Despite the unprecedented success in the rapid development of several effective vaccines against the Cov-SARS-2, global vaccination rollout efforts suffer from vaccine distribution inequality and vaccine acceptance, leading to insufficient public immunity provided by the vaccine products. While a major current focus in vaccine acceptance research is how to model and inform vaccine acceptance based on social-demographic parameters, characteristics of vaccine acceptance are not well understood and in particular, it is not known whether and how information diffusion influences vaccine acceptance. This study examines how information diffusion can change vaccine acceptance by developing a comprehensive computational model with an agent-based simulation technique to overcome the modeling and quantification complexity associated with socio-demographics, vaccine types, population statistics, and information diffusion. Our analyses, calibrated by the vaccine acceptance survey data from the provinces and territories of Canada, provide clear evidence that the propagation of information can greatly influence vaccine acceptance rates. The results illustrate that spread of negative messages about the COVID-19 vaccines can cause significant vaccine hesitancy that challenges the goal of a high public immunity provided by the vaccines. Our findings might help solve the vaccine hesitancy problem by focusing more on individuals' opinions and behavior.
翻译:尽管在迅速发展针对Cov-SARS-2的几种有效疫苗方面取得了前所未有的成功,但全球疫苗推广工作却因疫苗分配不平等和接受疫苗而遭遇到疫苗分配不平等和疫苗被接受,导致疫苗产品不能充分提供公共免疫。虽然疫苗接受研究目前的一个主要重点是如何根据社会人口参数来建模和通报疫苗的接受情况,但疫苗接受情况的特点并未得到很好地理解,特别是不知道信息传播是否以及如何影响疫苗的接受。这项研究研究信息传播如何能够改变疫苗的接受情况,方法是开发一个全面的计算模型,采用以代理为基础的模拟技术来克服与社会人口、疫苗类型、人口统计和信息传播有关的模型和定量复杂性。我们根据加拿大各省和地区的疫苗接受情况调查数据所作的分析,提供了明确的证据,表明信息传播会大大影响疫苗接受率。结果表明,传播关于COVID-19疫苗的负面信息可能会导致对疫苗提供的高公共免疫目标产生挑战。我们的调查结果可能有助于解决疫苗传播问题,因为更多地关注个人的意见和行为。