ABSTRACT
China has a lower rate of vaccination among older adults and those who have chronic conditions and functional disabilities. As China has recently ended the zero-COVID policy, understanding the factors behind low vaccination rates among these vulnerable populations can inform immediate policy priorities to save lives for China and offer lessons for the world at large. We used the fifth wave (2021-22) of the China Health and Retirement Longitudinal Study (CHARLS), which represented mainland Chinese 45 and older. Vaccination status was updated in the summer of 2022, reflecting the current situation because very few additional vaccinations were administered afterward. For those who were unvaccinated, self-reported reasons were recorded. Using regression analysis, we investigated the determinants of non-vaccination, including demographics, functional status, and chronic conditions. In addition, two-thirds of the respondents had their vaccination status recorded twice in 2021 and 2022, allowing us to examine changes in vaccination rates in the recent year, zeroing in on the effects of the government's most recent vaccination campaign. Finally, we corroborated the regression results using self-reported reasons for non-vaccination in both years. A total of 12900 participants were included in the analysis. By the summer of 2022, the weighted COVID-19 vaccination rate among older Chinese people (≥60 years old) was 92.3%, with 88.8% having completed the primary series and 72.7% having received boosters. Only 72.0% of the oldest-old (≥80 years old) had completed the primary series, and 47.1% had had boosters. Regression analysis showed that participants who were older, female, unmarried, registered with urban Hukou residence, functionally dependent, and comorbid with chronic conditions were less likely to receive COVID-19 vaccines. A significant increase in vaccination rates among ethnic minorities, older adults, rural residents, and those with chronic conditions and functional dependency was observed in the year after the winter of 2021 when the government started to push for universal vaccination. The self-reported reasons for non-vaccination in 2022 were contraindications (48%), advanced ages/frailty/health conditions (21%), problems in accessing vaccines (18%), concerns about side effects or efficacy (9%), and having never heard of COVID-19 vaccine (6%). Nevertheless, as China has ended the zero-COVID policy, many older people, especially the oldest and those with chronic conditions and disabilities, have not yet been fully vaccinated with the primary series or booster doses, exposing them to the danger of infection. Therefore, health authorities should immediately abandon the previous practice of refusing to vaccinate those with chronic conditions, change people's mistaken perceptions of contraindications and side effects, and improve access to vaccines. Most importantly, China should strengthen public trust in vaccines by making information transparent regarding the vaccine's protection rates and side effects.
Subject(s)
COVID-19ABSTRACT
COVID-19 can be easily transmitted to passengers by inhaling exhaled droplets from the infected person in a bus. Therefore, studying droplet dispersion would provide further insight into the mechanism of virus transmission and predict the risk of infection among passengers on a bus. In this research, a bus equipped with air-conditioning was employed as the research object. To determine the dispersion path, concentration distribution, and escape time of the droplets, computational fluid dynamic (CFD) was applied to simulate the flow field and the droplets' dispersion. The effect of the air supply rate, the location of vents, and the location of infected persons on the dispersion were discussed. Based on the distribution of droplets in the cabin calculated by CFD, a superposition method was used to determine the number of virus particles inhaled by every individual passenger over a four-hour journey. Then, infection risk was assessed by the Wells-Riley equation for all the passengers in the cabin after the whole journey. The results show that the distribution of droplets in the cabin is greatly influenced by the location of the infected person, and the airflow pattern is highly associated with the air supply rate and the location of vents. The infection risk of passengers located at the droplet dispersion path and the distance from the infected persons less than 2.2 m is over 10%. The increase in the air supply rate could speed up the spread of the droplets but at the same time, it could reduce the infection risk.
ABSTRACT
During an airborne infectious disease outbreak, bus passengers can be easily infected by the dispersion of exhaled droplets from an infected passenger. Therefore, measures to control the transport of droplets are necessary, such as a mask or purifier. The current research examined aerosol transport in a bus with air-conditioning. To determine the dispersion path, deposition distribution, and droplet escape time, the computational fluid dynamics were used to predict the flow field and the dispersion of droplets considering the effects of droplet size, location of the infected person, and purifier type. In addition, based on the viability and the number of virus particles in a droplet, the total number of virus particles inhaled by passengers over a 4-h journey was obtained by the superposition method. The Wells–Riley equation was then used to assess the infection risk of the passengers in the bus cabin. The results showed that droplets with a size of 1–20 μm have essentially the same deposition characteristics, and the location of the infected passenger affects the distribution of droplets' transport and the effectiveness of a purifier in removing droplets. A purifier can effectively remove droplets from passengers' coughs and reduce the infection risk of passengers. The performance of the smaller purifiers is not as stable as that of the larger purifiers, and the performance is influenced by the airflow structure where the infected passenger is located.
ABSTRACT
The information cluster that supports the final decision in a decision task is usually presented as a series of information. According to the serial position effect, the decision result is easily affected by the presentation order of the information. In this study, we seek to investigate how the presentation mode of commodities and the informativeness on a shopping website will influence online shopping decisions. To this end, we constructed two experiments via a virtual online shopping environment. The first experiment suggests that the serial position effect can induce human computer interaction decision-making bias, and user decision-making results in separate evaluation mode are more prone to the recency effect, whereas user decision-making results in joint evaluation mode are more prone to the primacy effect. The second experiment confirms the influence of explicit and implicit details of information on the decision bias of the human computer interaction caused by the serial position effect. The results of the research will be better applied to the design and development of shopping websites or further applied to the interactive design of complex information systems to alleviate user decision-making biases and induce users to make more rational decisions.