Background Since the coronavirus disease (COVID-19) epidemic in China in December 2019, information and discussions about COVID-19 have spread rapidly on the internet and have quickly become the focus of worldwide attention, especially on social media. Objective This study aims to investigate and analyze the public’s attention to events related to COVID-19 in China at the beginning of the COVID-19 epidemic (December 31, 2019, to February 20, 2020) through the Sina Microblog hot search list. Methods We collected topics related to the COVID-19 epidemic on the Sina Microblog hot search list from December 31, 2019, to February 20, 2020, and described the trend of public attention on COVID-19 epidemic-related topics. ROST Content Mining System version 6.0 was used to analyze the collected text for word segmentation, word frequency, and sentiment analysis. We further described the hot topic keywords and sentiment trends of public attention. We used VOSviewer to implement a visual cluster analysis of hot keywords and build a social network of public opinion content. Results The study has four main findings. First, we analyzed the changing trend of the public’s attention to the COVID-19 epidemic, which can be divided into three stages. Second, the hot topic keywords of public attention at each stage were slightly different. Third, the emotional tendency of the public toward the COVID-19 epidemic-related hot topics changed from negative to neutral, with negative emotions weakening and positive emotions increasing as a whole. Fourth, we divided the COVID-19 topics with the most public concern into five categories: the situation of the new cases of COVID-19 and its impact, frontline reporting of the epidemic and the measures of prevention and control, expert interpretation and discussion on the source of infection, medical services on the frontline of the epidemic, and focus on the worldwide epidemic and the search for suspected cases. Conclusions Our study found that social media (eg, Sina Microblog) can be used to measure public attention toward public health emergencies. During the epidemic of the novel coronavirus, a large amount of information about the COVID-19 epidemic was disseminated on Sina Microblog and received widespread public attention. We have learned about the hotspots of public concern regarding the COVID-19 epidemic. These findings can help the government and health departments better communicate with the public on health and translate public health needs into practice to create targeted measures to prevent and control the spread of COVID-19.

Background During the COVID-19 pandemic, the internet has significantly spread information, providing people with knowledge and advice about health protection regarding COVID-19. While a previous study demonstrated that health and eHealth literacy are related to COVID-19 prevention behaviors, few studies have focused on the relationship between health literacy, eHealth literacy, and COVID-19–related health behaviors. The latter includes not only preventative behaviors but also conventional health behaviors. Objective The objective of this study was to develop and verify a COVID-19–related health behavior questionnaire, explore its status and structure, and examine the associations between these behaviors and participants’ health literacy and eHealth literacy. Methods A snowball sampling method was adopted to recruit participants to complete anonymous cross-sectional questionnaire surveys online that assessed sociodemographic information, self-reported coronavirus knowledge, health literacy, eHealth literacy, and COVID-19–related health behaviors. Results Of 1873 college students who were recruited, 781 (41.7%) had adequate health literacy; the mean eHealth literacy score was 30.16 (SD 6.31). The COVID-19–related health behavior questionnaire presented a two-factor structure—COVID-19–specific precautionary behaviors and conventional health behaviors—with satisfactory fit indices and internal consistency (Cronbach α=.79). The mean score of COVID-19–related health behaviors was 53.77 (SD 8.03), and scores differed significantly (P<.05) with respect to residence, college year, academic major, family economic level, self-reported health status, having a family member or friend infected with coronavirus, and health literacy level. Linear regression analysis showed that health literacy and eHealth literacy were positively associated with COVID-19–specific precautionary behaviors (βhealth literacy=.149, βeHealth literacy=.368; P<.001) and conventional health behaviors (βhealth literacy=.219, βeHealth literacy=.277; P<.001). Conclusions The COVID-19–related health behavior questionnaire was a valid and reliable measure for assessing health behaviors during the pandemic. College students with higher health literacy and eHealth literacy can more actively adopt COVID-19–related health behaviors. Additionally, compared to health literacy, eHealth literacy is more closely related to COVID-19–related health behaviors. Public intervention measures based on health and eHealth literacy are required to promote COVID-19–related health behaviors during the pandemic, which may be helpful to reduce the risk of COVID-19 infection among college students.

