Using mean field game theory for epidemic modeling and control

We are exploring the use of the mean field game theory to epidemic modelling. The motivation for this is provided by the Covid 19 pandemic which has devastated the world like no other pandemic ever before. Mean field games have a natural appeal because of the need to model population scale effects of pandemics.

In particular, we are interested in controlling the  spread of the epidemic in a population where the individuals exercise control their contact factor and vaccinations are conducted to mitigate the disease spread in the population. We compare the socially optimal control strategy with an individually optimal strategy. To arrive at a social optimum, tools from optimal control are used and to model the individual decision making, a mean field approach is used where individuals observe the current state of the epidemic and choose their contact factor.

Our team consists of:

  • Y. Narahari
  • Chandramani Singh, Electronic Systems Engineering
  • Amalroy (Ph.D. Student)
  • Soumyarup Sadhukhan (C.V. Raman Postdoc)
  • Pranoy Das (M.Sc. (Research) Student – Biology), IISc