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Zhao J, Wu S, Rafal RA, Manguerra H, Dong Q, Huang H, Lau L, Wei X. Vaccine equity implementation: exploring factors influencing COVID-19 vaccine delivery in the Philippines from an equity lens. BMC Public Health 2024; 24:3058. [PMID: 39501210 PMCID: PMC11539703 DOI: 10.1186/s12889-024-20578-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/30/2024] [Indexed: 11/08/2024] Open
Abstract
BACKGROUND During the early phase of the COVID-19 vaccine rollout, low and middle-income countries (LMICs) were facing challenges in achieving equitable vaccine delivery. Few studies have contextualized global vaccine distributive injustice into national-specific contexts to understand its impact on vaccine delivery from an equity perspective. We aimed to investigate factors influencing equitable COVID-19 vaccine delivery in the Philippines and to provide recommendations to enhance equitable vaccine delivery in LMICs to prepare for future health emergencies. METHODS The Health Equity Implementation Framework was employed to guide this qualitative study. We recruited participants using purposeful and snowballing sampling strategies. Semi-structured interviews were conducted with participants in person, online, or over the phone. A reflective thematic analysis approach was employed to analyze data. RESULTS We recruited 38 participants including seven high-level stakeholders from the public and private sectors, 14 health workers, and 17 community members in the province of Negros Occidental, Philippines. Equitable delivery of COVID-19 vaccines was influenced by an interplay of multiple factors operating in different domains. Contextually, the rapidly evolving nature of the COVID-19 virus, ongoing scientific advancements, and international negotiations directed national-level vaccine policies. Political commitment and support were recognized as crucial drivers for successful vaccine delivery, with a strong emphasis on health information framing and communication and adherence to human rights principles. The vulnerability of the health system significantly impacted the timely and effective distribution of vaccines. Furthermore, the geographical characteristics of the Philippines presented unique logistical challenges to vaccine delivery. At the recipient domain, individual perceptions of vaccines, shaped by their socioeconomic status, exposure to (mis)information, social influence, and entrenched religious beliefs, played a major role in their vaccine decisions and thus vaccine coverage regionally. Additionally, vaccine characteristics and operational challenges related to its distribution also impacted fair allocation. CONCLUSIONS The findings highlight the urgent need for LMICs to strengthen their health system resilience and sustainability and use multilevel strategies to build public trust to improve vaccine uptake and coverage. Moreover, each LMIC must be attentive to its unique contextual factors to develop tailored implementation strategies to promote equitable vaccine distribution.
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Affiliation(s)
- Junqiang Zhao
- Waypoint Research Institute, Waypoint Centre for Mental Health Care, Penetanguishene, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Shishi Wu
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Renz Andrew Rafal
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | | | - Quanfang Dong
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Hongyu Huang
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Lincoln Lau
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- International Care Ministries, Manila, Philippines
| | - Xiaolin Wei
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
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Ferris BF, Balasubramanian S, Rajamanickam A, Munisankar S, Dasan B, Menon PA, Loke P, Babu S, Chami GF. Relative contribution of biomedical, demographic, and socioeconomic factors to COVID-19 vaccine receipt in rural India. PLoS One 2024; 19:e0305819. [PMID: 38913614 PMCID: PMC11195973 DOI: 10.1371/journal.pone.0305819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 06/05/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND In the first year of roll-out, vaccination for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevented almost 20 million deaths from coronavirus disease 2019 (COVID-19). Yet, little is known about the factors influencing access to vaccination at the individual level within rural poor settings of low-income countries. The aim of this study was to examine determinants of vaccine receipt in rural India. METHODS A census of a rural village in Tamil Nadu was undertaken from June 2021 to September 2022. We surveyed 775 participants from 262 households. Household-level data on socioeconomic status (SES), water, sanitation, and hygiene practices, and individual-level demographic information, travel history, and biomedical data, including anthropometry, vital signs, and comorbidities, were collected. Logistic regression models with 5-fold cross-validation were used to identify the biomedical, demographic, and socioeconomic determinants of vaccine receipt and the timing of receipt within the first 30 days of eligibility. Vaccine ineligible participants were excluded leaving 