| Summary: | Influenza remains one of the major infectious diseases that targets humankind. Understanding within-host dynamics of the virus and how it translates into the spread of the disease at a population level can help us obtain more accurate disease outbreak predictions. We created an ordinary differential equation model with parameter estimates based on the disease symptoms score data to determine various disease stages and parameters associated with infectiousness and disease progression. Having various stages with different intensities of symptoms enables us to incorporate spontaneous behavior change due to the onset/offset of disease symptoms. Additionally, we incorporate the effect of a waning vaccine on delaying the time and decreasing the size of an epidemic peak. Our results showed that the epidemic peak in the model was significantly lowered when public vaccination was performed up to two months past the onset of an epidemic. Also, behavior change in the earliest stages of the epidemic lowers and delays the epidemic peak. This study further provides information on the potential impact of pharmaceutical and non-pharmaceutical interventions during an influenza epidemic.
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