Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Dec 23;19(12):e0312488.
doi: 10.1371/journal.pone.0312488. eCollection 2024.

Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China

Yaming Zhang  1   2 , Xiaoyu Guo  1   2 , Yanyuan Su  1
Affiliations

Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China

Yaming Zhang et al. PLoS One. .

Abstract

Background: Internet searches offer an indicator of public attention and possible demand for certain things. Studying the spatiotemporal characteristics of the public's concern for vaccination can determine the spatiotemporal distribution of demand for vaccines in China, and capture the changes in the health awareness of the Chinese population, thus informing future vaccination strategies.

Methods: Based on the collection of Baidu search indices for vaccination-related keywords in 363 cities in China, This paper seeks to explore the spatiotemporal changes and regional differences in public attention toward vaccination in China by using the seasonal index, seasonal concentration index, Herfindahl index, Moran index, and Dagum Gini coefficient.

Results: The following findings are presented. First, there are significant seasonal fluctuations and unbalanced monthly distributions of vaccination-related public attention in China. Second, the public attention in Chinese cities shows the spatial characteristics of "leading in the east, followed by the central, western and northeastern regions". The spatial correlation of attention has been strengthened, and the high-high clusters are mainly distributed in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Greater Bay Area (GBA) urban agglomerations. Third, regional differences in overall public attention narrowed in China, with intra-regional differences narrowing in seven regions (Northwest China, Central China, and so on), and intra-regional differences increasing in East China. The dominant role in the Gini coefficient changes from transvariation intensity to inter-regional differences.

Conclusion: Major public health emergencies stimulate the public's attention to health topics. Although the short-term increase in vaccination-related public attention was not observed to translate into a long-term increase in public vaccine literacy, the seasonal and regional differences in vaccination-related public attention in China have significantly narrowed before and after COVID-19, suggesting that the imbalance between public health literacy levels has improved.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Research design for the spatiotemporal dynamics of public attention.
Fig 2
Fig 2. Time series characteristics of the public attention index in China.
(a) The monthly average public attention index in China, 2019–2013. (b) The seasonal index of public attention index from January to December.
Fig 3
Fig 3. Average daily public attention index of 363 cities in China.
Subfigures (a) to (e) depict the average daily PAI for 363 cities from 2019 to 2023, respectively. Note: Fig 3 was produced based on the standard map GS (2019) 1822 on the website of the Standard Map Service of the Ministry of Natural Resources of China, with no modifications to the boundaries of the base map.
Fig 4
Fig 4. The cluster and outlier analysis of the average daily public attention index.
Subfigures (a) to (e) depict the cluster and outlier analysis results from 2019 to 2023, respectively. Note: Fig 4 was produced based on the standard map GS (2019) 1822 on the website of the Standard Map Service of the Ministry of Natural Resources of China, with no modifications to the boundaries of the base map.
Fig 5
Fig 5. Tendency of the intra-regional Gini coefficient of public attention.
Fig 6
Fig 6. Tendency of the inter-regional Gini coefficient of public attention.
Fig 7
Fig 7. The sources of the differences in public attention and the trends of their contributions.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Kim K, Shin S, Kim S, Lee EN. The Relation Between eHealth Literacy and Health-Related Behaviors: Systematic Review and Meta-analysis. J Med Internet Res. 2023;25:e40778. doi: 10.2196/40778 WOS:001009078900003. - DOI - PMC - PubMed
    1. Ozawa S, Schuh HB, Nakamura T, Yemeke TT, Lee YFA, Macdonald NE. How to increase and maintain high immunization coverage: Vaccination Demand Resilience (VDR) framework. Vaccine. 2023;41(45):6710–8. doi: 10.1016/j.vaccine.2023.09.027 WOS:001101511500001. - DOI - PubMed
    1. Chakrabarti A, Bair EF, Thirumurthy H. Routine child immunizations in India during the COVID-19 pandemic. Ssm-Popul Hlth. 2023;22:101383. doi: 10.1016/j.ssmph.2023.101383 WOS:001042996400001. - DOI - PMC - PubMed
    1. Omer SB, Benjamin RM, Brewer NT, Buttenheim AM, Callaghan T, Caplan A, et al.. Promoting COVID-19 vaccine acceptance: recommendations from the Commission on Vaccine Refusal, Acceptance, and Demand in the USA. Lancet. 2021;398(10317):2186–92. doi: 10.1016/S0140-6736(21)02507-1 WOS:000729467800016. - DOI - PMC - PubMed
    1. Islam MS, Siddique A, Akter R, Tasnim R, Sujan MSH, Ward PR, et al.. Knowledge, attitudes and perceptions towards COVID-19 vaccinations: a cross-sectional community survey in Bangladesh. Bmc Public Health. 2021;21(1):1851. doi: 10.1186/s12889-021-11880-9 WOS:000707009300004. - DOI - PMC - PubMed