  A pandemic, the worldwide spread of a disease, can threaten human beings from
the social as well as biological perspectives and paralyze existing living
habits. To stave off the more devastating disaster and return to a normal life,
people make tremendous efforts at multiscale levels from individual to
worldwide: paying attention to hand hygiene, developing social policies such as
wearing masks, social distancing, quarantine, and inventing vaccines and
remedy. Regarding the current severe pandemic, namely the coronavirus disease
2019, we explore the spreading-suppression effect when adopting the
aforementioned efforts. Especially the quarantine and vaccination are
considered since they are representative primary treatments for block spreading
and prevention at the government level. We establish a compartment model
consisting of susceptible (S), vaccination (V), exposed (E), infected (I),
quarantined (Q), and recovered (R) compartments, called SVEIQR model. We look
into the infected cases in Seoul and consider three kinds of vaccines, Pfizer,
Moderna, and AstraZeneca. The values of the relevant parameters are obtained
from empirical data from Seoul and clinical data for vaccines and estimated by
Bayesian inference. After confirming that our SVEIQR model is plausible, we
test the various scenarios by adjusting the associated parameters with the
quarantine and vaccination policies around the current values. The quantitative
result obtained from our model could suggest a guideline for policy making on
effective vaccination and social policies.
