Background It is expected that COVID-19 vaccines will become available in China by the end of 2020. Vaccinating children against COVID-19 would contribute to the control of the pandemic and the recovery of the global economy. For children under the age of 18 years, parents are usually the decision makers regarding their children’s vaccination. Objective The goal of this study was to investigate parental acceptability of free COVID-19 vaccination for children under the age of 18 years in China. Methods This is a secondary analysis of a cross-sectional, closed online survey among 2053 factory workers in Shenzhen, China, implemented from September 1 to 7, 2020. Participants of the online survey were full-time employees aged 18 years or over who had resumed work in factories in Shenzhen. Factory workers in Shenzhen are required to receive physical examinations once a year. Eligible workers attending six designated physical examination sites were invited to complete an online survey. This study was based on a subsample of those who had at least one child under the age of 18 years (N=1052). After being briefed that COVID-19 vaccines developed by China are likely to be available by the end of 2020, participants were asked about their likelihood of having their children under the age of 18 years take up free COVID-19 vaccination provided by the government, if it existed. Multivariate logistic regression models were fitted to examine the associations of perceptions related to COVID-19 vaccination based on the theory of planned behavior (TPB) and exposure to information related to COVID-19 through social media with parental acceptability, after controlling for significant background characteristics. Results The prevalence of parents’ acceptability of COVID-19 vaccination for their children was 72.6% (764/1052). After adjusting for significant background characteristics, positive attitudes toward COVID-19 vaccination (adjusted odds ratio [AOR] 1.70, 95% CI 1.50-1.91), the perception that a family member would support them in having their children take up COVID-19 vaccination (ie, perceived subjective norm) (AOR 4.18, 95% CI 3.21-5.43), and perceived behavioral control to have the children take up COVID-19 vaccination (AOR 1.84, 95% CI 1.49-2.26) were associated with higher parental acceptability of COVID-19 vaccination. Regarding social media influence, higher exposure to positive information related to COVID-19 vaccination was associated with higher parental acceptability of COVID-19 vaccination (AOR 1.35, 95% CI 1.17-1.56). Higher exposure to negative information related to COVID-19 vaccination was negatively associated with the dependent variable (AOR 0.85, 95% CI 0.74-0.99). Conclusions Parents’ acceptability of COVID-19 vaccination for their children under 18 years of age was high in China. The TPB is a useful framework to guide the development of future campaigns promoting COVID-19 vaccination targeting parents. Transparency in communicating about the vaccine development process and vaccine safety testing is important. Public health authorities should also address misinformation in a timely manner.

