  The 2019 Novel Corona virus infection (COVID 19) is an ongoing public health
emergency of international focus. Significant gaps persist in our knowledge of
COVID 19 epidemiology, transmission dynamics, investigation tools and
management, despite (or possibly because of) the fact that the outbreak is an
unprecedented global threat. On the positive side, enough is currently known
about the epidemic process to permit the construction of mathematical
predictive models. In our work, we adapt a traditional SEIR epidemic model to
the specific dynamic compartments and epidemic parameters of COVID 19, as it
spreads in an age-heterogeneous community. We analyze management strategies of
the epidemic course (as they were implemented through lockdown and reopening
procedures in many of the US states and countries worldwide); however, to more
clearly illustrate ideas, we focus on the example of a small scale college town
community, with the timeline of control measures introduced in the state of New
York. We generate predictions, and assess the efficiency of these control
measures (closures, mobility restrictions, social distancing), in a
sustainability context.
