MS08 - MEPI-06 Part 3 of 3

Recent Advances in Dynamics of Human Behavior and Epidemics (Part 3)

Friday, July 18 at 10:20am

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Note: this minisymposia has multiple sessions. The other sessions are: Part-1 and Part-2.

Abba Gumel (University of Maryland), Alex Safsten, Alice Oveson (both University of Maryland)

Description:

The recent COVID-19 pandemic has highlighted the critical role human behavior plays in the dynamics and control of infectious diseases. The behavior changes with respect to the adherence or lack thereof to public health intervention and mitigation measures during this pandemic were triggered by factors such as the unprecedented burden of the disease, the epidemic of disease-related mis(dis)information, fear, polarization, peer influence, poor quality and inconsistency in public health messaging, etc. Specifically, epidemiological models that do not explicitly account for these behavioral changes were seen to generally fail to capture the correct trajectory and burden of the pandemic (thereby not being able to make realistic or accurate forecasts). This minisymposium brings together an interdisciplinary team of researchers to discuss and share ideas on the recent advances in designing, validating, and analyzing mathematical models that explicitly incorporate human behavior and socio-economic factors, and use these models to contribute to public health policy for controlling and mitigating the spread and burden of the disease. Some of the topics to be addressed include metrics of human behavior changes, the role of heterogeneity in compliance to public health intervention and mitigation measures, the influence of social networks, the impact of mis(dis)information, and risk perception.

Jacques Bélair

Université de Montréal

"Knowledge as an Infection: Modeling Variable Compliance with Non-Pharmaceutical Interventions (NPIs)"

Management of the COVID-19 pandemic required, during its early stages, the deployment of non pharmaceutical interventions (NPIs) [social isolation, physical distancing, mask-wearing, hand-washing], and then, as they became available, administration of repeated doses of vaccine. We are interested in the consequences, for the dynamics of the disease, of variable adherence to these measures, and the motivation generating the lack thereof. We present two modeling approaches to represent this evolution of behaviour. First, a basic SEIRS model is expanded by introducing a structure in the infectious class, to reflect the variable severity of symptoms and the presence of asymptomatic cases considering the population divided into two classes according to their degree of adherence to the NPIs. Then, from a different perspective, we focus on the health literacy level in a population and the consequences, for the disease dynamics, of both knowledge dissemination and its integration in behaviour.

Asa Rishel

University of Maryland

"Mind Over Matter: Balancing the Benefits of COVID Lockdowns with Their Cost on Mental Health"

The COVID-19 pandemic took its toll not only on the physical health of those who lived through it, but also on their mental health. I will present a model of the direct and indirect effects of COVID-19 and the associated public policies on mental health. This is an SIRS model of COVID-19, with compartments for mild, acute, and chronic COVID-19 infections and additional compartments for populations with mental health symptoms. Parameters are determined based on fitting from the first wave of COVID-19 in the New York state population, which includes several changes in local government policy, e.g, lockdown orders, which have an effect on the rate at which mental health systems develop. Finally, an additional “delay” term is included in the model to account for the delay between lockdowns going into effect and individuals developing mental health symptoms. The goal of our analysis is to understand how government policy in response to a pandemic can seek to maximize the population's quality-adjusted life years (QALY), which is a measure not only of lifespan, but also the quality of the years lived. I will present some preliminary results suggesting the optimal timing and strength of government lockdown mandates.

Bryce Morsky

Florida State University

"Social Dynamics, Information Spread, and Behavioral Responses in Epidemic Modeling"

Social dynamics and the spread of information are critical factors in the spread of disease, influencing contact rates, behavior, and beliefs. This talk presents behavioral-epidemiological models featuring tipping-point dynamics for the uptake of vaccines or non-pharmaceutical interventions (NPIs), driven by real and perceived infection risks and social norms. These dynamics create collective action problems, leading to cycles of protective behavior and infections, with nonlinear responses to epidemiological parameters. The role of information dissemination is explored, particularly the roles of broadly shared information along with information bubbles.

Claus Kadelka

Iowa State University

"Adaptive Human Behavior and Delays in Information Availability Autonomously Modulate Epidemic Waves"

The recurrence of epidemic waves has been a hallmark of infectious disease outbreaks. Repeated surges in infections pose significant challenges to public health systems, yet the mechanisms that drive these waves remain insufficiently understood. Most prior models attribute epidemic waves to exogenous factors, such as transmission seasonality, viral mutations, or implementation of public health interventions. We show that epidemic waves can emerge autonomously from the feedback loop between infection dynamics and human behavior. Our results are based on a behavioral framework in which individuals continuously adjust their level of risk mitigation subject to their perceived risk of infection, which depends on information availability and disease severity. We show that delayed behavioral responses alone can lead to the emergence of multiple epidemic waves. The magnitude and frequency of these waves depend on the interplay between behavioral factors (delay, severity, and sensitivity of responses) and disease factors (transmission and recovery rates). Notably, if the response is either too prompt or excessively delayed, multiple waves cannot emerge. Our results further align with previous observations that adaptive human behavior can produce non-monotonic final epidemic sizes, shaped by the trade-offs between various biological and behavioral factors – namely, risk sensitivity, response stringency, and disease generation time. Interestingly, we found that the minimal final epidemic size occurs on regimes that exhibit a few damped oscillations. Altogether, our results emphasize the importance of integrating social and operational factors into infectious disease models, in order to capture the joint evolution of adaptive behavioral responses and epidemic dynamics.

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Annual Meeting for the Society for Mathematical Biology, 2025.