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Moussa OZ, Takeuchi K. Does searching online for vaccination information affect vaccination coverage? Evidence from Sub-Saharan African countries. ECONOMICS AND HUMAN BIOLOGY 2022; 47:101181. [PMID: 36116175 DOI: 10.1016/j.ehb.2022.101181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 08/23/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
The Internet is reshaping the way people access health information. Over the past decades, an increasing number of people have been using the Internet to access vaccine-related information. Many studies suggest that the Internet can help improve people's understanding of health issues but at the same time facilitate the rapid spread of misinformation. This study explores the impact that searching the Internet for immunization information has on vaccination coverage. Using Google trends data, we found that access to online vaccination information has impacted vaccine uptake from 2004 to 2017, in Sub-Saharan African countries. The results indicate an overall positive impact on vaccine uptake. We also found that the effects are heterogeneous among vaccines. The effect is statistically significant for the vaccine related to high-risk disease, but not significant for the controversial vaccine and the vaccine related to low-risk disease.
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Affiliation(s)
- Ouattara Zieh Moussa
- Graduate School of Economics, Kobe University, 2-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo Prefecture 657-8501, Japan.
| | - Kenji Takeuchi
- Graduate School of Economics, Kobe University, 2-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo Prefecture 657-8501, Japan
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Hu F, Qiu L, Xia W, Liu CF, Xi X, Zhao S, Yu J, Wei S, Hu X, Su N, Hu T, Zhou H, Jin Z. Spatiotemporal evolution of online attention to vaccines since 2011: An empirical study in China. Front Public Health 2022; 10:949482. [PMID: 35958849 PMCID: PMC9360794 DOI: 10.3389/fpubh.2022.949482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 06/28/2022] [Indexed: 11/30/2022] Open
Abstract
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.
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Affiliation(s)
- Feng Hu
- Global Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China
| | - Liping Qiu
- Global Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China
| | - Wei Xia
- Institute of International Business and Economics Innovation and Governance, Shanghai University of International Business and Economics, Shanghai, China
| | - Chi-Fang Liu
- Department of Business Administration, Cheng Shiu University, Kaohsiung, Taiwan
| | - Xun Xi
- School of Management, Shandong Technology and Business University, Yantai, China
| | - Shuang Zhao
- Business School, Hohai University, Nanjing, China
| | - Jiaao Yu
- London College of Communication, University of the Arts London, London, United Kingdom
| | - Shaobin Wei
- Institute of Spatial Planning & Design, Zhejiang University City College, Hangzhou, China
| | - Xiao Hu
- Cash Crop Workstation, Shangcheng Bureau of Agriculture and Rural Affairs, Shangcheng, China
| | - Ning Su
- School of MBA, Zhejiang Gongshang University, Hangzhou, China
| | - Tianyu Hu
- School of Information Engineering, Zhengzhou University, Zhengzhou, China
| | - Haiyan Zhou
- Institute of Artificial Intelligence and Change Management, Shanghai University of International Business and Economics, Shanghai, China
- *Correspondence: Haiyan Zhou
| | - Zhuang Jin
- Baotou Teachers' College, Inner Mongolia University of Science & Technology, Baotou, China
- Zhuang Jin
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