolated class) epidemic model with long memory is proposed to describe the multi-wave peaks for the spread of COVID-19. Based on the basic reproduction number R0 , which is completely controlled by fractional order, the stability of the proposed system is studied. Furthermore, the numerical simulation is conducted to gauge the performance of the proposed model. The results on Hunan, China, reveal that R0

Published
2022

9. Causal association between snoring and stroke: a Mendelian randomization study in a Chinese population

Author

Chen, Junshi, Chen, Zhengming, Clarke, Robert, Collins, Rory, Guo, Yu, Li, Liming, Lv, Jun, Peto, Richard, Walter, Robin, Avery, Daniel, Bennett, Derrick, Boxall, Ruth, Burgess, Sue, Chan, Ka Hung, Chang, Yumei, Chen, Yiping, Clarke, Johnathan, Du, Huaidong, Mohamed, Ahmed Edris, Fairhurst-Hunter, Zammy, Fry, Hannah, Hill, Mike, Holmes, Michael, Im, Pek Kei, Iona, Andri, Kakkoura, Maria, Kartsonaki, Christiana, Kerosi, Rene, Lin, Kuang, Mazidi, Mohsen, Millwood, Iona, Morris, Sam, Nie, Qunhua, Pozarickij, Alfred, Ryder, Paul, Said, Saredo, Schmidt, Dan, Sherliker, Paul, Stevens, Becky, Turnbull, Iain, Walters, Robin, Wang, Lin, Wright, Neil, Yang, Ling, Yang, Xiaoming, Yao, Pang, Han, Xiao, Hou, Can, Pei, Pei, Liu, Chao, Yu, Canqing, Xia, Qingmei, Pang, Zengchang, Gao, Ruqin, Li, Shanpeng, Duan, Haiping, Wang, Shaojie, Liu, Yongmei, Du, Ranran, Zang, Yajing, Cheng, Liang, Tian, Xiaocao, Zhang, Hua, Zhai, Yaoming, Ning, Feng, Sun, Xiaohui, Li, Feifei, Lv, Silu, Wang, Junzheng, Hou, Wei, Sun, Wei, Yan, Shichun, Cui, Xiaoming, Wang, Chi, Wu, Zhenyuan, Li, Yanjie, Kang, Quan, Luo, Huiming, Ou, Tingting, Zheng, Xiangyang, Guo, Zhendong, Wu, Shukuan, Li, Yilei, Li, Huimei, Wu, Ming, Zhou, Yonglin, Zhou, Jinyi, Tao, Ran, Yang, Jie, Su, Jian, Liu, Fang, Zhang, Jun, Hu, Yihe, Lu, Yan, Ma, Liangcai, Tang, Aiyu, Zhang, Shuo, Jin, Jianrong, Liu, Jingchao, Lin, Mei, Lu, Zhenzhen, Zhou, Lifang, Xie, Changping, Lan, Jian, Zhu, Tingping, Liu, Yun, Wei, Liuping, Zhou, Liyuan, Chen, Ningyu, Qin, Yulu, Wang, Sisi, Wu, Xianping, Zhang, Ningmei, Chen, Xiaofang, Chang, Xiaoyu, Yuan, Mingqiang, Wu, Xia, Jiang, Wei, Liu, Jiaqiu, Sun, Qiang, Chen, Faqing, Ren, Xiaolan, Dong, Caixia, Zhang, Hui, Mao, Enke, Wang, Xiaoping, Wang, Tao, zhang, Xi, Kang, Kai, Feng, Shixian, Tian, Huizi, Fan, Lei, Li, XiaoLin, Sun, Huarong, He, Pan, Zhang, Xukui, Yu, Min, Hu, Ruying, Wang, Hao, Zhang, Xiaoyi, Cao, Yuan, Xie, Kaixu, Chen, Lingli, Shen, Dun, Li, Xiaojun, Jin, Donghui, Yin, Li, Liu, Huilin, Fu, Zhongxi, Xu, Xin, Zhang, Hao, Chen, Jianwei, Peng, Yuan, Zhang, Libo, Qu, Chan, Zhu, Yunqing, Zhuang, Zhenhuang, Sun, Dianjianyi, Millwood, Iona Y., and Walters, Robin G.

