Abstract
This paper generalizes the standard epidemiological SEIR model of the spread of diseases such as COVID-19 in two respects. First, it considers the structure of the infectious population in more detail and introduces the concept of the "cohort composition kernel" that generalizes the aggregate transmission function. Second, it shows how policy measures such as testing and quarantine rules can affect this kernel and how this can provide estimates for the impact and lag of non-pharmaceutical policy interventions. On the technical side, the paper shows how to dispense with the standard assumption of exponential transition dynamics and to work with general transition processes by using the convolution of densities.
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