Abstract
Due to modern transportation networks (airplanes, cruise ships, etc.) an epidemic in a given country or city may be triggered by the arrival of external infected agents. Posterior government quarantine policies are usually taken in order to control the epidemic growth. We formulate a minimal epidemic evolution model that takes into account these components. The previous and posterior evolutions to the quarantine policy are modeled in a separate way by considering different complexities parameters in each stage. Application of this model to COVID-19 data in different countries is implemented. Estimations of the infected peak time-occurrence and epidemic saturation values as well as possible post-quarantine scenarios are analyzed over the basis of the model, reported data, and the fraction of the population that adopts the quarantine policy.
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