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Title: Coupling compartmental models with Markov chains and measure evolution equations to capture virus mutability
The COVID-19 pandemic lit a fire under researchers who have subsequently raced to build models which capture various physical aspects of both the biology of the virus and its mobility throughout the human population. These models could include characteristics such as different genders, ages, frequency of interactions, mutation of virus, etc. Here, we propose two mathematical formulations to include virus mutation dynamics. The first uses a compartmental epidemiological model coupled with a discrete-time finite-state Markov chain. If one includes a nonlinear dependence of the transition matrix on current infected, the model is able to reproduce pandemic waves due to different variants. The second approach expands such an idea to a continuous state-space leveraging a combination of ordinary differential equations with an evolution equation for measure. This approach allows to include reinfections with partial immunity with respect to variants genetically similar to that of first infection.  more » « less
Award ID(s):
2033580
PAR ID:
10437523
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Mathematical Models and Methods in Applied Sciences
Volume:
32
Issue:
10
ISSN:
0218-2025
Page Range / eLocation ID:
2099 to 2119
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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