A classification of countries and regions by degree of the spread of coronavirus based on statistical criteria

Abstract

This paper presents models of the spread of SARS-CoV-2 coronavirus in individual countries and globally in 2020 based on the statistical characteristics of the spread in the given countries or regions (in particular, in Hubei province). Through modeling, we attempt to achieve a goal which is of vital interest to societies in a pandemic catastrophe, and to answer the question of what stage of spread the epidemic has reached in a given country. The country classifier we developed is based on the relative variability indicator of the confirmed cases variable. This classification indicator is compared with a set of data-driven thresholds, the crossing of which determines the degree of spread of the epidemic in a given country. The article was written between April 2020, when the pandemic had been suppressed in China and was raging in Europe and the USA, and August 2020, as a new wave of local resumed outbreaks appeared in many countries. We contend that the spread phases are predictable based on statistical similarity. There are four phases of epidemic spread: growth, duration, suppression and re-outbreak. The authors’ Matlab software, which allows simulations of the spread of coronavirus in any country based on data published by CSSE, is available in the public GitHub repository.