The author developed an individual-based simulator in which the user is allowed to set the parameter values and to examine what would go on in a virtual population of up to 1 million individuals. The parameters include the metrics for environment, mobility, pathogenesis, countermeasures, tests, vaccination, and virus variants. The simulator provides not only a graphical user interface and dynamic graphical monitoring functionalities but also a batch job management and a recording capability of a number of statistical indexes. Through some cases of simulation experiments based on the parameter settings targeting SARS-CoV-2, we observed that all of implemented measures are effective to suppress the spreads. The dynamics shows almost same figures to those known from SIR model when the population size is large. However, under some conditions of strong restriction in relatively small population, the end of epidemic comes early. This fact also means it takes long period until the cessation in big cities, even when a similar scale of restrictions to the country side is applied. Agent-based simulations have a capability to introduce a variety of features including geometrical population distribution, virus variants, and vaccination accompanying with graphical animation of people’s move. It has a potential to use against future epidemic of unknown pathogens.