  Contagious respiratory diseases, such as COVID-19, depend on sufficiently
prolonged exposures for the successful transmission of the underlying pathogen.
It is important for organizations to evaluate the efficacy of interventions
aiming at mitigating viral transmission among their personnel. We have
developed a operational risk assessment simulation framework that couples a
spatial agent-based model of movement with a SIR epidemiological model to
assess the relative risks of different intervention strategies. By applying our
model on MIT's STATA building, we assess the impacts of three possible
dimensions of intervention: one-way vs unrestricted movement, population size
allowed onsite, and frequency of leaving designated work location for breaks.
We find that there is no significant impact made by one-way movement
restrictions over unrestricted movement. Instead, we find that a combination of
lowering the number of individuals admitted below the current recommendations
and advising individuals to reduce the frequency at which they leave their
workstations lowers the likelihood of highly connected individuals within the
contact networks that emerge, which in turn lowers the overall risk of
infection. We discover three classes of possible interventions based on their
epidemiological effects. By assuming a direct relationship between data on
secondary attack rates and transmissibility in the SIR model, we compare
relative infection risk of four respiratory diseases, MERS, SARS, COVID-19, and
Measles, within the simulated area, and recommend appropriate intervention
guidelines.