659 eligible participants. There were 650 eligible participants with complete biomedical, demographic, and socioeconomic data. RESULTS There were 68.0% and 34.0% of individuals (N = 650) who had received one and two vaccine doses, respectively. Participants with household ownership of a permanent account number (PAN) or ration card were 2.15 (95% CI:1.32-3.52) or 3.02 (95% CI:1.72-5.29) times more likely to receive at least one vaccine dose compared to households with no ownership of such cards. Participants employed as housewives or self-employed non-agricultural workers were 65% (95% CI:0.19-0.67) or 59% (95% CI:0.22-0.76) less likely to receive at least one vaccine dose compared to salaried workers. Household PAN card ownership, occupation and age were linked to the timing of vaccine receipt. Participants aged ≤18 and 45-60 years were 17.74 (95% CI:5.07-62.03) and 5.51 (95% CI:2.74-11.10) times more likely to receive a vaccine within 30 days of eligibility compared to 19-44-year-olds. Biomedical factors including BMI, vital signs, comorbidities, and COVID-19 specific symptoms were not consistently associated with vaccine receipt or timing of receipt. No support was found that travel history, contact with COVID-19 cases, and hospital admissions influenced vaccine receipt or timing of receipt. CONCLUSION Factors linked to SES were linked to vaccine receipt, more so than biomedical factors which were targeted by vaccine policies. Future research should explore if government interventions including vaccine mandates, barriers to vaccine access, or peer influence linked to workplace or targeted vaccine promotion campaigns underpin these findings.
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Affiliation(s)
- Bethany F. Ferris
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - Suganthi Balasubramanian
- National Institutes of Health – National Institute for Research in Tuberculosis -International Center for Excellence in Research (NIH-ICER), Chennai, Tamil Nadu, India
| | - Anuradha Rajamanickam
- National Institutes of Health – National Institute for Research in Tuberculosis -International Center for Excellence in Research (NIH-ICER), Chennai, Tamil Nadu, India
| | - Saravanan Munisankar
- National Institutes of Health – National Institute for Research in Tuberculosis -International Center for Excellence in Research (NIH-ICER), Chennai, Tamil Nadu, India
| | - Bindu Dasan
- National Institutes of Health – National Institute for Research in Tuberculosis -International Center for Excellence in Research (NIH-ICER), Chennai, Tamil Nadu, India
| | - Pradeep A. Menon
- Indian Council of Medical Research – National Institute for Research in Tuberculosis, Chennai, Tamil Nadu, India
| | - P'ng Loke
- Laboratory of Parasitic Diseases, National Institutes of Health National Institutes of Allergy and Infectious Diseases (NIAID), Bethesda, Maryland, United States of America
| | - Subash Babu
- National Institutes of Health – National Institute for Research in Tuberculosis -International Center for Excellence in Research (NIH-ICER), Chennai, Tamil Nadu, India
- Laboratory of Parasitic Diseases, National Institutes of Health National Institutes of Allergy and Infectious Diseases (NIAID), Bethesda, Maryland, United States of America
| | - Goylette F. Chami
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, Oxfordshire, United Kingdom
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Limbu YB, Gautam RK. How Well the Constructs of Health Belief Model Predict Vaccination Intention: A Systematic Review on COVID-19 Primary Series and Booster Vaccines. Vaccines (Basel) 2023; 11:816. [PMID: 37112728 PMCID: PMC10141697 DOI: 10.3390/vaccines11040816] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/02/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
This systematic review synthesizes the findings of quantitative studies examining the relationships between Health Belief Model (HBM) constructs and COVID-19 vaccination intention. We searched PubMed, Medline, CINAHL, Web of Science, and Scopus using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and identified 109 eligible studies. The overall vaccination intention rate was 68.19%. Perceived benefits, perceived barriers, and cues to action were the three most frequently demonstrated predictors of vaccination intention for both primary series and booster vaccines. For booster doses, the influence of susceptibility slightly increased, but the impact of severity, self-efficacy, and cues to action on vaccination intention declined. The impact of susceptibility increased, but severity's effect declined sharply from 2020 to 2022. The influence of barriers slightly declined from 2020 to 2021, but it skyrocketed in 2022. Conversely, the role of self-efficacy dipped in 2022. Susceptibility, severity, and barriers were dominant predictors in Saudi Arabia, but self-efficacy and cues to action had weaker effects in the USA. Susceptibility and severity had a lower impact on students, especially in North America, and barriers had a lower impact on health care workers. However, cues to action and self-efficacy had a dominant influence among parents. The most prevalent modifying variables were age, gender, education, income, and occupation. The results show that HBM is useful in predicting vaccine intention.
