Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B model

Author:

Suwanbamrung CharuaiORCID,Srinam Benchawan,Promkool Pakawan,Suwannakarn Warissara,Siripanich Sangchom,Rahman Md. SiddikurORCID,Stanikzai Muhammad HaroonORCID

Abstract

Background The COVID-19 pandemic has imposed unprecedented suffering on social and individual levels worldwide. Vaccines against COVID-19 have been prioritized as a crucial strategy for ending the pandemic as well as minimizing its consequences. Objectives This study aimed to determine the uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the Capability, Opportunity, Motivation, and Behavior (COM-B) model. Methods We conducted a web-based cross-sectional study in the Hat Yai district, Songkhla province in Southern Thailand, in September and October 2021. The questionnaire was composed of sections on sociodemographic characteristics, COVID-19 vaccination status, and COM-B constructs. We employed a multivariable logistic regression analysis to determine factors associated with the uptake of the COVID-19 vaccine. We set statistical significance at p < 0.05. Results In this study, females constituted 54.7% of the total participants (n = 358), and nearly half of the participants (45.8%) were in the younger age group (18–29). Of all the participants, 59.5% (95%CI: 54.2%-64.6%) received at least one dose of the COVID-19 vaccine. Factors associated with the uptake of COVID-19 vaccine and their adjusted OR (95% CI) were being married: 3.59 (2.06–6.24), having a graduate degree: 2.34 (1.38–3.96), gainfully employed: 3.30 (1.91–5.67), having a high level of opportunity: 2.90 (1.48–5.66), and having a high level of motivation: 2.87 (1.17–17.08). Conclusion The uptake of COVID-19 vaccines was moderate in this population. Moreover, the results showed that the COM-B model is useful in predicting COVID-19 vaccine uptake. The findings of this study could be used to aid future public health interventions in any event of outbreaks similar to COVID-19 disease in Thailand and beyond.

Funder

Walailak University

Publisher

Public Library of Science (PLoS)

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