Vaccinations are an effective choice to stop disease outbreaks, including COVID-19. There is little research on individuals' COVID-19 vaccination decision-making. We aimed to determine individual preferences for COVID-19 vaccinations in China, and to assess the factors influencing vaccination decision-making to facilitate vaccination coverage. A D-efficient discrete choice experiment was conducted across six Chinese provinces selected by the stratified random sampling method. Vaccine choice sets were constructed using seven attributes: vaccine effectiveness, side-effects, accessibility, number of doses, vaccination sites, duration of vaccine protection, and proportion of acquaintances vaccinated. Conditional logit and latent class models were used to identify preferences. Although all seven attributes were proved to significantly influence respondents’ vaccination decision, vaccine effectiveness, side-effects and proportion of acquaintances vaccinated were the most important. We also found a higher probability of vaccinating when the vaccine was more effective; risks of serious side effects were small; vaccinations were free and voluntary; the fewer the number of doses; the longer the protection duration; and the higher the proportion of acquaintances vaccinated. Higher local vaccine coverage created altruistic herd incentives to vaccinate rather than free-rider problems. The predicted vaccination uptake of the optimal vaccination scenario in our study was 84.77%. Preference heterogeneity was substantial. Individuals who were older, had a lower education level, lower income, higher trust in the vaccine and higher perceived risk of infection, displayed a higher probability to vaccinate. Preference heterogeneity among individuals should lead health authorities to address the diversity of expectations about COVID-19 vaccinations. To maximize COVID-19 vaccine uptake, health authorities should promote vaccine effectiveness; pro-actively communicate the absence or presence of vaccine side effects; and ensure rapid and wide media communication about local vaccine coverage.

Background: In the prevention and control of infectious diseases, previous research on the application of big data technology has mainly focused on the early warning and early monitoring of infectious diseases. Although the application of big data technology for COVID-19 warning and monitoring remain important tasks, prevention of the disease’s rapid spread and reduction of its impact on society are currently the most pressing challenges for the application of big data technology during the COVID-19 pandemic. After the outbreak of COVID-19 in Wuhan, the Chinese government and nongovernmental organizations actively used big data technology to prevent, contain, and control the spread of COVID-19. Objective: The aim of this study is to discuss the application of big data technology to prevent, contain, and control COVID-19 in China; draw lessons; and make recommendations. Methods: We discuss the data collection methods and key data information that existed in China before the outbreak of COVID-19 and how these data contributed to the prevention and control of COVID-19. Next, we discuss China’s new data collection methods and new information assembled after the outbreak of COVID-19. Based on the data and information collected in China, we analyzed the application of big data technology from the perspectives of data sources, data application logic, data application level, and application results. In addition, we analyzed the issues, challenges, and responses encountered by China in the application of big data technology from four perspectives: data access, data use, data sharing, and data protection. Suggestions for improvements are made for data collection, data circulation, data innovation, and data security to help understand China’s response to the epidemic and to provide lessons for other countries’ prevention and control of COVID-19. Results: In the process of the prevention and control of COVID-19 in China, big data technology has played an important role in personal tracking, surveillance and early warning, tracking of the virus’s sources, drug screening, medical treatment, resource allocation, and production recovery. The data used included location and travel data, medical and health data, news media data, government data, online consumption data, data collected by intelligent equipment, and epidemic prevention data. We identified a number of big data problems including low efficiency of data collection, difficulty in guaranteeing data quality, low efficiency of data use, lack of timely data sharing, and data privacy protection issues. To address these problems, we suggest unified data collection standards, innovative use of data, accelerated exchange and circulation of data, and a detailed and rigorous data protection system. Conclusions: China has used big data technology to prevent and control COVID-19 in a timely manner. To prevent and control infectious diseases, countries must collect, clean, and integrate data from a wide range of sources; use big data technology to analyze a wide range of big data; create platforms for data analyses and sharing; and address privacy issues in the collection and use of big data.