Published
2024
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11. A wide landscape of morbidity and mortality risk associated with marital status in 0.5 million Chinese men and women: a prospective cohort study

Author

Chen, Junshi, Chen (PI, Zhengming, Clarke, Robert, Collins, Rory, Guo, Yu, Li (PI, Liming, Lv, Jun, Peto, Richard, Walters, Robin, Avery, Daniel, Bennett, Derrick, Boxall, Ruth, Burgess, Sue, Chan, Ka Hung, Chang, Yumei, Chen, Yiping, Chen, Zhengming, Clarke, Johnathan, Du, Huaidong, Mohamed, Ahmed Edris, Fairhurst-Hunter, Zammy, Fry, Hannah, Hill, Mike, Holmes, Michael, Im, Pek Kei, Iona, Andri, Kakkoura, Maria, Kartsonaki, Christiana, Kerosi, Rene, Lin, Kuang, Mazidi, Mohsen, Millwood, Iona, Morris, Sam, Nie, Qunhua, Pozarickij, Alfred, Ryder, Paul, Said, Saredo, Schmidt, Dan, Sherliker, Paul, Stevens, Becky, Turnbull, Iain, Wang, Lin, Wright, Neil, Yang, Ling, Yang, Xiaoming, Yao, Pang, Han, Xiao, Hou, Can, Pei, Pei, Liu, Chao, Yu, Canqing, Xia, Qingmei, Pang, Zengchang, Gao, Ruqin, Li, Shanpeng, Duan, Haiping, Wang, Shaojie, Liu, Yongmei, Du, Ranran, Zang, Yajing, Cheng, Liang, Tian, Xiaocao, Zhang, Hua, Zhai, Yaoming, Ning, Feng, Sun, Xiaohui, Li, Feifei, Lv, Silu, Wang, Junzheng, Hou, Wei, Sun, Wei, Yan, Shichun, Cui, Xiaoming, Wang, Chi, Wu, Zhenyuan, Li, Yanjie, Kang, Quan, Luo, Huiming, Ou, Tingting, Zheng, Xiangyang, Guo, Zhendong, Wu, Shukuan, Li, Yilei, Li, Huimei, Wu, Ming, Zhou, Yonglin, Zhou, Jinyi, Tao, Ran, Yang, Jie, Su, Jian, Liu, Fang, Zhang, Jun, Hu, Yihe, Lu, Yan, Ma, Liangcai, Tang, Aiyu, Zhang, Shuo, Jin, Jianrong, Liu, Jingchao, Lin, Mei, Lu, Zhenzhen, Zhou, Lifang, Xie, Changping, Lan, Jian, Zhu, Tingping, Liu, Yun, Wei, Liuping, Zhou, Liyuan, Chen, Ningyu, Qin, Yulu, Wang, Sisi, Wu, Xianping, Zhang, Ningmei, Chen, Xiaofang, Chang, Xiaoyu, Yuan, Mingqiang, Wu, Xia, Jiang, Wei, Liu, Jiaqiu, Sun, Qiang, Chen, Faqing, Ren, Xiaolan, Dong, Caixia, Zhang, Hui, Mao, Enke, Wang, Xiaoping, Wang, Tao, zhang, Xi, Kang, Kai, Feng, Shixian, Tian, Huizi, Fan, Lei, Li, XiaoLin, Sun, Huarong, He, Pan, Zhang, Xukui, Yu, Min, Hu, Ruying, Wang, Hao, Zhang, Xiaoyi, Cao, Yuan, Xie, Kaixu, Chen, Lingli, Shen, Dun, Li, Xiaojun, Jin, Donghui, Yin, Li, Liu, Huilin, Fu, Zhongxi, Xu, Xin, Zhang, Hao, Chen, Jianwei, Peng, Yuan, Zhang, Libo, Qu, Chan, Xiao, Meng, Li, Aolin, Wang, Yueqing, Pang, Yuanjie, Li, Liming, and Sun, Dianjianyi

