Minimal epidemic model considering external infected injection and governmental quarantine policies: Application to COVID-19 pandemic

TL;DR

This paper introduces a minimal epidemic model that incorporates external infection sources and government quarantine policies, applied to COVID-19 data to analyze epidemic peaks and post-quarantine scenarios.

Contribution

It presents a novel minimal model distinguishing pre- and post-quarantine dynamics with different complexities, tailored for COVID-19 data analysis.

Findings

Estimated peak infection times for different countries.

Analyzed effects of quarantine adoption rates on epidemic saturation.

Explored post-quarantine epidemic scenarios.

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.