Application of SEIRV Model in Prediction of Mpox Development: A Survey-Based Vaccination Hesitancy Study
Name
Yuexi Li
Major
Applied Mathematics and Computational Science / Math
Class
2023
About
Yuexi (Kylee) is an Applied Mathematics major student interested in biomedical topic modeling and global health statistical methods.
Signature Work Project Overview
This project aimed to gauge vaccination hesitancy among U.S. residents in the next six months by conducting an anonymous online survey of 316 participants. The survey results were used to inform parameters for an SEIRV model, which predicted the impact of varying vaccination rates on the future spread of mpox. The SEIRV model analysis revealed the disease-free and fully endemic equilibria, which were locally stable. Sensitivity analysis was conducted to assess the impact of parameters on the model. The survey data indicated that 19% (60) more participants plan to get vaccinated in the next six months, resulting in a 0.2 increase in the vaccination rate. The study found that both sexual orientation (P=0.004, CI [1.18‐2.39]) and confidence level in mpox vaccines (P=0.000, CI [1.70‐4.58]) significantly impacted vaccination hesitancy. Increasing the vaccination rate by 0.2 could shorten the endemic duration by half in the next six months, resulting in 75\% fewer infections and a 50% increase in vaccinations. Therefore, advertising campaigns promoting mpox vaccinations are necessary to curb transmission.