Abstract： Objective： To retrospectively analyze the medication rule of the first Chinese medicine prescription of patients with corona virus disease 2019 (COVID-19) in The Second Affiliated Hospital of Zhejiang Chinese Medical University， in order to provide reference for the treatment of COVID-19 with traditional Chinese medicine. Methods： The first prescriptions of patients who were hospitalized in The Second Affiliated Hospital of Zhejiang Chinese Medical University from December 2022 to January 2023 and were diagnosed with COVID-19 were collected to build a database； the frequency of Chinese medicine usage，natures and flavors，meridian tropism，and efficacy categories were summarized；high-frequency medicine association rules and complex network analysis were conducted. Results：A total of 168 prescriptions were collected，involving 159 Chinese medicinals，with a cumulative frequency of 2 332 uses and 23 highfrequency medicinals，which were used ≥30 times. The top 10 Chinese medicine were Platycodonis Radix， Armeniacae Semen Amarum， Pinelliae Rhizoma， Phragmitis Rhizoma， Glycyrrhizae Radix et Rhizoma， Coicis Semen，Scutellariae Radix，Fritillariae Thunbergii Bulbus，Glycyrrhizae Radix et Rhizoma Praeparata cum Melle，Ophiopogonis Radix，with the highest frequency of use were mainly effective in clearing heat， resolving phlegm， relieving cough， and boosting qi and nourishing yin； the nature was mainly cold and cool，and the flavors were mainly sweet，bitter，and acrid；the meridian tropism were mainly related to the lung meridian，followed by the spleen and stomach meridians. Association rules analysis showed that the Chinese medicinals with highest frequency were Platycodonis Radix， Coicis Semen， Armeniacae Semen Amarum. Conclusion：Among the first Chinese medicine prescriptions of COVID-19，most of the patients are treated with Chinese medicine of clearing heat，resolving phlegm，and relieving cough，and those of boosting qi and nourishing yin. The study could provide the reference for the medication of COVID- 19 through association rules and complex network analysis.