Prospective Prediction of Future SARS-CoV-2 Infections Using Empirical Data on a National Level to Gauge Response Effectiveness

Understand

Predicting an accurate expected number of future COVID-19 cases is essential to properly evaluate the effectiveness of any treatment or preventive measure.

• This study aimed to identify the most appropriate mathematical model to prospectively predict the expected number of cases without any intervention.
• The total number of cases for the COVID-19 epidemic in 28 countries was analyzed and fitted to several simple rate models including the logistic, Gompertz, quadratic, simple square, and simple exponential growth models.
• The resulting model parameters were used to extrapolate predictions for more recent data.