Background COVID-19 vaccines will become available in China soon. Understanding communities’ responses to the forthcoming COVID-19 vaccines is important. We applied the theory of planned behavior as the theoretical framework. Objective This study investigates the prevalence of and factors associated with behavioral intention to receive self-financed or free COVID-19 vaccinations among Chinese factory workers who resumed work during the pandemic. We examined the effects of factors including sociodemographics, perceptions related to COVID-19 vaccination, exposure to information about COVID-19 vaccination through social media, and COVID-19 preventive measures implemented by individuals and factories. Methods Participants were full-time employees 18 years or older who worked in factories in Shenzhen. Factory workers in Shenzhen are required to receive a physical examination annually. Eligible workers attending six physical examination sites were invited to complete a survey on September 1-7, 2020. Out of 2653 eligible factory workers, 2053 (77.4%) completed the online survey. Multivariate two-level logistic regression models and ordinal logistic regression models were fitted. Results The prevalence of behavioral intention to receive a COVID-19 vaccination was 66.6% (n=1368, conditional on 80% vaccine efficacy and market rate) and 80.6% (n=1655, conditional on 80% vaccine efficacy and free vaccines). After adjusting for significant background characteristics, positive attitudes toward COVID-19 vaccination (adjusted odds ratio [AOR] 1.20, 95% CI 1.15-1.25 and AOR 1.24, 95% CI 1.19-1.30), perceived support from significant others for getting a COVID-19 vaccination (AOR 1.43, 95% CI 1.32-1.55 and AOR 1.37, 95% CI 1.25-1.50), and perceived behavioral control to get a COVID-19 vaccination (AOR 1.51, 95% CI 1.32-1.73 and AOR 1.28, 95% CI 1.09-1.51) were positively associated with both dependent variables (conditional on 80% vaccine efficacy and market rate or free vaccines, respectively). Regarding social media influence, higher frequency of exposure to positive information related to COVID-19 vaccination was associated with a higher intention to receive a COVID-19 vaccination at market rate (AOR 1.53, 95% CI 1.39-1.70) or a free vaccination (AOR 1.52, 95% CI 1.35-1.71). Higher self-reported compliance with wearing a face mask in the workplace (AOR 1.27, 95% CI 1.02-1.58 and AOR 1.67, 95% CI 1.24-2.27) and other public spaces (AOR 1.80, 95% CI 1.42-2.29 and AOR 1.34, 95% CI 1.01-1.77), hand hygiene (AOR 1.21, 95% CI 1.00-1.47 and AOR 1.52, 95% CI 1.19-1.93), and avoiding social gatherings (AOR 1.22, 95% CI 1.01-1.47 and AOR 1.55, 95% CI 1.23-1.95) and crowded places (AOR 1.24, 95% CI 1.02-1.51 and AOR 1.73, 95% CI 1.37-2.18) were also positively associated with both dependent variables. The number of COVID-19 preventive measures implemented by the factory was positively associated with the intention to receive a COVID-19 vaccination under both scenarios (AOR 1.08, 95% CI 1.04-1.12 and AOR 1.06, 95% CI 1.01-1.11). Conclusions Factory workers in China reported a high behavioral intention to receive a COVID-19 vaccination. The theory of planned behavior is a useful framework to guide the development of future campaigns promoting COVID-19 vaccination.

Pharmacovigilance serves to detect previously unrecognised adverse events associated with the use of medicines. The simplest method for detecting signals of such events is crude inspection of lists of spontaneously reported drug-event combinations. Quantitative and automated numerator-based methods such as Bayesian data mining can supplement or supplant these methods. The theoretical basis and limitations of these methods should be understood by drug safety professionals, and automated methods should not be automatically accepted. Published evaluations of these techniques are mainly limited to large regulatory databases, and performance characteristics may differ in smaller safety databases of drug developers. Head-to-head comparisons of the major techniques have not been published. Regardless of previous statistical training, pharmacovigilance practitioners should understand how these methods work. The mathematical basis of these techniques should not obscure the numerous confounders and biases inherent in the data. This article seeks to make automated signal detection methods transparent to drug safety professionals of various backgrounds. This is accomplished by first providing a brief overview of the evolution of signal detection followed by a series of sections devoted to the methods with the greatest utilisation and evidentiary support: proportional reporting rations, the Bayesian Confidence Propagation Neural Network and empirical Bayes screening. Sophisticated yet intuitive explanations are provided for each method, supported by figures in which the underlying statistical concepts are explored. Finally the strengths, limitations, pitfalls and outstanding unresolved issues are discussed. Pharmacovigilance specialists should not be intimidated by the mathematics. Understanding the theoretical basis of these methods should enhance the effective assessment and possible implementation of these techniques by drug safety professionals.

This research demonstrated that information loss due to incomplete mapping of medical and drug codes as well as data structure in the current CDM THIN limits its use for all possible epidemiological evaluation studies. Current HOIs and DOIs predefined by the OMOP were constructed with minimal loss of information and can be used for active surveillance methodological research. The OMOP CDM THIN can be a valuable tool for multiple aspects of pharmacoepidemiological research when the unique features of UK Electronic Health Records are incorporated in the OMOP library.

Differences were observed between OMOP and Mini-Sentinel CDMs. The analysis of both CDMs at the data model level indicated that such conceptual differences had only a slight but not significant impact on identifying known safety associations. Our results show that differences at the ecosystem level of analyses across the CDMs can lead to strikingly different risk estimations, but this can be primarily attributed to the choices of analytic approach and their implementation in the community-developed analytic tools. The opportunities of using CDMs are clear, but our study shows the need for judicious comparison of analyses across the CDMs. Our work emphasizes the need for ongoing efforts to ensure sustainable transparent platforms to maintain and develop CDMs and associated tools for effective safety surveillance.