Published
2024
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15. Forecast analysis of the epidemics trend of COVID-19 in the United States by a generalized fractional-order SEIR model

Author

Xu, Conghui, Yu, Yongguang, Yang, QuanChen, and Lu, Zhenzhen

Subjects
Quantitative Biology - Populations and Evolution, Mathematics - Dynamical Systems
Abstract

In this paper, a generalized fractional-order SEIR model is proposed, denoted by SEIQRP model, which has a basic guiding significance for the prediction of the possible outbreak of infectious diseases like COVID-19 and other insect diseases in the future. Firstly, some qualitative properties of the model are analyzed. The basic reproduction number $R_{0}$ is derived. When $R_{0}<1$, the disease-free equilibrium point is unique and locally asymptotically stable. When $R_{0}>1$, the endemic equilibrium point is also unique. Furthermore, some conditions are established to ensure the local asymptotic stability of disease-free and endemic equilibrium points. The trend of COVID-19 spread in the United States is predicted. Considering the influence of the individual behavior and government mitigation measurement, a modified SEIQRP model is proposed, defined as SEIQRPD model. According to the real data of the United States, it is found that our improved model has a better prediction ability for the epidemic trend in the next two weeks. Hence, the epidemic trend of the United States in the next two weeks is investigated, and the peak of isolated cases are predicted. The modified SEIQRP model successfully capture the development process of COVID-19, which provides an important reference for understanding the trend of the outbreak.

Published
2020

16. A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects

Author

Lu, Zhenzhen, Yu, Yongguang, Chen, YangQuan, Ren, Guojian, Xu, Conghui, Wang, Shuhui, and Yin, Zhe

Subjects
Physics - Physics and Society, Mathematics - Dynamical Systems, Quantitative Biology - Populations and Evolution
Abstract

In this paper, a mathematical model is proposed to analyze the dynamic behavior of COVID-19. Based on inter-city networked coupling effects, a fractional-order SEIHDR system with the real-data from 23 January to 18 March, 2020 of COVID-19 is discussed. Meanwhile, hospitalized individuals and the mortality rates of three types of individuals (exposed, infected and hospitalized) are firstly taken into account in the proposed model. And infectivity of individuals during incubation is also considered in this paper. By applying least squares method and predictor-correctors scheme, the numerical solutions of the proposed system in the absence of the inter-city network and with the inter-city network are stimulated by using the real-data from 23 January to $18-m$ March, 2020 where $m$ is equal to the number of prediction days. Compared with integer-order system ($\alpha=0$), the fractional-order model without network is validated to have a better fitting of the data on Beijing, Shanghai, Wuhan, Huanggang and other cities. In contrast to the case without network, the results indicate that the inter-city network system may be not a significant case to virus spreading for China because of the lock down and quarantine measures, however, it may have an impact on cities that have not adopted city closure. Meanwhile, the proposed model better fits the data from 24 February to 31, March in Italy, and the peak number of confirmed people is also predicted by this fraction-order model. Furthermore, the existence and uniqueness of a bounded solution under the initial condition are considered in the proposed system. Afterwards, the basic reproduction number $R_0$ is analyzed and it is found to hold a threshold: the disease-free equilibrium point is locally asymptotically stable when $R_0\le 1$, which provides a theoretical basis for whether COVID-19 will become a pandemic in the future., Comment: 11 pages, 10 figures, ND Special Issue paper submitted

Published
2020

18. Long-Term Exposure to Fine Particulate Matter and Incidence of Esophageal Cancer: A Prospective Study of 0.5 Million Chinese Adults

