The use of the dynamic time warping (DTW) method to describe the COVID-19 dynamics in Poland

Research background: In recent times, the whole world has been severely affected by COVID-19 pandemic. The influence of epidemic on society and economy caused a great deal scientific interest. development pandemic in many countries was analyzed using various models. However, literature dissemination lacks econometric analyzes this Polish voivodeships.
 Purpose article: aim study is to find similarities time series for infected with those who died voivodeships method dynamic warping.
 Methods: warping allows calculate distance between two different lengths. This feature very important our analysis because coronavirus did not start all at same time. also enables an adjustment timeline similar, but shifted, phases. Using method, we jointly analyze number deceased people each province. next step, based measured similarity series, are grouped hierarchically.
 Findings & value added: We use identify groups extent. classification performed may be useful as it indicates patterns disease evolution voivodeships. results obtained regional level will allow better prediction future infections. Decision makers should formulate further recommendations lockdowns local level, long run, adjust medical infrastructure regions accordingly. Policymakers other can benefit from findings shaping their own policies