  Intercity travel is one of the most important parameters for combating a
pandemic. The ongoing COVID-19 pandemic has resulted in different computational
studies involving intercity connections. In this study, the effects of
intercity connections during an epidemic such as COVID-19 are evaluated using a
new network model. This model considers the actual geographic neighborhood and
population density data. This new model is applied to actual Turkish data by
the means of provincial connections and populations. A Monte Carlo algorithm
with a hybrid lattice model is applied to a lattice with 8,802 data points.
Results show that this model is quantitatively very efficient in modeling real
world COVID-19 epidemic data based on populations and geographical intercity
connections, by the means of estimating the number of deaths, disease spread,
and epidemic termination.