Author

Chen, Junshi, Chen, Zhengming, Clarke, Robert, Collins, Rory, Guo, Yu, Li, Liming, Peto, Richard, Walters, Robin, Avery, Daniel, Bennett, Derrick, Boxall, Ruth, Burgess, Sue, Chan, Ka Hung, Chang, Yumei, Chen, Yiping, Clarke, Johnathan, Du, Huaidong, Mohamed, Ahmed Edris, Fairhurst-Hunter, Zammy, Fry, Hannah, Gilbert, Simon, Hacker, Alex, Hill, Mike, Holmes, Michael, Im, Pek Kei, Iona, Andri, Kakkoura, Maria, Kartsonaki, Christiana, Kerosi, Rene, Lin, Kuang, Mazidi, Mohsen, Millwood, Iona, Morris, Sam, Nie, Qunhua, Pozarickij, Alfred, Ryder, Paul, Said, Saredo, Sansome, Sam, Schmidt, Dan, Sherliker, Paul, Sohoni, Rajani, Stevens, Becky, Turnbull, Iain, Wang, Lin, Wright, Neil, Yang, Ling, Yang, Xiaoming, Yao, Pang, Han, Xiao, Hou, Can, Lv, Jun, Pei, Pei, Liu, Chao, Yu, Canqing, Xia, Qingmei, Pang, Zengchang, Gao, Ruqin, Li, Shanpeng, Duan, Haiping, Wang, Shaojie, Liu, Yongmei, Du, Ranran, Zang, Yajing, Cheng, Liang, Tian, Xiaocao, Zhang, Hua, Zhai, Yaoming, Ning, Feng, Sun, Xiaohui, Li, Feifei, Lv, Silu, Wang, Junzheng, Hou, Wei, Sun, Wei, Yan, Shichun, Cui, Xiaoming, Wang, Chi, Wu, Zhenyuan, Li, Yanjie, Kang, Quan, Luo, Huiming, Ou, Tingting, Zheng, Xiangyang, Guo, Zhendong, Wu, Shukuan, Li, Yilei, Li, Huimei, Wu, Ming, Zhou, Yonglin, Zhou, Jinyi, Tao, Ran, Yang, Jie, Su, Jian, Liu, Fang, Zhang, Jun, Hu, Yihe, Lu, Yan, Ma, Liangcai, Tang, Aiyu, Zhang, Shuo, Jin, Jianrong, Liu, Jingchao, Lin, Mei, Lu, Zhenzhen, Zhou, Lifang, Xie, Changping, Lan, Jian, Zhu, Tingping, Liu, Yun, Wei, Liuping, Zhou, Liyuan, Chen, Ningyu, Qin, Yulu, Wang, Sisi, Wu, Xianping, Zhang, Ningmei, Chen, Xiaofang, Chang, Xiaoyu, Yuan, Mingqiang, Wu, Xia, Jiang, Wei, Liu, Jiaqiu, Sun, Qiang, Chen, Faqing, Ren, Xiaolan, Dong, Caixia, Zhang, Hui, Mao, Enke, Wang, Xiaoping, Wang, Tao, Zhang, Xi, Kang, Kai, Feng, Shixian, Tian, Huizi, Fan, Lei, Li, XiaoLin, Sun, Huarong, He, Pan, Zhang, Xukui, Yu, Min, Hu, Ruying, Wang, Hao, Zhang, Xiaoyi, Cao, Yuan, Xie, Kaixu, Chen, Lingli, Shen, Dun, Li, Xiaojun, Jin, Donghui, Yin, Li, Liu, Huilin, Fu, Zhongxi, Xu, Xin, Zhang, Hao, Chen, Jianwei, Peng, Yuan, Zhang, Libo, Qu, Chan, Sun, Dong, Liu, Cong, Zhu, Yunqing, Sun, Dianjianyi, Pang, Yuanjie, Meng, Xia, Liu, Yang, and Kan, Haidong

Published
2023
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21. Forecast analysis of the epidemics trend of COVID-19 in the USA by a generalized fractional-order SEIR model.

