Date of Award
Summer 6-4-2023
Document Type
Thesis (Undergraduate)
Department
Quantitative Social Science
First Advisor
Olivia Chu
Abstract
In this paper, I build a data-driven theoretical model that reproduces the epidemiological (epi) curve of the mpox outbreak in the United States. The general framework presented in this paper considers the susceptible (S), infected (I), and recovered (R) stages of an mpox infection through an SIR model of disease spread. I use vaccination, transmissibility, recovery, and self isolation rates as parameters in my SIR model as well as a lag-time to account for the delay in vaccination roll-out. By using real-world data to inform estimates of the susceptible population and mpox transmission characteristics, I am able to simulate an epi curve that precisely mimics real-world pre-vaccination data and therefore postulate the number of individuals who were likely to be engaging in restrictive social-distancing or self-quarantine in mpox hot-beds California and New York, a previously unknown marker. I also simulate real-world disease dynamics over the entirety of the nine-month outbreak (with vaccination roll-out) with a +/- 20 case count accuracy. After replicating the 2022 mpox outbreak trajectory, I develop epidemic models to determine vaccination and self-isolation thresholds, ascertaining the level of intervention needed to quell an outbreak within the first month a case is detected and limit the number of infections to single digit case counts.
The results of my study demonstrate that an SIR model with a self-isolation variable can accurately predict mpox case counts for all three hot-spots before vaccinations were distributed, and an SIR model with self-isolation and vaccination with lag-time can accurately predict several peaks for all three hot-spots. The results also reveal critical thresholds of self-isolation and vaccination. Based on the match between real-world and simulated values, the outbreak simulations can be used as a predictive tool in future mpox outbreaks and further upgraded to incorporate a variety of underlying complex phenomena.
Recommended Citation
Scherzer, Amar Johanna, "Using Infectious Disease Simulations to Model, Quantify, and Predict the Impact of Self-Quarantine and Vaccination on Mpox Spread across the United States" (2023). Quantitative Social Science Undergraduate Senior Theses. 12.
https://digitalcommons.dartmouth.edu/qss_senior_theses/12
