Modeling COVID-19 Case Distribution Across Age Groups: Effects of Differential Susceptibility, Age-Specific Severity, and Heterogeneous Contacts

The transmission dynamics of COVID-19 within and between age groups is studied using a mathematical model with direct and indirect transmission pathways. The model captures infections arising from contact with environmental pathogens and from exposed individuals, with an adjustment parameter introduced to account for reduced infectiousness associated with absence of severe symptoms. Effects of three potential drivers: heterogeneous contacts, differential susceptibility, and age-specific variations in infection severity on the age distribution of cases is investigated. Results of the model analysis show that differential susceptibility is the leading driver of the pattern of case distribution compared to heterogeneous contact and age-specific severity. It is also shown that initiating interventions 20 days earlier prevents approximately three times as many cases as those averted by mitigation implemented after 30 days. When heterogeneous contact is combined with differential susceptibility, the model predicts that early mitigation substantially reduces cases among adults by more than half but has limited impact on individuals younger than 20 years.