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Affiliation(s)
- Yam B. Limbu
- Feliciano School of Business, Montclair State University, 1 Normal Ave., Montclair, NJ 07043, USA
| | - Rajesh K. Gautam
- Department of Anthropology, Dr. Harisingh Gour Central University, Sagar 470003, MP, India;
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Anagaw TF, Tiruneh MG, Fenta ET. Application of behavioral change theory and models on COVID-19 preventive behaviors, worldwide: A systematic review. SAGE Open Med 2023; 11:20503121231159750. [PMID: 37026109 PMCID: PMC10067469 DOI: 10.1177/20503121231159750] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/08/2023] [Indexed: 04/03/2023] Open
Abstract
Objective: This systematic review aimed to assess the global application of behavioral change theory and models on COVID-19 preventive behaviors. Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedure. Databases such as PubMed/MIDLINE, Web of Science, Scopus, EMB ASE, World Health Organization libraries, and Google Scholar were used to search all published articles in the area of application of behavioral change theory and model on COVID-19 preventive behavior until October 1, 2022. Studies published in another language other than English were excluded. Two independent reviewers did the article selection and quality check. A third reviewer asked if any disagreement were found. Result: Seventeen thousand four hundred thirty-six total articles were retrieved from all sources after the removal of duplicated articles and those not evaluating the outcome of interest were excluded. Finally, 82 articles done using behavioral change theory and model on COVID-19 preventive behaviors were included. The health belief model (HBM) and theory of planned behavior (TPB) were most commonly used in COVID-19 preventive behaviors. The constructs of most behavioral theories and models were significantly associated with COVID-19 preventive behaviors such as hand washing, face mask use, vaccine uptake, social isolation, self-quarantine, social distance, and use of sanitizers. Conclusion: This systematic review summarizes comprehensive evidence on the application of behavioral change theory and model on COVID-19 preventive behaviors globally. A total of seven behavioral change theories and models were included. The HBM and TPBs were most commonly used for COVID-19 preventive behaviors. Therefore, the application of behavioral change theory and models is recommended for developing behavioral change interventional strategies.
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Affiliation(s)
- Tadele Fentabil Anagaw
- Department of Health Promotion and Behavioural Science, School of Public health, College of Medicine and Health Science, Bahir Dar University, Bahir Dar, Ethiopia
| | - Misganaw Guadie Tiruneh
- Department of Public health, College of Medicine and Health Science, Woldia University, Woldia, Ethiopia
| | - Eneyew Talie Fenta
- Department of Public health, College of Medicine and Health Science, Injibara University, Injibara, Ethiopia
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Berdida DJE, Franco FMC, Santos XAG, Dacol CB, Dimaano M, Rosario ESD, Lantin CC. Filipinos' COVID-19 vaccine hesitancy comments in TikTok videos: A manifest content analysis. Public Health Nurs 2023; 40:135-143. [PMID: 36300833 PMCID: PMC9874770 DOI: 10.1111/phn.13143] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/28/2022] [Accepted: 09/28/2022] [Indexed: 01/28/2023]
Abstract
OBJECTIVES Vaccine hesitancy is one of the top 10 threats to world health. The ongoing pandemic highlighted this health threat. The COVID-19 vaccine hesitancy remains underreported in the Philippines. Thus, this study aimed to describe and analyze the comments of Filipinos in TikTok videos about COVID-19 vaccine hesitancy. DESIGN Manifest content analysis. SAMPLE A total of 25 TikTok videos and their comments (n = 4564) were analyzed. METHODS We collected data between July 2021 and October 2021. Bengtsson's approach to content analysis was utilized to analyze the data. Data were validated using member-checking and intercoder reliability. RESULTS This study afforded three themes of COVID-19 vaccine hesitancy: (a) fear and mistrust (subthemes: influence of Dengvaxia vaccine, the influence of people who refuse to be vaccinated, lack of trust in the government, lack of trust in healthcare workers, doubts on vaccines' effectiveness), (b) misinformation and disinformation (subthemes: misbeliefs, insufficient knowledge), and (c) adamant attitudes (subthemes: unwillingness to be vaccinated, picky on vaccine brand). CONCLUSION Our study established Filipinos' diverse reasons for COVID-19 vaccine hesitancy. TikTok, as a social media platform, is used for COVID-19 vaccine discussions and the dissemination of misinformation. To prepare for the next pandemic or public health disaster, the government, HCWs, and the public must efficiently convey timely, accurate health information and dispel misinformation on social media platforms.
