 |
Center for Nonlinear Studies |
The influenza virus is classified as a major public health issue by the World Health Organization (WHO) and Centers for Disease Control (CDC). We created ordinary differential equation models with parameter estimates based on the whining host viral load profile to determine various disease stages and parameters associated with infectiousness, disease progression, and behavior change due to the symptoms. Additionally, we incorporate the effect of a waning and an imperfect vaccine on delaying the time and decreasing the size of an epidemic peak. Many individuals are vaccinated annually in the hopes of avoiding the influenza virus. However, some of these individuals are unaware that the vaccine efficacy is never 100% and that protection is acquired approximately two weeks following immunization. Understanding the effects of this misconception and connecting it to behavior change allows for improved predictions of an influenza epidemic. We took various parameter scenarios to numerically study thresholds associated with vaccine effectiveness and behavior change. Our model also showed that incorporating behavior change in addition to vaccination also significantly lowers and delays the epidemiological peak giving more time to develop control and prevention strategies. These studies further predict that behavior change is still necessary during an influenza outbreak even when a given individual is vaccinated.
Host: Sara Del Valle