title: Public avoidance and epidemics: insights from an economic model.
abstract: In this paper, we present a mathematical model of infectious disease transmission in which people can engage in public avoidance behavior to minimize the likelihood of acquiring an infection. The framework employs the economist's theory of utility maximization to model people's decision regarding their level of public avoidance. We derive the reproductive number of a disease which determines whether an endemic equilibrium exists or not. We show that when the contact function exhibits saturation, an endemic equilibrium must be unique. Otherwise, multiple endemic equilibria that differ in disease prevalence can coexist, and which one the population gets to depends on initial conditions. Even when a unique endemic equilibrium exists, people's preferences and the initial conditions may determine whether the disease will eventually die out or become endemic. Public health policies that increase the recovery rate or encourage self-quarantine by infected people can be beneficial to the community by lowering disease prevalence. However, it is also possible for these policies to worsen the situation and cause prevalence to rise since these measures give people less incentive to engage in public avoidance behavior. We also show that implementing policies that result in a higher level of public avoidance behavior in equilibrium does not necessarily lower prevalence and can result in more infections.
authors.affiliation: Department of Economics, Wake Forest University, Box 7505, Wake Forest University, Winston-Salem, NC 27109, USA. chenfh@wfu.edu
authors.forename: Frederick
authors.initials: F
authors.lastname: Chen
authors.forename: Miaohua
authors.initials: M
authors.lastname: Jiang
authors.forename: Scott
authors.initials: S
authors.lastname: Rabidoux
authors.forename: Stephen
authors.initials: S
authors.lastname: Robinson
mesh_terms: D003140:Communicable Disease Control; D058872:Epidemics / Q000517:prevention & control*; D006801:Humans; D008954:Models, Biological; D018803:Models, Economic; D015995:Prevalence; D011640:Public Policy; D013997:Time Factors