Evaluating socioeconomic influences on Nipah virus vaccination decisions in Bangladesh through machine learning.

ABSTRACT: Nipah virus (NiV) is emerging as a noteworthy public health threat in Bangladesh, with propagation transpiring across accidental person-to-person contact and proximity with contaminated food or animals. Addressing the socio-demographic elements impacting the awareness of NiV is essential for productive public health initiatives. This study explores the impact of socio-demographic characteristics on individuals' willingness to get vaccinated (WGTV) for the Nipah virus during an outbreak in Bangladesh and to develop optimal control strategies using machine learning techniques. A cross-sectional survey in Bangladesh examined socio-demographic factors, health conditions, and common misconceptions about vaccination, and statistical analysis was performed using chi-square tests to identify signi

SUBMITTER: Zobayer A 

PROVIDER: S-EPMC12482778 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature