A Simple, Non-Recursive Model of the Spread of COVID-19 with Applications to Policy

The paper presents early research on problems that make an application of the basic SIR-model of epidemiology difficult for short- and medium-run policy. The model essentially generalizes the simple SIR model in two respects. First, it generalizes the relation n_t = βY_t to account for the structure of the infectious population and introduces the concept of the "cohort composition kernel" that generalizes the aggregate transmission function and renders the transmission model non-recursive. Second, it shows how policy measures such as testing, social distancing, or quarantine rules can affect this kernel and how this can provide estimates for the impact and lag of non-pharmaceutical policy interventions