Parametric analysis of early data on COVID-19 expansion in selected European countries

Martin Spousta

Approximation (3) is a pure exponential distribution which we shall observe if no human measures are taken to control the spread of the disease and no immunization of the population is assumed. Approximation (4) is modified exponential expansion where parameter b 2 , if negative, characterizes the "pushback" resulting from human measures to control the disease. Approximation (5) allows to control the validity of |b i | > |b i+1 | assumption and a need for the higher order terms to model the spread of the disease. Data can be fitted by (3), (4), and (5). The quality of the fits then decides which of the approximation serves as the best description of the data. When fitting the data over the full available time range from three representative European countries, namely Italy, France, and Czechia, we found that indeed |b 1 | |b 2 | |b 3 | and that approximation (5) has slightly worse χ 2 /NDOF than approximation (4) (typically by 10%). We may therefore conclude that approximation (5) and higher order terms are not needed for parameterizing the data.