BackgroundMental health risks associated with the aftermath of the COVID-19 pandemic are often overlooked by the public. The aim of this study was to investigate the effects of the COVID-19 pandemic on depression and anxiety disorders in China.MethodsStudies were analyzed and extracted in accordance with the PRISMA 2020 flowchart. The studies were screened and extracted using electronic databases including PubMed, Web of Science, Embase, Cochrane Library, and ClinicalTrials.gov according to the predefined eligibility criteria. The Cochrane Review Manager software 5.3.1 was used for data analysis and the risk of bias assessment.ResultsAs of 2023, a total of 9,212,751 Chinese have been diagnosed with COVID-19 infection. A total of 913,036 participants in 44 studies were selected following the eligibility criteria, the statistical information of which was collected for meta-analysis. The pooled prevalence of depression and anxiety were 0.31 (95% CI: 0.28, 0.35; I2 = 100.0%, p 

BackgroundMental health risks associated with the aftermath of the COVID-19 pandemic are often overlooked by the public. The aim of this study was to investigate the effects of the COVID-19 pandemic on depression and anxiety disorders in China.MethodsStudies were analyzed and extracted in accordance with the PRISMA 2020 flowchart. The studies were screened and extracted using electronic databases including PubMed, Web of Science, Embase, Cochrane Library, and ClinicalTrials.gov according to the predefined eligibility criteria. The Cochrane Review Manager software 5.3.1 was used for data analysis and the risk of bias assessment.ResultsAs of 2023, a total of 9,212,751 Chinese have been diagnosed with COVID-19 infection. A total of 913,036 participants in 44 studies were selected following the eligibility criteria, the statistical information of which was collected for meta-analysis. The pooled prevalence of depression and anxiety were 0.31 (95% CI: 0.28, 0.35; I2 = 100.0%, p 

This dataset supports a research project in the field of digital medicine, which aims to quantify the impact of disseminating scientific information on social media—as a form of "meta-intervention"—on public adherence to Non-Pharmaceutical Interventions (NPIs) during health crises such as the COVID-19 pandemic. The research encompasses multiple sub-studies and pilot experiments, drawing data from various global and China-specific social media platforms.The data included in this submission has been collected from several sources:From Sina Weibo and Tencent WeChat, 189 online poll datasets were collected, involving a total of 1,391,706 participants. These participants are users of Sina Weibo or Tencent WeChat.From Twitter, 187 tweets published by scientists (verified with a blue checkmark) related to COVID-19 were collected.From Xiaohongshu and Bilibili, textual content from 143 user posts/videos concerning COVID-19, along with associated user comments and specific user responses to a question, were gathered.It is important to note that while the broader research project also utilized a 3TB Reddit corpus hosted on Academic Torrents (academictorrents.com), this specific Reddit dataset is publicly available directly from Academic Torrents and is not included in this particular DataHub submission. The submitted dataset comprises publicly available data, formatted as Excel files (.xlsx), and includes the following:Filename: scientists' discourse (source from screenshot of tweets)Description: This file contains screenshots of tweets published by scientists on Twitter concerning COVID-19 research, its current status, and related topics. It also includes a coded analysis of the textual content from these tweets. Specific details regarding the coding scheme can be found in the readme.txt file.Filename: The links of online polls (Weibo & WeChat)Description: This data file includes information from online polls conducted on Weibo and WeChat after December 7, 2022. These polls, often initiated by verified users (who may or may not be science popularizers), aimed to track the self-reported proportion of participants testing positive for COVID-19 (via PCR or rapid antigen test) or remaining negative, particularly during periods of rapid Omicron infection spread. The file contains links to the original polls, links to the social media accounts that published these polls, and relevant metadata about both the poll-creating accounts and the online polls themselves.Filename: Online posts & comments (From Xiaohongshu & Bilibili)Description: This file contains textual content from COVID-19 related posts and videos published by users on the Xiaohongshu and Bilibili platforms. It also includes user-generated comments reacting to these posts/videos, as well as user responses to a specific question posed within the context of the original content.Key Features of this Dataset:Data Type: Mixed, including textual data, screenshots of social media posts, web links to original sources, and coded metadata.Source Platforms: Twitter (global), Weibo/WeChat (primarily China), Xiaohongshu (China), and Bilibili (video-sharing platform, primarily China).Use Case: This dataset is intended for the analysis of public discourse, the dissemination of scientific information, and user engagement patterns across different cultural contexts and social media platforms, particularly in relation to public health information.

BackgroundThe non-pharmaceutical interventions (NPIs) against COVID-19 may have affected the transmission of hand, foot and mouth disease (HFMD). We aimed to assess the impact of the NPIs on HFMD in the high epidemic area of HFMD, Guangdong Province.MethodsThe data of HFMD cases, etiological information, and meteorological factors in Guangdong from January 1, 2012, to December 31, 2021, were collected. Using a Bayesian structural time series (BSTS) model integrated counterfactual framework, we assessed the effect of NPIs on HFMD by different intervention periods, populations (gender, age, occupation), and cities. We further explored the correlation between the reduction of HFMD and socioeconomic factors in 21 cities.ResultsA total of 351,217 HFMD cases were reported and 455,327 cases were averted in Guangdong Province during 2020–2021 with a reduction of 84.94% (95%CI: 81.63–87.22%) in 2020 and 29.49% (95%CI: 15.26–39.54%) in 2021. The impact of NPIs on HFMD differed by age and gender. The effects of NPIs were more remarkable for children aged 0–2 years and scattered children. We found that the relative reductions in 21 cities were related to the composition ratio of children and COVID-19 incidence.ConclusionThe reduction of HFMD incidence was significantly associated with COVID-19 NPIs, and school closure was an effective intervention to prevent HFMD outbreaks. Our findings will contribute to the development of HFMD prevention and control measures.

The characteristics of the COVID-19 cases in Guangzhou, China, reported from 21 May through 24 June 2021.

Here we report a critically ill patient who was cured of SARS-CoV-2 infection in Changsha, China. A 66-year-old Chinese woman, with no significant past medical history, developed severe pneumonia-like symptoms and later diagnosed as severe COVID-19 pneumonia. Within 2 months of hospitalization, the patient deteriorated to ARDS including pulmonary edema and SIRS with septic shock. When treatment schemes such as antibiotics plus corticosteroids showed diminished therapeutic value, hUCMSC therapy was compassionately prescribed under the patient's consent of participation. After treatment, there was significant improvement in disease inflammation-related indicators such as IL-4, IL-6, and IL-10. Eventually, it confirmed the therapeutic value that hUCMSCs could dampen the cytokine storm in the critically ill COVID-19 patient and modulated the NK cells. In the continued hUCMSC treatment, gratifying results were achieved in the follow-up of the patient. The data we acquired anticipate a significant therapeutic value of MSC treatment in severe and critically ill patients with COVID-19, while further studies are needed.