Individual Preferences for COVID-19 Vaccination under the China’s 2021 National Vaccination Policy: A Discrete Choice Experiment Study

NT-proBNP ratio is a potential predictor for COVID-19 outcomes in adult Chinese patients: a retrospective study

Despite the progressive decline in the virulence of the novel coronavirus, there has been no corresponding reduction in its associated hospital mortality. Our aim was to redefine an accurate predictor of mortality risk in COVID-19 patients, enabling effective management and resource allocation. We conducted a retrospective analysis of 2917 adult Chinese patients diagnosed with COVID-19 who were admitted to our hospital during two waves of epidemics, involving the Beta and Omicron variants. Upon admission, NT-proBNP levels were measured, and we collected demographic, clinical, and laboratory data. We introduced a new concept called the NT-proBNP ratio, which measures the NT-proBNP level relative to age-specific maximum normal values. The primary outcome was all-cause in-hospital mortality. Our analysis revealed a higher in-hospital mortality rate in 2022, as shown by the Kaplan-Meier Survival Curve. To assess the predictive value of the NT-proBNP ratio, we employed the time-dependent receiver operating characteristic (ROC) curve. Notably, the NT-proBNP ratio emerged as the strongest predictor of mortality in adult Chinese hospitalized COVID-19 patients (area under the curve, AUC = 0.826; adjusted hazard ratio [HR], 3.959; 95% confidence interval [CI] 3.001-5.221; P < 0.001). This finding consistently held true for both the 2020 and 2022 subgroups. The NT-proBNP ratio demonstrates potential predictive capability compared to several established risk factors, including NT-proBNP, hsCRP, and neutrophil-to-lymphocyte ratio, when it comes to forecasting in-hospital mortality among adult Chinese patients with COVID-19.Trial registration Clinical Trial Registration: www.clinicaltrials.gov NCT05615792.

Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study

BACKGROUND

To contain and curb the spread of COVID-19, the governments of countries around the world have used different strategies (lockdown, mandatory vaccination, immunity passports, voluntary social distancing, etc).

OBJECTIVE

This study aims to examine the reactions produced by the public announcement of a binding political decision presented by the president of the French Republic, Emmanuel Macron, on July 12, 2021, which imposed vaccination on caregivers and an immunity passport on all French people to access restaurants, cinemas, bars, and so forth.

METHODS

To measure these announcement reactions, 901,908 unique tweets posted on Twitter (Twitter Inc) between July 12 and August 11, 2021, were extracted. A neural network was constructed to examine the arguments of the tweets and to identify the types of arguments used by Twitter users.

RESULTS

This study shows that in the debate about mandatory vaccination and immunity passports, mostly "con" arguments (399,803/847,725, 47%; χ26=952.8; P<.001) and "scientific" arguments (317,156/803,583, 39%; χ26=5006.8; P<.001) were used.

CONCLUSIONS

This study shows that during July and August 2021, social events permeating the public sphere and discussions about mandatory vaccination and immunity passports collided on Twitter. Moreover, a political decision based on scientific arguments led citizens to challenge it using pseudoscientific arguments contesting the effectiveness of vaccination and the validity of these political decisions.

Student COVID-19 vaccination preferences in China: A discrete choice experiment

Objective

This study uses a discrete choice experiment (DCE) questionnaire to investigate student vaccination preferences for both intrinsic and extrinsic attributes.

Methods

A two-part DCE questionnaire was distributed to 1,138 students through face-to-face interviews at vaccination centers in Qingdao, China. Conditional logit models were used to understand student preference trade-offs. Mixed logit models (MLM) and sub-group analysis were conducted to understanding student preference heterogeneity.

Results

We found that students preferred vaccines with fewer side effects (β = 0.845; 95% CI, 0.779-0.911), administered through third level health facilities (β = 0.170; 95% CI, 0.110-0.230), and had at least 1 year duration of protection (β = 0.396; 95% CI, 0.332-0.461. Higher perception of COVID-19 risks (β = 0.492; 95% CI, 0.432-0.552) increased the likelihood of student vaccination uptake. Surprisingly, vaccine effectiveness (60%) and percentages of acquaintances vaccinated (60%) reduced vaccination utility, which points to free-rider problems. In addition, we find that student study majors did not contribute to preference heterogeneity, and the main disparities in preferences were attributed to student risk tolerances.

Conclusion

Both intrinsic and extrinsic attributes were influential factors shaping student preferences for COVID-19 vaccines. Our results inform universities and local governments across China on targeting their vaccination programs.

Impact of income on mental health during the COVID-19 pandemic: Based on the 2020 China family panel survey

Since December 2019, the COVID-19 has continued to rage, and epidemic prevention policies have limited contact between individuals, which may has a great influence on the income of individuals, exacerbate anxiety and depression, and cause serious mental health problems. The current study aims to examine the association between income and mental health during the COVID-19 pandemic by using the data of 9,296 observations from the 2020 China Family Panel Studies. Employing ordinary least squares regression and two-stage least squares regression, we find the significant positive effect of income on Chinese mental health during this pandemic. In addition, the number of cigarettes smoked per day has significant negative effects on mental health. Education levelˎmarriage and exercise frequency have significant positive correlation with mental health. Furthermore, the impact of income on individuals of different groups is heterogeneous during this pandemic. The impact of income for well-educated individuals is less strong than their less-educated counterparts. People who exercise regularly respond less strongly to changes in income than those who do not exercise. Finally, individuals’ salary satisfaction and interpersonal relationship are shown to be the potential mechanism for the effect of income on Chinese mental health.

Relationship between Income and Mental Health during the COVID-19 Pandemic in China

Mental health problems represent one most pressing concerns in the world, which produce costly consequences for individuals, families and society as a whole. One of the determinants on mental health during the COVID-19 pandemic is income. To complement relevant research and provide valuable recommendations for governments and societies, this study investigates the nexus between income and mental health in China by employing 8049 observations from the 2020 China Family Panel Studies. Using ordinary least squares regression we find the significant positive relationship between income and mental health, and estimate the effect of income on mental health. Furthermore, this effect is heterogeneous depending on individuals’ education level and registered residence type. Finally, individuals’ economic status and happiness are shown to be the potential mechanism through which the effect of income on mental health operates.