Author

Xu, Conghui, Yu, Yongguang, Chen, YangQuan, and Lu, Zhenzhen

Subjects
COVID-19, Epidemic, Fractional order, Generalized SEIR model, Peak prediction, q-bio.PE, math.DS, Acoustics, Mathematical Sciences, Engineering
Abstract

In this paper, a generalized fractional-order SEIR model is proposed, denoted by SEIQRP model, which divided the population into susceptible, exposed, infectious, quarantined, recovered and insusceptible individuals and has a basic guiding significance for the prediction of the possible outbreak of infectious diseases like the coronavirus disease in 2019 (COVID-19) and other insect diseases in the future. Firstly, some qualitative properties of the model are analyzed. The basic reproduction number R0 is derived. When R01 , the endemic equilibrium point is also unique. Furthermore, some conditions are established to ensure the local asymptotic stability of disease-free and endemic equilibrium points. The trend of COVID-19 spread in the USA is predicted. Considering the influence of the individual behavior and government mitigation measurement, a modified SEIQRP model is proposed, defined as SEIQRPD model, which is divided the population into susceptible, exposed, infectious, quarantined, recovered, insusceptible and dead individuals. According to the real data of the USA, it is found that our improved model has a better prediction ability for the epidemic trend in the next two weeks. Hence, the epidemic trend of the USA in the next two weeks is investigated, and the peak of isolated cases is predicted. The modified SEIQRP model successfully capture the development process of COVID-19, which provides an important reference for understanding the trend of the outbreak.

Published
2020

24. Tracing the transmission dynamics of HIV-1 CRF55_01B.

Author

Zai, Junjie, Liu, Haizhou, Lu, Zhenzhen, Chaillon, Antoine, Smith, Davey, Li, Yi, and Li, Xingguang

Subjects
Humans, HIV-1, HIV Infections, Homosexuality, Male, Phylogeny, Genome, Viral, China, Female, Male, pol Gene Products, Human Immunodeficiency Virus, Genetic Linkage, HIV/AIDS, Genetics, Substance Abuse, Behavioral and Social Science, Infectious Diseases, Sexual and Gender Minorities (SGM/LGBT*), Mental Health, Clinical Research, Prevention, Infection
Abstract

To investigate the genetic diversity, spatiotemporal dynamics, and transmission networks of HIV-1 CRF55_01B epidemic in China. A total of 209 partial pol gene sequences of HIV-1 CRF55_01B were sampled during 2007-2015 from 7 provinces of China. Phylogenetic analyses and trait diffusion process of these sequences were performed using Bayesian methods. Distance-based molecular network analyses were performed to infer putative relationships. Characteristics of genetically linked individuals were analyzed. Our study identified that HIV-1 CRF55_01B likely originated among men who have sex with men (MSM) in Guangdong province in January 2003 (April 2000-April 2005), and that Guangdong province and MSM are major hubs for the spread of the HIV-1 CRF55_01B epidemic in China. A Bayesian Skygrid plot revealed that the effective population size of HIV-1 CRF55_01B experienced increased phase followed by a plateau. All sequences from persons of unknown risk clustered within groups who reported MSM risk. This could be because Chinese MSM may not report such risk due to HIV/AIDS-related stigmatization and discrimination. This study inferred the transmission dynamics of the HIV-1 CRF55_01B epidemic in China at high resolution. The methods developed in this study may be critical for designing effective HIV prevention strategies in China and beyond.

