2021-08-30

Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China.; Beijing Key Laboratory of Drug Dependence, National Institute on Drug Dependence, Peking University, Beijing 100191, China.; School of Public Health, Peking University, Beijing 100191, China.; Beijing Key Laboratory of Drug Dependence, National Institute on Drug Dependence, Peking University, Beijing 100191, China.; School of Public Health, Peking University, Beijing 100191, China.; Peking-Tsinghua Center for Life Sciences, PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Department of Social Work and Social Administration, University of Hong Kong, Hong Kong, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Beijing Key Laboratory of Drug Dependence, National Institute on Drug Dependence, Peking University, Beijing 100191, China.; Department of Psychiatry, Baylor College of Medicine, Houston, TX 77030, USA.; Beijing Key Laboratory of Drug Dependence, National Institute on Drug Dependence, Peking University, Beijing 100191, China.; School of Public Health, Peking University, Beijing 100191, China.; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing 100191, China.; Beijing Key Laboratory of Drug Dependence, National Institute on Drug Dependence, Peking University, Beijing 100191, China.; Peking-Tsinghua Center for Life Sciences, PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China.; Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing 100191, China.

COVID-19 might have long-term mental health impacts. We aim to investigate the longitudinal changes in mental problems from initial COVID-19 peak to its aftermath among general public in China. Depression, anxiety and insomnia were assessed among a large-sample nationwide cohort of 10,492 adults during the initial COVID-19 peak (28 February 2020 to 11 March 2020) and its aftermath (8 July 2020 to 8 August 2020) using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Insomnia Severity Index. We used generalized estimating equations and linear mixed models to explore factors associated with long-term mental health symptoms during COVID-19. During the five months, mental health symptoms remained consistently elevated (baseline 46.4%; follow-up 45.1%). Long-term depression, anxiety and insomnia were associated with several personal and work-related factors including quarantine (adjusted OR for any mental health symptoms 1.31, 95%CI 1.22-1.41, p < 0.001), increases in

2021-06-10

Law School, Hunan University, Changsha, Hunan Province, P.R. China. 1183772557@qq.com.; Law School, Hunan University, Changsha, Hunan Province, P.R. China.; School of Mathematics and Statistics, Hunan Normal University, Changsha, Hunan Province, P.R. China.

BACKGROUND: With the accelerated aging of the Chinese population, elder abuse has become a serious social problem. As COVID-19 has had a very large impact on economic development and lifestyle in China, it has also affected elder abuse. The purpose of this study is to estimate the prevalence of elder abuse in China during the COVID-19 pandemic, and to identify changes in risk factors for elder abuse in the context of COVID-19. METHODS: We designed a cross-sectional study. In Hunan Province, a face-to-face questionnaire survey was conducted among elderly people over 65 years of age. To ensure the consistency of the measurement standards, we used the elder abuse questionnaire from the "Third Survey on Chinese Women's Social Status." According to related research, we selected 10 victim-related risk factors as independent variables. A logistic regression model was established to analyze the relationship between the independent variables and the four kinds of abuse. RESULTS: We collected

2021-04-07

Institute of Global Studies, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Health, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Studies, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Health, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Studies, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Health, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Studies, University of Geneva, 1205 Geneva, Switzerland.; Institute of Global Health, University of Geneva, 1205 Geneva, Switzerland.

The ongoing pandemic of COVID-19 (Coronavirus Infectious Disease-2019) was first reported at the end of 2019 in Wuhan, China. On 30 January 2020, the WHO declared a Public Health Emergency for the novel coronavirus. On 11 March 2020, the WHO officially declared the COVID-19 outbreak as a pandemic. Due to the differences in population distribution, economic structure, degree of damage and other factors, the affected countries have introduced policies tailored to local conditions as a response to the pandemic, leading to different economic and social impacts. Considering the highly heterogeneous spreading of COVID-19 across regions, this paper takes a specific country (China) as a case study of the spread of the disease and national intervention models for the COVID-19 pandemic. The research period of this article is from 17 December to 26 April 2020, because this time period basically covered the important time nodes of the epidemic in China from animal-to-human transmission, limited

2021-02-24

Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Administrative Office, Haihe University, Tianjin, China.; Division of Liver Disease, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Cardiology, Beijing Hospital of the Ministry of Health, Beijing, China.; Department of Clinical Laboratory, Haihe University, Tianjin, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.; Department of Medicine, University of Hong Kong, Hong Kong, China.; Division of Liver Disease, The Fifth Hospital of Shijiazhuang, Hebei Medical University, Shijiazhuang, China.; Department of Laboratory Medicine, Peking Union Medical College Hospital & Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. yongzhelipumch@126.com.

