School of Public Health, NHC Key Laboratory of Health Technology Assessment, and Global Health Institute, Fudan University, 130 Dong'an Road, Shanghai, 200032, China.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, England.
Bull World Health Organ. 2024 Jan 1;102(1):32-45. doi: 10.2471/BLT.23.289682. Epub 2023 Oct 31.
To assess spatiotemporal trends in, and determinants of, the acceptance of coronavirus disease 2019 (COVID-19) vaccination globally, as expressed on the social media platform X (formerly Twitter).
We collected over 13 million posts on the platform regarding COVID-19 vaccination made between November 2020 and March 2022 in 90 languages. Multilingual deep learning XLM-RoBERTa models annotated all posts using an annotation framework after being fine-tuned on 8125 manually annotated, English-language posts. The annotation results were used to assess spatiotemporal trends in COVID-19 vaccine acceptance and confidence as expressed by platform users in 135 countries and territories. We identified associations between spatiotemporal trends in vaccine acceptance and country-level characteristics and public policies by using univariate and multivariate regression analysis.
A greater proportion of platform users in the World Health Organization's South-East Asia, Eastern Mediterranean and Western Pacific Regions expressed vaccine acceptance than users in the rest of the world. Countries in which a greater proportion of platform users expressed vaccine acceptance had higher COVID-19 vaccine coverage rates. Trust in government was also associated with greater vaccine acceptance. Internationally, vaccine acceptance and confidence declined among platform users as: (i) vaccination eligibility was extended to adolescents; (ii) vaccine supplies became sufficient; (iii) nonpharmaceutical interventions were relaxed; and (iv) global reports on adverse events following vaccination appeared.
Social media listening could provide an effective and expeditious means of informing public health policies during pandemics, and could supplement existing public health surveillance approaches in addressing global health issues.
评估全球社交媒体平台 X（原 Twitter）上表达的对 2019 年冠状病毒病（COVID-19）疫苗接种的接受程度的时空趋势及其决定因素。
我们收集了该平台上自 2020 年 11 月至 2022 年 3 月间以 90 种语言发表的 1300 多万篇与 COVID-19 疫苗接种相关的帖子。多语言深度学习 XLM-RoBERTa 模型使用一个标注框架对所有帖子进行标注，该框架在对 8125 篇人工标注的英文帖子进行微调后使用。标注结果用于评估 135 个国家和地区的平台用户在 COVID-19 疫苗接种接受度和信心方面的时空趋势。我们通过单变量和多变量回归分析，确定了疫苗接受度的时空趋势与国家层面特征和公共政策之间的关联。
世界卫生组织东南亚、东地中海和西太平洋区域的平台用户中，表达疫苗接受度的比例高于世界其他地区的用户。平台用户中表达疫苗接受度比例较高的国家 COVID-19 疫苗接种率也较高。对政府的信任也与更高的疫苗接受度有关。在国际上，随着以下情况的发生，平台用户对疫苗的接受度和信心下降：（i）扩大了青少年的接种资格；（ii）疫苗供应充足；（iii）非药物干预措施放宽；（iv）全球出现疫苗接种后不良反应报告。
社交媒体监测可以为大流行期间制定公共卫生政策提供一种有效和迅速的手段，并可以补充现有的公共卫生监测方法，以解决全球卫生问题。
