Coronaviruses are one of the most dangerous forms of viruses. The development of the COVID-19 pandemic takes the form of a potential threat to all of humanity. This is due to the fact that coronaviruses have high pathogenicity, the ability to overcome human immunity. There are also difficulties in treating diseases that are associated with coronavirus. To solve such issues, it is important to obtain reliable statistical data, as well as conduct a comprehensive analysis of the data that are currently received. Based on this, the paper considers the possibility of analyzing data on the development of the COVID-19 pandemic based on wavelet analysis approaches. The wavelet coherence method was used as the main approach for statistical data analysis. The consistency of the results for different countries of the Persian Gulf is shown. Based on the analysis of the depth of cross-references between the studied data series, the most significant time periods were obtained until patients recover or die. Some explanation is given for the patterns that arise for individual Gulf countries. The data obtained can be used in the fight against the pandemic COVID-19, understanding the dynamics of its development.