BACKGROUND: SARS-CoV-2 is a novel coronavirus first recognized in late December 2019 that causes coronavirus disease 19 (COVID-19). Due to the highly contagious nature of SARS-CoV-2, it has developed into a global pandemic in just a few months. Antibody testing is an effective method to supplement the diagnosis of COVID-19. However, multicentre studies are lacking to support the understanding of the seroprevalence and kinetics of SARS-CoV-2 antibodies in COVID-19 epidemic regions. METHOD: A multicentre cross-sectional study of suspected and confirmed patients from 4 epidemic cities in China and a cohort study of consecutive follow-up patients were conducted from 29/01/2020 to 12/03/2020. IgM and IgG antibodies elicited by SARS-CoV-2 were tested by a chemiluminescence assay. Clinical information, including basic demographic data, clinical classification, and time interval from onset to sampling, was collected from each centre. RESULTS: A total of 571 patients were enrolled in the

2021-01-14

The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.; The Chinese Center for Disease Control and Prevention, Beijing, China.

BACKGROUND: Between mid-January and early February, provinces of mainland China outside the epicentre in Hubei province were on high alert for importations and transmission of COVID-19. Many properties of COVID-19 infection and transmission were still not yet established. METHODS: We collated and analysed data on 449 of the earliest COVID-19 cases detected outside Hubei province to make inferences about transmission dynamics and severity of infection. We analysed 64 clusters to make inferences on serial interval and potential role of pre-symptomatic transmission. RESULTS: We estimated an epidemic doubling time of 5.3 days (95% confidence interval (CI): 4.3, 6.7) and a median incubation period of 4.6 days (95% CI: 4.0, 5.2). We estimated a serial interval distribution with mean 5.7 days (95% CI: 4.7, 6.8) and standard deviation 3.5 days, and effective reproductive number was 1.98 (95% CI: 1.68, 2.35). We estimated that 32/80 (40%) of transmission events were likely to have occurred

Department of Sleep Medicine, Mental Health Center of Shantou University, Shantou, China; Sleep Medicine Center, Shantou University Medical College, Shantou, China. Electronic address: s_liyun@stu.edu.cn.; Department of Sleep Medicine, Mental Health Center of Shantou University, Shantou, China; Sleep Medicine Center, Shantou University Medical College, Shantou, China.; Department of Sleep Medicine, Mental Health Center of Shantou University, Shantou, China; Sleep Medicine Center, Shantou University Medical College, Shantou, China.; Department of Sleep Medicine, Mental Health Center of Shantou University, Shantou, China; Sleep Medicine Center, Shantou University Medical College, Shantou, China.; Department of Sleep Medicine, Mental Health Center of Shantou University, Shantou, China; Sleep Medicine Center, Shantou University Medical College, Shantou, China.; Department of Psychiatry, University Hospital of Heraklion, Heraklion, Crete, Greece.; Sleep Medicine Center, Translational Neuroscience Center, West China Hospital, Sichuan University, Chengdu, China.; Laboratory of Human Virology and Oncology, Shantou University Medical College, Shantou, China.

BACKGROUND: Evidence suggests that the outbreak of the coronavirus disease 2019 (COVID-19) and the prevention/control measures for COVID-19 may cause insomnia during the acute phase of COVID-19 pandemic in China. However, it is unclear whether insomnia sustains during the later phases of the pandemic. METHODS: We searched PubMed/Medline, EMBASE, PsycINFO and China National Knowledge Infrastructure from the 27th December 2019 to the 2nd February 2021. As early stage studies on COVID-19 pandemic in China were defined as those conducted prior to April 1st, 2020, while late stage studies were those conducted after April 1st, 2020. RESULTS: A total of 98 studies with 193,889 participants were included. The pooled prevalence of insomnia symptoms among all populations was 39.1% (95% CI 36.2-42.0%); the pooled prevalence of insomnia symptoms during the early and late stages of COVID-19 in China were 37.0% (95% CI 34.1-39.9%) and 41.8% (95% CI 33.6-50.0%), respectively. Importantly, there was

Center of Infectious Disease, West China Hospital, Sichuan University, Chengdu, China.; Center of Infectious Disease, West China Hospital, Sichuan University, Chengdu, China.

