A STATISTICAL ANALYSIS OF THE COVID-19 OUTBREAK DATA

Abstract

The exponential model is a commonly used epidemic model for the analysis of initial outbreak data due to an infectious disease. But there have been questions about its validity in practice. This article examines this issue through statistical analysis on 22 countries’ initial COVID-19 outbreak data provided by the World Health Organization. For each of 22 countries, a general regression analysis is conducted  for the cumulative confirmed cases. Our regression function is a 3-5 piecewise fitted functions which are obtained via regression analysis, data transformation and careful detection of change-points. The detection of change-points is conducted by the combination of residual analysis and r² values, and we introduce the concept of overall R² value to assess the goodness of fit for the fitted curves. Among the 22 countries considered in our analysis, 77.3% and 22.7% of these countries had fitted exponential curve and logistic curve, respectively, during the initial period. The average length of the fitted exponential curves is 31 days, and the average length of the fitted logistic curves is 39 days. Regionally, we have similar results. In conclusion, our data analysis in this article suggests that the usual epidemic exponential model assumption does not always hold in practice.

Received: February 5, 2023 
Accepted: March 15, 2023