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Affiliation(s)
- Daniel Joseph E. Berdida
- College of NursingUniversity of Santo TomasManilaPhilippines
- Department of NursingCollege of Health SciencesUniversidad de ManilaManilaPhilippines
| | | | | | - Camille B. Dacol
- Department of NursingCollege of Health SciencesUniversidad de ManilaManilaPhilippines
| | - Michaela Dimaano
- Department of NursingCollege of Health SciencesUniversidad de ManilaManilaPhilippines
| | - Erika S. Del Rosario
- Department of NursingCollege of Health SciencesUniversidad de ManilaManilaPhilippines
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Cabanilla KI, Enriquez EAT, Velasco AC, Mendoza VMP, Mendoza R. Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level. PeerJ 2022; 10:e14151. [PMID: 36199283 PMCID: PMC9528907 DOI: 10.7717/peerj.14151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/07/2022] [Indexed: 01/21/2023] Open
Abstract
In this work, we present an approach to determine the optimal location of coronavirus disease 2019 (COVID-19) vaccination sites at the municipal level. We assume that each municipality is subdivided into smaller administrative units, which we refer to as barangays. The proposed method solves a minimization problem arising from a facility location problem, which is formulated based on the proximity of the vaccination sites to the barangays, the number of COVID-19 cases, and the population densities of the barangays. These objectives are formulated as a single optimization problem. As an alternative decision support tool, we develop a bi-objective optimization problem that considers distance and population coverage. Lastly, we propose a dynamic optimization approach that recalculates the optimal vaccination sites to account for the changes in the population of the barangays that have completed their vaccination program. A numerical scheme that solves the optimization problems is presented and the detailed description of the algorithms, which are coded in Python and MATLAB, are uploaded to a public repository. As an illustration, we apply our method to determine the optimal location of vaccination sites in San Juan, a municipality in the province of Batangas, in the Philippines. We hope that this study may guide the local government units in coming up with strategic and accessible plans for vaccine administration.
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Affiliation(s)
- Kurt Izak Cabanilla
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
| | | | | | | | - Renier Mendoza
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
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Cabanilla KI, Enriquez EAT, Velasco AC, Mendoza VMP, Mendoza R. Optimal selection of COVID-19 vaccination sites in the Philippines at the municipal level. PeerJ 2022. [PMID: 36199283 DOI: 10.1101/2021.06.20.21259194] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023] Open
Abstract
In this work, we present an approach to determine the optimal location of coronavirus disease 2019 (COVID-19) vaccination sites at the municipal level. We assume that each municipality is subdivided into smaller administrative units, which we refer to as barangays. The proposed method solves a minimization problem arising from a facility location problem, which is formulated based on the proximity of the vaccination sites to the barangays, the number of COVID-19 cases, and the population densities of the barangays. These objectives are formulated as a single optimization problem. As an alternative decision support tool, we develop a bi-objective optimization problem that considers distance and population coverage. Lastly, we propose a dynamic optimization approach that recalculates the optimal vaccination sites to account for the changes in the population of the barangays that have completed their vaccination program. A numerical scheme that solves the optimization problems is presented and the detailed description of the algorithms, which are coded in Python and MATLAB, are uploaded to a public repository. As an illustration, we apply our method to determine the optimal location of vaccination sites in San Juan, a municipality in the province of Batangas, in the Philippines. We hope that this study may guide the local government units in coming up with strategic and accessible plans for vaccine administration.
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Affiliation(s)
- Kurt Izak Cabanilla
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
| | | | | | - Victoria May P Mendoza
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
| | - Renier Mendoza
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
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