For China, the coronavirus disease 2019 (COVID-19) outbreak is a major public health emergency with the fastest spread, the most extensive infection, and the hardest to contain over the past 70 years. The different organizations and institutions in China have taken unprecedented public health responses to interrupt the virus transmission in the past several months. The outbreak in China was under control, but the number of confirmed cases abroad is still rising. Coronavirus disease 2019 has presented a global pandemic. We summarized the response measures adopted by different organizations at different levels (country, province, and hospital) in China, such as setting up an effective integrated system for disease prevention and control, effective deployment of medical staff, adjusting measures according to local conditions, establishing Fangcang hospitals, strengthening scientific research on COVID-19, epidemic prevention knowledge education, mass rapid testing for severe acute

Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Faculty of Health Sciences, University of Macau, Taipa, Macau, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.; The Fifth Affiliated Hospital of Zunyi Medical University, Zhuhai, China. 2496453591@qq.com.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China. nanshan@vip.163.com.; Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China. sunbaoqing@vip.163.com.

In December 2019, the COVID-19 pandemic quickly spread throughout China and beyond, posing enormous global challenges. With prompt, vigorous, and coordinated control measures, mainland China contained the spread of the epidemic within two months and halted the epidemic in three months. Aggressive containment strategy, hierarchical management, rational reallocation of resources, efficient contact tracing, and voluntary cooperation of Chinese citizens contributed to the rapid and efficient control of the epidemic, thus promoting the rapid recovery of the Chinese economy. This review summarizes China's prevention and control strategies and other public health measures, which may provide a reference for the epidemic control in other countries.CI - © 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

2021-12-19

School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.; National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.; School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; School of Public Health, Peking University, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.; China Center for Health Development Studies, Peking University, Beijing, China.; Peking University Health Science Center-Chinese Center for Disease Control and Prevention Joint Center for Vaccine Economics, Beijing, China.; Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing, China.

As Coronavirus Disease-2019 (COVID-19) vaccines became available in December 2020, increasingly more surveys were organized to examine the acceptance of vaccination, while most of them were conducted online. This study aimed to explore the difference between online and traditional on-site surveys in terms of COVID-19 vaccine acceptance. From November to December 2020, an online survey (n = 2013) and an on-site survey (n = 4,316) were conducted simultaneously in China. Multivariate logistic regression was used to identify influencing factors of acceptance, and propensity score matching (PSM) was adopted to balance the outcomes. As a result, 90.0% of the online respondents accepted COVID-19 vaccination, while it was only 82.1% in the on-site survey. After applying PSM, the acceptance rate of the on-site survey was declined to 78.6%. The age structure, residence location, education, and health status were observed as important factors in addressing vaccination acceptance, which needed to

2021-12-07

Department of Neurology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.; Department of Infectious Disease Surveillance, Shanghai International Travel Healthcare Center, Shanghai, China.; Department of Epidemiology, Second Military Medical University, Shanghai, China.; Department of High Altitude Operational Medicine, Army Medical University, Chongqing, China.; Department of Infectious Disease Surveillance, Shanghai International Travel Healthcare Center, Shanghai, China.; Department of Infectious Disease Surveillance, Shanghai International Travel Healthcare Center, Shanghai, China.; Office of Scientific Research and Information Management, Center for Disease Control and Prevention, Pudong New Area, Shanghai, China.; Office of Scientific Research and Information Management, Fudan University Pudong Institute of Preventive Medicine, Pudong New Area, Shanghai, China.; Office of Clinical Research Center, Shanghai Skin Disease Hospital, Shanghai, China.; Office of Scientific Research and Information Management, Center for Disease Control and Prevention, Pudong New Area, Shanghai, China.; Office of Scientific Research and Information Management, Fudan University Pudong Institute of Preventive Medicine, Pudong New Area, Shanghai, China.; Department of Hepatobiliary Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

Background: International travel during the Coronavirus disease 2019 (COVID-19) pandemic carries a certain magnitude of infection risk both to travelers and their destination, which may be difficult to assess in the early stage. The characteristics of common infectious diseases of tourists may provide some clues to identify the high-risk travelers and protect susceptible population. Methods: From among 48,444 travelers screened at Shanghai Port, we analyzed 577 travelers with 590 infectious diseases for age, sex, disease type, and World Health Organization (WHO) regions. We used the Joinpoint Regression Program to identify the average percent changes (APC) in the various trends among these individuals. Results: Hepatitis B, syphilis, and HIV were the most common infectious diseases in travelers entering China, and Hepatitis B, pulmonary tuberculosis, and syphilis in Chinese nationals traveling abroad (overall detection rates, 1.43 and 0.74%, respectively; P < 0.05). Africa (2.96%),