Bagger, Niels-Christian Fink

Hoogervorst, Rowan

Pisinger, David

van der Hurk, Evelien

One of the most efficient tools for limiting the disease spread during a pandemic is to limit the contacts between people. However, too strict restrictions may seriously affect the economy, health, education, and well-being of people. Hence, we will study in this talk the use of individualized strategies instead of uniform restrictions for the organisation of activities that include close contacts. Concretely, we will look at how to schedule a set of activities where the participants meet, and hence can spread infection. Those could be classroom teaching, sports activities, work shifts, etc. Formulating the contacts resulting from the assignment of participants to scheduled activities as a graph, we propose to search for graph structures that limit the disease spread. We develop a mathematical algorithm for identifying such favourable graphs by limiting the distinct contacts the individuals meet during an activity. The quality of a contact graph is evaluated using an agentbased model where individual disease progress is defined according to the so-called SEIR (Susceptible, Exposed, Infectious or Removed) model. We will explore the ability of this algorithm to limit the spread of a disease under several realistic setups by means of a computational study targeted towards the re-opening of physical lecturing at a major university, using real-life data from a course database

Reducing disease spread through optimization: Limiting mixture of the population is more important than limiting group sizes

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