Epidemiological models are a mathematical representation of the transmission of certain diseases. Studying these models can help predict the spread of these diseases. This graduate project analyzes the Susceptible - Exposed - Infectious - Recovered - Vaccinated (SEIRV) model as it relates to measles and explores the contribution of each parameter within the model, specifically the vaccination rate, to help predict and prevent the spread of measles. Using an Ensemble Kalman Filter (EnKF), each compartment population in the SEIRV model can be estimated, along with unknown parameters. In this work, the vaccination rate of measles is estimated using the EnKF in order to approximate the trend of vaccination rates over years and predict a measles outbreak. This is done using simulated data motivated by the potential of applying this method to an example with real data.

Creator

• Folino, Molly

Contributors

• Arnold, Andrea N.

Degree

• MS

Unit

• Mathematical Sciences

Publisher

• Worcester Polytechnic Institute

Identifier

• etd-109201

Advisor

• Arnold, Andrea N.

Defense date

• 2023-05-05

Year

• 2023

Date created

• 2023-05-05

Resource type

• Report

Source

• etd-109201

Rights statement

• In Copyright

Last modified

• 2023-06-01