The willingness of Chinese adults to receive the COVID-19 vaccine and its associated factors at the early stage of the vaccination programme: a network analysis.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has been a continuous global threat since the first identification of the disease in December 2019. COVID-19 vaccination is a crucial preventive approach that can halt this pandemic. However, many factors affect the willingness of the public to be vaccinated against COVID-19 at the early stage of the vaccination programme. We used network analysis to investigate the interrelation of vaccination willingness and its associated factors. METHODS: A population-representative sample of 539 Chinese adults completed a battery of online self-assessments, including those on vaccination willingness, health status, attitude towards vaccines, COVID-19-related psychological elements and other variables. Network analysis was performed using the R qgraph package. RESULTS: In total, 445 (82.6%) participants scored high on their willingness to vaccinate. Attitude towards vaccines, the influence of people around an individual and health status were directly significantly related to vaccination willingness. The betweenness of age was the highest and, the emotional states had the strongest centrality. LIMITATIONS: Network analysis is not sufficient to determine the causal relationships of the links between nodes. In addition, there are other latent essential elements that were not evaluated. Finally, the sample size was relatively small. CONCLUSION: Network analysis showed that attitude toward vaccines and emotional states are the most critical factors affecting vaccination willingness, which indicates that we should pay attention to the impact of the dissemination of Internet information on vaccination willingness and public emotional states during a pandemic which is very important for promoting vaccination programs.

Symptomless multi-variable apnea prediction index assesses adverse outcomes in patients with Corona Virus Disease 2019.

PURPOSE: To explore the relationship between symptomless multi-Variable apnea prediction (sMVAP) index and adverse outcomes of patients with Corona Virus Disease 2019 (COVID-19). METHODS: According to the sMVAP quartiles, we divided all patients into four groups. The clinical electronic medical records, nursing records, laboratory findings, and radiological examinations for all patients with laboratory confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection were reviewed. Cox proportional hazard ratio (HR) models were used to determine the risk factors associated with in hospital death. RESULTS: A total of 97 patients were included in this study. The "Quartile 4" group 's ICU transfer rate was significantly higher than the "Quartile 1" group. Coronary heart disease, high d-dimer and sMVAP at admission were associated with increased odds of death. CONCLUSIONS: Using the sMVAP index for obstructive sleep apnea hypopnea syndrome (OSAHS) risk assessment, and then predicting the adverse outcomes of COVID-19 patients, is an effective method. Therefore, the use of sMVAP index for OSAHS screening for inpatients with COVID-19 should be vigorously promoted, and high-risk patients should be effectively managed.