The discrete-time Kermack-McKendrick model: A versatile and computationally attractive framework for modeling epidemics.

ABSTRACT: The COVID-19 pandemic has led to numerous mathematical models for the spread of infection, the majority of which are large compartmental models that implicitly constrain the generation-time distribution. On the other hand, the continuous-time Kermack-McKendrick epidemic model of 1927 (KM27) allows an arbitrary generation-time distribution, but it suffers from the drawback that its numerical implementation is rather cumbersome. Here, we introduce a discrete-time version of KM27 that is as general and flexible, and yet is very easy to implement computationally. Thus, it promises to become a very powerful tool for exploring control scenarios for specific infectious diseases such as COVID-19. To demonstrate this potential, we investigate numerically how the incidence-peak size depends on model

SUBMITTER: Diekmann O 

PROVIDER: S-EPMC8488666 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature