Spatiotemporal evolution of online attention to vaccines since 2011: An empirical study in China - Hu, Feng; Qiu, Liping; Xia, Wei; Liu, Chi-Fang; Xi, Xun; Zhao, Shuang; Yu, Jiaao; Wei, Shaobin; Hu, Xiao; Su, Ning; Hu, Tianyu; Zhou, Haiyan; et al. (Frontiers in Public Health, 2022)
Since the outbreak of Coronavirus Disease 2019 (COVID-19), the Chinese government has taken a number of measures to effectively control the pandemic. By the end of 2021, China achieved a full vaccination rate higher than 85%. The Chinese Plan provides an important model for the global fight against COVID-19. Internet search reflects the public's attention toward and potential demand for a particular thing. Research on the spatiotemporal characteristics of online attention to vaccines can determine the spatiotemporal distribution of vaccine demand in China and provides a basis for global public health policy making. This study analyzes the spatiotemporal characteristics of online attention to vaccines and their influencing factors in 31 provinces/municipalities in mainland China with Baidu Index as the data source by using geographic concentration index, coefficient of variation, GeoDetector, and other methods. The following findings are presented. First, online attention to vaccines showed an overall upward trend in China since 2011, especially after 2016. Significant seasonal differences and an unbalanced monthly distribution were observed. Second, there was an obvious geographical imbalance in online attention to vaccines among the provinces/municipalities, generally exhibiting a spatial pattern of “high in the east and low in the west.” Low aggregation and obvious spatial dispersion among the provinces/municipalities were also observed. The geographic distribution of hot and cold spots of online attention to vaccines has clear boundaries. The hot spots are mainly distributed in the central-eastern provinces and the cold spots are in the western provinces. Third, the spatiotemporal differences in online attention to vaccines are the combined result of socioeconomic level, socio-demographic characteristics, and disease control level.