Published
2020

27. Causal association between snoring and stroke: a Mendelian randomization study in a Chinese population

Author

Zhu, Yunqing, primary, Zhuang, Zhenhuang, additional, Lv, Jun, additional, Sun, Dianjianyi, additional, Pei, Pei, additional, Yang, Ling, additional, Millwood, Iona Y., additional, Walters, Robin G., additional, Chen, Yiping, additional, Du, Huaidong, additional, Wu, Xianping, additional, Schmidt, Dan, additional, Avery, Daniel, additional, Chen, Junshi, additional, Chen, Zhengming, additional, Li, Liming, additional, Yu, Canqing, additional, Clarke, Robert, additional, Collins, Rory, additional, Guo, Yu, additional, Peto, Richard, additional, Walter, Robin, additional, Bennett, Derrick, additional, Boxall, Ruth, additional, Burgess, Sue, additional, Chan, Ka Hung, additional, Chang, Yumei, additional, Clarke, Johnathan, additional, Mohamed, Ahmed Edris, additional, Fairhurst-Hunter, Zammy, additional, Fry, Hannah, additional, Hill, Mike, additional, Holmes, Michael, additional, Im, Pek Kei, additional, Iona, Andri, additional, Kakkoura, Maria, additional, Kartsonaki, Christiana, additional, Kerosi, Rene, additional, Lin, Kuang, additional, Mazidi, Mohsen, additional, Millwood, Iona, additional, Morris, Sam, additional, Nie, Qunhua, additional, Pozarickij, Alfred, additional, Ryder, Paul, additional, Said, Saredo, additional, Sherliker, Paul, additional, Stevens, Becky, additional, Turnbull, Iain, additional, Walters, Robin, additional, Wang, Lin, additional, Wright, Neil, additional, Yang, Xiaoming, additional, Yao, Pang, additional, Han, Xiao, additional, Hou, Can, additional, Liu, Chao, additional, Xia, Qingmei, additional, Pang, Zengchang, additional, Gao, Ruqin, additional, Li, Shanpeng, additional, Duan, Haiping, additional, Wang, Shaojie, additional, Liu, Yongmei, additional, Du, Ranran, additional, Zang, Yajing, additional, Cheng, Liang, additional, Tian, Xiaocao, additional, Zhang, Hua, additional, Zhai, Yaoming, additional, Ning, Feng, additional, Sun, Xiaohui, additional, Li, Feifei, additional, Lv, Silu, additional, Wang, Junzheng, additional, Hou, Wei, additional, Sun, Wei, additional, Yan, Shichun, additional, Cui, Xiaoming, additional, Wang, Chi, additional, Wu, Zhenyuan, additional, Li, Yanjie, additional, Kang, Quan, additional, Luo, Huiming, additional, Ou, Tingting, additional, Zheng, Xiangyang, additional, Guo, Zhendong, additional, Wu, Shukuan, additional, Li, Yilei, additional, Li, Huimei, additional, Wu, Ming, additional, Zhou, Yonglin, additional, Zhou, Jinyi, additional, Tao, Ran, additional, Yang, Jie, additional, Su, Jian, additional, Liu, Fang, additional, Zhang, Jun, additional, Hu, Yihe, additional, Lu, Yan, additional, Ma, Liangcai, additional, Tang, Aiyu, additional, Zhang, Shuo, additional, Jin, Jianrong, additional, Liu, Jingchao, additional, Lin, Mei, additional, Lu, Zhenzhen, additional, Zhou, Lifang, additional, Xie, Changping, additional, Lan, Jian, additional, Zhu, Tingping, additional, Liu, Yun, additional, Wei, Liuping, additional, Zhou, Liyuan, additional, Chen, Ningyu, additional, Qin, Yulu, additional, Wang, Sisi, additional, Zhang, Ningmei, additional, Chen, Xiaofang, additional, Chang, Xiaoyu, additional, Yuan, Mingqiang, additional, Wu, Xia, additional, Jiang, Wei, additional, Liu, Jiaqiu, additional, Sun, Qiang, additional, Chen, Faqing, additional, Ren, Xiaolan, additional, Dong, Caixia, additional, Zhang, Hui, additional, Mao, Enke, additional, Wang, Xiaoping, additional, Wang, Tao, additional, zhang, Xi, additional, Kang, Kai, additional, Feng, Shixian, additional, Tian, Huizi, additional, Fan, Lei, additional, Li, XiaoLin, additional, Sun, Huarong, additional, He, Pan, additional, Zhang, Xukui, additional, Yu, Min, additional, Hu, Ruying, additional, Wang, Hao, additional, Zhang, Xiaoyi, additional, Cao, Yuan, additional, Xie, Kaixu, additional, Chen, Lingli, additional, Shen, Dun, additional, Li, Xiaojun, additional, Jin, Donghui, additional, Yin, Li, additional, Liu, Huilin, additional, Fu, Zhongxi, additional, Xu, Xin, additional, Zhang, Hao, additional, Chen, Jianwei, additional, Peng, Yuan, additional, Zhang, Libo, additional, and Qu, Chan, additional

