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Zhang SS, Shi W, Du J, Zhang WX, Yuan M, Zhou Y, Wang L, Zhao T, Ma QY, Zhang S, Yang H, Zhang X, Wang M, Huang N, Zeng J, Liu Y, Zhang Y, Cui F, Lu QB. Impact of propensity to COVID-19 vaccination/vaccine on influenza vaccination from willingness to behavior among older adults in rural China. Hum Vaccin Immunother 2024; 20:2428017. [PMID: 39539085 PMCID: PMC11572224 DOI: 10.1080/21645515.2024.2428017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2024] [Revised: 10/19/2024] [Accepted: 11/07/2024] [Indexed: 11/16/2024] Open
Abstract
To explore impact of the propensity to coronavirus disease 2019 (COVID-19) vaccine/vaccination on influenza vaccination from willingness to behavior after COVID-19 pandemic among older adults in rural China. A combined study involving a cross-sectional survey for the willingness of influenza vaccination, a health education momentary intervention and a community intervention program were conducted from September 11th to 16th, 2023 among rural older adults in China. Totally 3138 individuals were investigated in this study with 1923 (61.3%) willing to receive influenza vaccination. After the momentary intervention, 47.8% (582/1215) individuals changed to be willing to receive influenza vaccination. There were 1440 (78.8%) vaccinated. The influenza vaccination willingness rate was significantly higher in the participants willing to receive COVID-19 vaccine booster dose vaccination than the participants unwilling to (69.4% vs. 37.7%, adjusted OR [aOR] = 2.671, 95% CI 2.211-3.227, p < .001), as well as for the influenza vaccination willingness change rate (52.2% vs. 41.7%, aOR = 1.303, 95% CI 1.022-1.662, p < .05) and the influenza vaccination behavior rate (79.7% vs. 74.9%, aOR = 1.337, 95% CI 1.002-1.784, p < .05). The influenza vaccination behavior rate was significantly higher in those positive toward COVID-19 vaccine effectiveness or safety overall (80.0% vs. 74.9%, aOR = 1.394, 95% CI 1.065-1.823; 80.6% vs. 70.9%, aOR = 1.850, 95% CI 1.395-2.454; both p < .05). There was a positive impact of COVID-19 vaccine/vaccination on influenza vaccination from willingness to behavior among the older adults in rural China after COVID-19 pandemic, suggesting that integrating health education of related pathogens and vaccines might promote influenza vaccination.
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Affiliation(s)
- Shan-Shan Zhang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
| | - Wanna Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Juan Du
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Wan-Xue Zhang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | | | - Yiguo Zhou
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Lili Wang
- Department of Immunization Program, Lingcheng Center for Diseases Control and Prevention, Dezhou, China
| | - Tianshuo Zhao
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Qin-Yi Ma
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Sihui Zhang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Han Yang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Xiyu Zhang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Mingting Wang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Ninghua Huang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Ministry of Education, Key Laboratory of Epidemiology of Major Diseases (Peking University), Beijing, China
| | - Jing Zeng
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Ministry of Education, Key Laboratory of Epidemiology of Major Diseases (Peking University), Beijing, China
| | - Yaqiong Liu
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
| | - Yuanshan Zhang
- Department of Infectious Diseases Control, Lingcheng Center for Diseases Control and Prevention, Dezhou, China
| | - Fuqiang Cui
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Qing-Bin Lu
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
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Enayati M, Arlikatti S, Ramesh MV. A qualitative analysis of rural fishermen: Potential for blockchain-enabled framework for livelihood sustainability. Heliyon 2024; 10:e24358. [PMID: 38288013 PMCID: PMC10823113 DOI: 10.1016/j.heliyon.2024.e24358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/05/2024] [Accepted: 01/08/2024] [Indexed: 01/31/2024] Open
Abstract
Rural fishing communities face numerous challenges related to livelihood security, as they are engaged in a risky and labour-intensive occupation. They often receive only a small portion of the profits, due to the influence of self-serving local intermediaries, lack of transparency in the business processes, trust issues, and power differentials among stakeholders. Although still in its infancy, blockchain technology has been adopted in various urban settings to mitigate similar challenges and to build trust through its security attributes, data ledger transparency, and smart contract automation. Yet, few have explored the efficacy of blockchain technology in addressing the unique challenges faced by rural fishermen in marketing their catch and connecting them to a broader range of customers for improved livelihood resilience. This study aims to examine how the livelihood resilience of fishermen can be increased through the potential of a blockchain, in a fishing community in the coastal village of Alappad in Kerala, India. Thematic analysis of data acquired from 43 semi-structured qualitative interviews and participatory rural appraisal tools revealed five categories of challenges: business cost and profitability, government regulations, low education and digital illiteracy, socio-cultural limitations, and over-dependence on middlemen as inhibitors to fishermen's livelihoods. The study proposes a blockchain-based e-commerce framework to mitigate selected challenges that emerged due to a lack of trust and transparency in the local fish market. It contributes to rural development by exploring an innovative, solution aligned with five UN Sustainable Development Goals, in contrast to the Business-as-usual approach in offering technological solutions.
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Affiliation(s)
- Mojtaba Enayati
- Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri, India
| | - Sudha Arlikatti
- Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri, India
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