  The evacuation of the population from flood-affected regions is a
non-structural measure to mitigate flood hazards. Shelters used for this
purpose usually accommodate a large number of flood evacuees for a temporary
period. Floods during pandemic result in a compound hazard. Evacuations under
such situations are difficult to plan as social distancing is nearly impossible
in the highly crowded shelters. This results in a multi-objective problem with
conflicting objectives of maximizing the number of evacuees from flood-prone
regions and minimizing the number of infections at the end of the shelter's
stay. To the best of our knowledge, such a problem is yet to be explored in
literature. Here we develop a simulation-optimization framework, where multiple
objectives are handled with a max-min approach. The simulation model consists
of an extended Susceptible Exposed Infectious Recovered Susceptible (SEIRS)
model.We apply the proposed model to the flood-prone Jagatsinghpur district in
the state of Odisha, India. We find that the proposed approach can provide an
estimate of people required to be evacuated from individual flood-prone
villages to reduce flood hazards during the pandemic. At the same time, this
does not result in an uncontrolled number of new infections. The proposed
approach can generalize to different regions and can provide a framework to
stakeholders to manage conflicting objectives in disaster management planning
and to handle compound hazards.
