The Mechanism and Phenomena of Adaptive Human Behavior During an Epidemic and the Role of Information

Eli P. Fenichel () and Xiaoxia Wang ()
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Eli P. Fenichel: Yale University, School of Forestry and Environmental Studies
Xiaoxia Wang: Arizona State University, Mathematical, Computational and Modeling Sciences Center

A chapter in Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases, 2013, pp 153-168 from Springer

Abstract: Abstract Disease transmission can be described phenomenologically at the population level or mechanistically as the aggregate result of individual behaviors. To explain why epidemics evolve as they do in response to information, a mechanistic approach is required. However, taking a mechanistic approach reveals that information can be parsed in terms of forecasting models or the approach to forming expectations, timeliness or quality of information, and information processing and how the information is used to make trade-offs. We develop a mechanistic model that uses microeconomic theory to describe adaptive or strategic human behavior. We show that phenomenological forecasting models and forecasting models based on classical epidemiological theory guide human behavior towards similar biological results, but different social well-being results. Moreover, we find that assumptions about information processing method, i.e., the utility function of individuals, may have a substantial influence on an epidemic.

Keywords: Forecast Model; Rational Expectation; Disease Dynamic; Dynamic Optimization Problem; Peak Prevalence (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-5474-8_10

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DOI: 10.1007/978-1-4614-5474-8_10

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