A mathematical model to distinguish sociological and biological susceptibility factors in disease transmission in the context of H1N1/09 influenza.

The pandemic H1N1/09 influenza virus differs from seasonal influenza in its greater prevalence among younger individuals. It is well known that younger individuals interact with one another and society as a whole more than older individuals, suggesting that this could account for the skewed prevalence. However, the observed skewed disease prevalence could also be due to a lesser biological vulnerability (cross-immunity or partial immunity) in the older generation. We develop an age-structured, compartmental mathematical model to quantify the degree to which the skewed disease prevalence among younger individuals is due to a lesser biological vulnerability in the older generation. The model incorporates synthetic data regarding sociological interaction between different age groups generated from the simulation software EpiSims, which allows a clear distinction of the sociological and biological susceptibility effects on the transmission rate of the disease. After fitting the model to available data, we quantify the degree of biological susceptibility of five age groups in the population of the United States. Our model indicates that individuals over the age of 60 are 1/15 as susceptible to H1N1/09 influenza as those under 30 years of age. The key feature in the model is separating social contact factors of disease transmission from biological ones.