Background The potential link between sleep disorders and suicidal behaviour has been the subject of several reviews. We performed this meta-analysis to estimate the overall association between sleep disorders and suicidal behaviour and to identify a more specific relationship in patients with depression. Methods A systematic search strategy was developed across the electronic databases PubMed, EMBASE and the Cochrane Library from inception to January 1, 2019 for studies that reported a relationship between sleep disorders and suicidal behaviour in depressed patients. The odds ratio (OR) and corresponding 95% confidence interval (CI) were used to measure the outcomes. Heterogeneity was evaluated by Cochran’s Q test and the I2 statistic. The Newcastle-Ottawa Scale (NOS) was adopted to evaluate the methodological quality of each of the included studies, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to assess the quality of the evidence. We calculated the overall association between sleep disorders and suicidal behaviour and estimated more specific categories, including insomnia, nightmares, hypersomnia, suicidal ideation, suicide attempt, and completed suicide. Results A total of 18 studies were included in this study. Overall, sleep disorders were closely related to suicidal behaviour in patients with depression (OR = 2.45 95% CI: 1.33 4.52). The relatively increased risks of sleep disorders with suicidal ideation, suicide attempt and completed suicide ranged from 1.24 (95% CI: 1.00 1.53) to 2.41 (95% CI: 1.45 4.02). Nightmares were found to be highly correlated with the risk of suicidal behaviour (OR = 4.47 95% CI: 2.00 9.97), followed by insomnia (OR = 2.29 95% CI: 1.69 3.10). The certainty of the evidence was rated as very low for the overall outcome and the major depression subgroup and was rated as low for the depression subgroup. Conclusions This meta-analysis supports the finding that sleep disorders, particularly nightmares and insomnia, increase the risk of suicidal behaviour in depressed patients. Considering that all included studies were observational, the quality of the evidence is rated as very low. More well-designed studies are needed to confirm our findings and to better explain the mechanisms by which sleep disorders aggravate suicidal behaviour in depressed patients.

Background: An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus (SARS-CoV-2) emerged in December 2019 in Wuhan, China. Epidemiologic evidence suggests that patients with comorbidities and novel coronavirus disease 2019 (COVID-19) infection may have poor survival outcomes. However, the risk of these coexisting medical conditions in severe and non-severe cases has not been systematically reported. Purpose: The present study aimed to estimate the association of chronic comorbidities in severe and non-severe cases. Methods: A literature search was conducted using the databases PubMed, Embase, China National Knowledge Infrastructure (CNKI), and Wanfang Database, Chinese Scientific Journals Full-text Database (CQVIP) from the inception dates to April 1, 2020, to identify cohort studies assessing comorbidity and risk of adverse outcome. Either a fixed- or random-effects model was used to calculate the overall combined risk estimates. Results: A total of 22 studies involving 3286 patients with laboratory-confirmed COVID-19 were included in the analysis. Overall, compared with the patients with non-severe cases, the pooled odds ratios (ORs) of hypertension, diabetes mellitus, and cardiovascular, cerebrovascular, and respiratory diseases in patients with severe cases were 2.79 (95% confidence intervals [95% CI]: 1.66–4.69), 1.64 (95% CI: 2.30–1.08), 1.79 (95% CI: 1.08–2.96), 3.92 (95% CI: 2.45–6.28), and 1.98 (95% CI: 1.26–3.12), respectively. Conclusions: This meta-analysis supports the finding that chronic comorbidities may contribute to severe outcome in patients with COVID-19. According to the findings of the present study, old age and 2 or more comorbidities are significantly impactful to COVID-19 outcomes in hospitalized patients in China.