Abstract
Objectives The purpose of this study was to identify predictors of COVID-19 vaccine intention among Bangladeshi adults. Methods Secondary data from the COVID-19 Beliefs, Behaviors & Norms Survey conducted by the Massachusetts Institute of Technology (MIT) and Facebook were analyzed. Data were collected from 2,669 adult Facebook users in Bangladesh and was collected between February 15 and February 28, 2021. Binomial logistic regression examined the relationship between COVID-19 vaccination intent and demographic variables, risk perception, preventive behaviors, COVID-19 knowledge, and likelihood of future actions. Results Seventy-nine percent of respondents reported intent to get the COVID-19 vaccine when it becomes available. Intent to get vaccinated was highest among females, adults aged 71- 80, individuals with college or graduate-level degrees, city dwellers, and individuals who perceived that they were in excellent health. Results of the binomial logistic regression indicated that predictors of vaccination intent include age (OR = 1.39), high risk perception of COVID-19 (OR = 1.47), and intent to practice social distancing (OR = 1.22). Discussion Findings suggest that age, perceived COVID-19 risk, and non-pharmaceutical COVID-19 interventions may predict COVID-19 vaccination intent among Bangladeshi adults. Findings can be used to create targeted messaging to increase demand for and uptake of COVID-19 vaccines in Bangladesh.
| Original language | English |
|---|---|
| Article number | e0261929 |
| Journal | PLOS ONE |
| Volume | 17 |
| Issue number | 1 January 2022 |
| DOIs | |
| State | Published - 1 Jan 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- General
Fingerprint
Dive into the research topics of 'COVID-19 vaccine acceptance among Bangladeshi adults: Understanding predictors of vaccine intention to inform vaccine policy'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver