Imputing Measles Outbreak Data Based on COVID-19 Vaccine Hesitancy

Vaccine hesitancy is on the rise nationally, resulting in outbreaks of dangerous diseases such as measles. In counties where measles vaccine uptake is low, measles outbreaks tend to go underreported.  Measles outbreak data from neighboring Canada suggesting measles is likely more prevalent in the U.S. than is reported.  Available, comprehensive data on the relationship between vaccine uptake and outbreaks during the COVID-19 pandemic might allow us to impute missing measles data and better predict measles outbreaks.

Interested students should indicate in their application essay any relevant coursework.  Programming proficiency and basic knowledge of probability and statistics is a necessary skill; background or interest in operations research preferred.  This is applied research, so students should expect a fair number of computational tasks. However it is not just a coding project.

Name of research group, project, or lab
MuddOR Lab (Prof. Martonosi)
Why join this research group or lab?

This is a great opportunity for students who want to learn how to use mathematical and statistical models to inform public policy.

Logistics Information:
Project categories
Mathematics
Data Science
Operations Research
Statistical Modeling
Student ranks applicable
Sophomore
Junior
Senior
Student qualifications

- Programming proficiency in R

- Introductory or higher probability and statistics

Time commitment
Fall - Part Time
Compensation
Academic Credit
Number of openings
2
Techniques learned
  • Statistical modeling
  • Data imputation
  • R programming
Project start
Fall 2025
Contact Information:
Mentor
martonosi@hmc.edu
Professor of Mathematics
Name of project director or principal investigator
Prof. Susan Martonosi
Email address of project director or principal investigator
martonosi@g.hmc.edu
2 sp. | 0 appl.
Hours per week
Fall - Part Time
Project categories
Operations Research (+3)
MathematicsData ScienceOperations ResearchStatistical Modeling