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Title: Mathematical analysis of simple behavioral epidemic models
COVID-19 highlighted the importance of considering human behavior change when modeling disease dynamics. This led to developing various models that incorporate human behavior. Our objective is to contribute to an in-depth, mathematical examination of such models. Here, we consider a simple deterministic compartmental model with endogenous incorporation of human behavior (i.e., behavioral feedback) through transmission in a classic Susceptible–Exposed–Infectious–Recovered (SEIR) structure. Despite its simplicity, the SEIR structure with behavior (SEIRb) was shown to perform well in forecasting, especially compared to more complicated models. We contrast this model with an SEIR model that excludes endogenous incorporation of behavior. Both models assume permanent immunity to COVID-19, so we also consider a modification of the models which include waning immunity (SEIRS and SEIRSb). We perform equilibria, sensitivity, and identifiability analyses on all models and examine the fidelity of the models to replicate COVID-19 data across the United States. Endogenous incorporation of behavior significantly improves a model’s ability to produce realistic outbreaks. While the two endogenous models are similar with respect to identifiability and sensitivity, the SEIRSb model, with the more accurate assumption of the waning immunity, strengthens the initial SEIRb model by allowing for the existence of an endemic equilibrium, a realistic feature of COVID-19 dynamics. When fitting the model to data, we further consider the addition of simple seasonality affecting disease transmission to highlight the explanatory power of the models.  more » « less
Award ID(s):
2229819
PAR ID:
10536020
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Mathematical Biosciences
Date Published:
Journal Name:
Mathematical Biosciences
Volume:
375
Issue:
C
ISSN:
0025-5564
Page Range / eLocation ID:
109250
Subject(s) / Keyword(s):
Endogenous behavioral feedback Identifiability Human behavior Stability analysis Sensitivity analysis Early COVID-19 dynamics
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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