Background: To examine the relationship between social support and depressive symptoms of Chinese family caregivers of older people with disabilities, and to evaluate the role of caregiver burden as a potential mediator of that relationship. Methods: A survey questionnaire was completed face-to-face by 567 primary family caregivers of older people with disabilities in four provinces in China. Covariates that may affect depressive symptoms, such as the characteristics of disabled people (socio-economic factors, functional and cognitive capacity) and caregivers (caregiver duration and self-rated health of caregivers) were collected. Social support was measured by the Multidimensional Scale of Perceived Social Support (MSPSS); depressive symptoms were assessed by the shortened 10 item version of Center for Epidemiological Studies Depression scale (CES-D); and the caregiver burden was assessed by the Zarit Burden Interview (ZBI). Results: The prevalence of depressive symptoms among caregivers was 37.7%. Higher levels of social support was negatively associated with lower depressive symptoms. This relationship was partially mediated by the caregiver burden, where higher levels of the caregiver burden were negatively associated with depressive symptoms. Furthermore, caregivers who were women, spent extended time in caregiving and were in poor health, reported significantly higher depressive symptoms. Conclusions: Our results indicated that social support was negatively associated with depressive symptoms in family caregivers and in the caregiver burden. The caregiver burden partially mediated the social support-depressive symptoms association. Interventions for family caregivers should include increasing social support, health monitoring and structured interventions to reduce the caregiver burden and attenuate family caregivers’ depressive symptoms.

China’s recent growth in income has been unequally distributed, resulting in an unusually rapid retreat from relative income equality, which has impacted negatively on health services access. There exists a significant gap between health care utilization in rural and urban areas and inequality in health care access due to differences in socioeconomic status is increasing. We investigate inequality in service utilization among the mid-aged and elderly, with a special attention of health insurance.

To evaluate the quality of life (QoL) and social support among family caregivers of a family member with a mental illness and to identify factors associated with the QoL. This is a cross-sectional study, where participants were recruited and independently interviewed using a questionnaire, consisting of demographic characteristics, the Medical Outcome Survey SF-36 form, and social support rating scales. Multiple stepwise regression analysis was used to analyse the factors related to QoL. 181 family caregivers were recruited in Shandong province, China. On a composite QoL score, family caregivers perceived that their QoL was poor (68.3), especially in the aspects of role-physical (61.3), role-emotional (57.6) and mental health (63.0). We also found family caregivers received low social support, especially in objective support and utilization of social support. Patient's illness state, care time, financial burden and objective support were significantly correlated to caregivers' QoL in the physical component score (PCS). Patient's illness state, patient's marital status, family monthly income, caregiver's knowledge about the illness, caregivers coordinating caring, life and work, subjective support received and utility of support were significantly associated with caregivers' QoL in the mental component score (MCS). Social support had a significant correlation with caregivers' QoL. Caregivers should be encouraged to request assistance from other family members and friends in providing care, especially when caregivers are unemployed or long-time carers. Mental health education campaigns and helping families to maintain and enhance a supportive social network may provide useful means to improve caregivers' QoL.

Gender difference and life-course socioeconomic inequalities in functional disability may exist among older adults. However, the association is less well understood among Chinese older population. The objective is to provide empirical evidences on this issue by exploring the association between gender, childhood and adult socioeconomic inequalities in functional disability. Data from the 2013 wave of the China Health and Retirement Longitudinal Study (CHARLS) was utilized. Functional disability was assessed by the activities of daily living (ADL) and instrumental activities of daily living (IADL). Childhood socioeconomic status (SES) was measured by birthplace, father’s education and occupation. Adult SES was measured in terms of education and household income. Multivariate logistic regressions were conducted to assess the association between gender, childhood and adult SES and functional disability. Based on a sample of 18,448 older adults aged 45 years old and above, our results showed that the prevalence of ADL and IADL disability was higher among women than men, but gender difference disappeared after adult SES and adult health were controlled. Harsh conditions during childhood were associated with functional disability but in multivariate analyses only father’s education was associated with IADL disability (OR for no education = 1.198; 95% CI = 1.062–1.353). Current SES such as higher education and good economic situation are protective factors of functional disability. Childhood and adult SES were both related to functional disability among older adults. Our findings highlight the need for policies and programs aimed at decreasing social inequalities during childhood and early adulthood, which could reduce socioeconomic inequalities in functional disability in later life.