Mapping Mpox vaccine hesitancy using an integrated machine learning and structural equation modeling approach

Area of Science:

• Public Health
• Behavioral Science
• Computational Epidemiology

Background:

• Mpox (Monkeypox) vaccination strategies necessitate understanding behavioral determinants.
• Assessing vaccine intention is crucial for effective public health interventions in Bangladesh.

Purpose of the Study:

• To investigate Mpox vaccine intention in Bangladesh using an integrated computational approach.
• To identify demographic, attitudinal, and social-structural factors influencing Mpox vaccination decisions.

Main Methods:

• Analysis of data from 405 participants using frequentist statistics, t-distributed Stochastic Neighbour Embedding (t-SNE), and structural equation modelling (SEM).
• Examined relationships between demographics, vaccine knowledge, social factors, and vaccination intention.

Main Results:

• 77% of participants expressed willingness to be vaccinated, influenced by age, education, and occupation.
• Two distinct patterns of vaccine reluctance were identified: practical barriers and neutral/skeptical attitudes.
• Perceived vaccine efficacy was the primary driver of intention, with social-structural factors like family structure also playing a significant role.

Conclusions:

• Mpox vaccine hesitancy is not uniform and varies significantly within the population.
• Public health interventions in South Asia should adopt customized approaches targeting specific "efficacy gaps" and structural obstacles.
• Prosocial motivation and community advocacy are key drivers for vaccination intention.