Published
2024
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30. Reduced clinical severity during 2022 Shanghai Spring epidemic of SARS-CoV-2 omicron BA.2 variant infection—an integrated account of virus pathogenicity and vaccination effectiveness

Author

Wu, Xingyue, primary, Chen, Yao, additional, Cao, Kangli, additional, Shen, Yao, additional, Wu, Xueling, additional, Yang, Yilin, additional, Kuang, Zhongshu, additional, Li, Qingrun, additional, Lu, Zhenzhen, additional, Jia, Yichen, additional, Shao, Mian, additional, Gu, Guorong, additional, Wang, Xiangwei, additional, Yao, Ye, additional, Wang, Ying, additional, Chen, Shaodie, additional, Yu, Zhigao, additional, Wei, Wei, additional, Ding, Longfei, additional, Lan, Lulu, additional, Gu, Tianwen, additional, Long, Xiangyu, additional, Sun, Jian, additional, Xing, Lingyu, additional, Shen, Jiayuan, additional, Han, Yi, additional, Luo, Yue, additional, Mu, Sucheng, additional, Lin, Mengna, additional, Zhang, Xiaoyan, additional, Zeng, Rong, additional, Xu, Jianqing, additional, Zhao, Guoping, additional, Huang, Lihong, additional, and Song, Zhenju, additional

Published
2024
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44. The Impact of China's Overseas Economic and Trade Cooperation Zones on Sustainable Trade of Host Countries.

Author

Zhang, Yu, Fu, Zeyu, Xu, Lei, and Lu, Zhenzhen

Abstract

Under the concept of "government-guided, enterprise-led, and market-oriented" operation, the Chinese Overseas Economic and Trade Cooperation Zones (COCZs) have developed a new type of international production pattern, which has become an effective way for developing countries to integrate into the global production network sustainably. Based on the COCZ data collected manually and country-level panel data from 1997 to 2019, this study innovatively analyzes the sustainable trade effect of COCZs with the difference-in-differences method. The research finds that the establishment of COCZs significantly boosts the import and export of the host country in a sustainable manner. Further analysis finds that COCZs can promote the sustainable trade growth of the host country in three aspects: economic, societal, and environmental. This sustainable trade effect is closely related to the institutional improvement and infrastructure construction generated by COCZs. By providing a comprehensive and rigorous analysis of the impact of COCZs on the host country's trade performance, the paper effectively responds to the criticisms on China's "going out" strategy, which is often based on biased assumptions and a lack of empirical evidence. It also provides policy implications for both China and the host countries to enhance the cooperation and mutual benefits of COCZs. [ABSTRACT FROM AUTHOR]

Published
2023
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45. Long-Term Exposure to Fine Particulate Matter and Incidence of Esophageal Cancer: A Prospective Study of 0.5 Million Chinese Adults

Author

Sun, Dong, primary, Liu, Cong, additional, Zhu, Yunqing, additional, Yu, Canqing, additional, Guo, Yu, additional, Sun, Dianjianyi, additional, Pang, Yuanjie, additional, Pei, Pei, additional, Du, Huaidong, additional, Yang, Ling, additional, Chen, Yiping, additional, Meng, Xia, additional, Liu, Yang, additional, Zhang, Jun, additional, Schmidt, Dan, additional, Avery, Daniel, additional, Chen, Junshi, additional, Chen, Zhengming, additional, Lv, Jun, additional, Kan, Haidong, additional, Li, Liming, additional, Clarke, Robert, additional, Collins, Rory, additional, Peto, Richard, additional, Walters, Robin, additional, Bennett, Derrick, additional, Boxall, Ruth, additional, Burgess, Sue, additional, Chan, Ka Hung, additional, Chang, Yumei, additional, Clarke, Johnathan, additional, Mohamed, Ahmed Edris, additional, Fairhurst-Hunter, Zammy, additional, Fry, Hannah, additional, Gilbert, Simon, additional, Hacker, Alex, additional, Hill, Mike, additional, Holmes, Michael, additional, Im, Pek Kei, additional, Iona, Andri, additional, Kakkoura, Maria, additional, Kartsonaki, Christiana, additional, Kerosi, Rene, additional, Lin, Kuang, additional, Mazidi, Mohsen, additional, Millwood, Iona, additional, Morris, Sam, additional, Nie, Qunhua, additional, Pozarickij, Alfred, additional, Ryder, Paul, additional, Said, Saredo, additional, Sansome, Sam, additional, Sherliker, Paul, additional, Sohoni, Rajani, additional, Stevens, Becky, additional, Turnbull, Iain, additional, Wang, Lin, additional, Wright, Neil, additional, Yang, Xiaoming, additional, Yao, Pang, additional, Han, Xiao, additional, Hou, Can, additional, Liu, Chao, additional, Xia, Qingmei, additional, Pang, Zengchang, additional, Gao, Ruqin, additional, Li, Shanpeng, additional, Duan, Haiping, additional, Wang, Shaojie, additional, Liu, Yongmei, additional, Du, Ranran, additional, Zang, Yajing, additional, Cheng, Liang, additional, Tian, Xiaocao, additional, Zhang, Hua, additional, Zhai, Yaoming, additional, Ning, Feng, additional, Sun, Xiaohui, additional, Li, Feifei, additional, Lv, Silu, additional, Wang, Junzheng, additional, Hou, Wei, additional, Sun, Wei, additional, Yan, Shichun, additional, Cui, Xiaoming, additional, Wang, Chi, additional, Wu, Zhenyuan, additional, Li, Yanjie, additional, Kang, Quan, additional, Luo, Huiming, additional, Ou, Tingting, additional, Zheng, Xiangyang, additional, Guo, Zhendong, additional, Wu, Shukuan, additional, Li, Yilei, additional, Li, Huimei, additional, Wu, Ming, additional, Zhou, Yonglin, additional, Zhou, Jinyi, additional, Tao, Ran, additional, Yang, Jie, additional, Su, Jian, additional, Liu, Fang, additional, Hu, Yihe, additional, Lu, Yan, additional, Ma, Liangcai, additional, Tang, Aiyu, additional, Zhang, Shuo, additional, Jin, Jianrong, additional, Liu, Jingchao, additional, Lin, Mei, additional, Lu, Zhenzhen, additional, Zhou, Lifang, additional, Xie, Changping, additional, Lan, Jian, additional, Zhu, Tingping, additional, Liu, Yun, additional, Wei, Liuping, additional, Zhou, Liyuan, additional, Chen, Ningyu, additional, Qin, Yulu, additional, Wang, Sisi, additional, Wu, Xianping, additional, Zhang, Ningmei, additional, Chen, Xiaofang, additional, Chang, Xiaoyu, additional, Yuan, Mingqiang, additional, Wu, Xia, additional, Jiang, Wei, additional, Liu, Jiaqiu, additional, Sun, Qiang, additional, Chen, Faqing, additional, Ren, Xiaolan, additional, Dong, Caixia, additional, Zhang, Hui, additional, Mao, Enke, additional, Wang, Xiaoping, additional, Wang, Tao, additional, Zhang, Xi, additional, Kang, Kai, additional, Feng, Shixian, additional, Tian, Huizi, additional, Fan, Lei, additional, Li, XiaoLin, additional, Sun, Huarong, additional, He, Pan, additional, Zhang, Xukui, additional, Yu, Min, additional, Hu, Ruying, additional, Wang, Hao, additional, Zhang, Xiaoyi, additional, Cao, Yuan, additional, Xie, Kaixu, additional, Chen, Lingli, additional, Shen, Dun, additional, Li, Xiaojun, additional, Jin, Donghui, additional, Yin, Li, additional, Liu, Huilin, additional, Fu, Zhongxi, additional, Xu, Xin, additional, Zhang, Hao, additional, Chen, Jianwei, additional, Peng, Yuan, additional, Zhang, Libo, additional, and Qu, Chan, additional

Published
2023
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