ABSTRACT
Background With the relief of the zero-COVID prevention policy in China, great changes in the COVID-19 pandemic took place. Against this backdrop, we aimed to investigate the impact of this policy shift on the mental health of younger adults in China.Methods A cross-sectional study was conducted using an online questionnaire survey between January 1st and February 28th, 2023. The survey aimed to estimate the prevalence of sleep quality, anxiety, and depression among participants aged 18-45years old. Pearson's correlation analysis was used to explore the relationships between these variables. Logistic regression analyses were used to identify factors associated with anxiety and depression.Results We collected the data from 992 persons in the final analysis. The estimated prevalence of poor sleep quality, anxiety, and depression was 71.4%, 11.1%, and 57.5% respectively. Poor sleep quality was positively correlated with both anxiety and depression. Between the two sleep quality groups, variables that showed significant differences included gender, marital status, education, comorbidity, occupation, COVID-19 healthcare work, and infection status (p < 0.05), but not fertility(p = 0.099).In the logistic regression analyses, divorce(or widow)(OR 4.115, 95%CI:1.361–12.441, p = 0.012),comorbidity(OR 1.879, 95%CI: 1.088–3.245,p = 0.024), and poor sleep quality(OR 13.417, 95%CI:4.189–42.97, p < 0.001) were identified as independent factors for anxiety. Bachelor's degree (OR 0.598, 95% CI: 0.373–0.959, p = 0.033), postgraduate or above degree (OR 0.555, 95%CI: 0.316–0.975, p = 0.041) and poor sleep quality (OR 2.438, 95%CI: 1.814–3.276, p < 0.001) were identified as independent factors for depression.Conclusions Under the new social environment, younger adults showed serious mental health problems, especially poor sleep quality and depression. Divorce (or widow), comorbidity, and poor sleep quality contribute to anxiety. Poor sleep quality was the risk factor for depression, while a bachelor’s or above degree served as a protective factor.
Subject(s)
COVID-19 , Anxiety Disorders , Depressive DisorderABSTRACT
The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) caused the devastating ongoing coronavirus disease-2019 (COVID-19) pandemic which poses a great threat to global public health. The spike (S) polypeptide of SARS-CoV-2 consists of the S1 and S2 subunits and is processed by cellular proteases at the S1/S2 boundary. The inclusion of the 4 amino acids (PRRA) at the S1/S2 boundary forms a furin cleavage site (FCS), 682RRAR{downarrow}S686, distinguishing SARS-CoV-2 from its closest relative, the SARS-CoV. Various deletions surrounding the FCS have been identified in patients. When SARS-CoV-2 propagated in Vero cells, the virus acquired various deletions surrounding the FCS. In the present study, we studied the viral transcriptome in SARS-CoV-2 infected primary human airway epithelia (HAE) cultured at an air-liquid interface (ALI) with an emphasis on the viral genome stability at the S1/S2 boundary using RNA-seq. While we found overall the viral transcriptome is similar to that generated from infected Vero cells, we identified a high percentage of mutated viral genome and transcripts in HAE-ALI. Two highly frequent deletions were found at the S1/S2 boundary of the S gene: one is a deletion of 12 amino acids, 678TNSPRRAR{downarrow}SVAS689, which contains the FCS, another is a deletion of 5 amino acids, 675QTQTN679, which is two amino acids upstream of the FCS. Further studies on the dynamics of the FCS deletions in apically released virions revealed that the selective pressure for the FCS maintains the S gene stability in HAE-ALI but with exceptions, in which the FCS deletions are remained at a high rate. Thus, our study presents evidence for the role of unique properties of human airway epithelia in the dynamics of the FCS region during infection of human airways, which is donor-dependent.
Subject(s)
COVID-19ABSTRACT
Background The World Health Organization characterized the 2019 novel coronavirus disease (COVID-19) as a pandemic on March 11. Many clinical trials on COVID-19 have been registered, and we aim to review the characteristics of the trials and provide guidance for future trials to avoid duplicated effort.Methods All the studies on COVID-19 registered before Mar 3, 2020 on eight registry platforms worldwide were searched and the data of design, participants, interventions, and outcomes were extracted and analyzed. The most promising trials were screened based on study design, rationale, and resource availability.Results 393 studies registered were identified until Mar 3 2020 and 380 (96.7%) studies were from mainland China, while 3 in Japan, 3 in France, 2 in the US, and 3 were international collaborative studies. 363 studies (92.4%) recruited participants from hospitals and 266 studies (67.7%) aimed at therapeutic effect, others were for prevention, diagnosis, prognosis, etc. 202 studies (51.4%) were randomized controlled trials (RCTs). The average sample size was 1061 and ranged from 8 to 150,000 per study. 177 out of 266 therapeutic studies (66.5% ) tested Western medicines including antiviral drugs (17.7%), stem cell and cord blood therapy (10.2%), chloroquine and derivatives (8.3%), 16 (6.0%) on Chinese medicines, and 73 (27.4%) on integrated therapy of Western and Chinese medicines. 14 Chinese medicines had its clear rationale for evaluation of therapeutic effects. 31 studies among 266 therapeutic studies (11.7%) used mortality as primary outcome, while the most designed secondary outcomes were symptoms and signs (47.0%). 106 studies (27.0%) were funded by the government, and 268 (68.2%) demonstrated ethical approval. 45.5% studies (179 out of 266) had not started recruiting till Mar 3. Eight RCTs were evaluated as the most promising trials.Conclusions Majority of the studies focused on assessing therapeutics for COVID-19 but inappropriate outcome setting, delayed recruitment and insufficient numbers of new cases in China implied many studies may fail to complete. Strategies and protocols of the studies with robust and rapid data sharing from international collaboration are warranted for emergency public health events, helping to accelerate priority setting for timely evidence-based decision-making.