Modelling the Cumulative Number of COVID-19 Cases

Each country has its own characteristics of COVID-19 infection trajectory and epidemic waves. Differences in government-implemented restrictions social regulations result variability the virus transmissions spread dynamics. This turn results various shapes growth function used to represent describe propagation infection. Statistical methods are applied fit non-linear functions daily time-series data cumulative numbers cases. The aim this work is statistical models number Also overview types existed numerical methodologies. (since December 31, 2019) available for almost each world. As examples, we cases Poland, Italy, Canada, USA. Non-linear approximations these time series data. fitted allow us investigate dynamics pandemic. constructed compositions a few nonlinear functions, which process trajectories. Two Gompertz distribution (cdf) were estimated Poland Italy (using cdf normal distribution) Canada USA gamma distribution). An analytical (parametric) representation useful tool study epidemics.