目標：新冠肺炎的介入措施可分為針對個人層面的個案型介入（如接觸者回溯或檢疫）與針對大眾的群體型介入（如口罩與疫苗），隨疫情流感化趨勢與疫苗施打，防疫目標從清零轉為降低中重症個案對醫療的衝擊，故本研究欲探討不同介入措施對於中重症住院人數的影響。方法：本研究使用Hellewell等人於2020年開發出的分枝模型（branching model）進行模擬，搭配Omicron變種病毒的流行病學資料與不同假設情境，並計算不同介入措施組合下的每日住院人數作為評價依據。結果：本研究發現群體型介入比個案型介入有效，但在較高強度的群體型介入下加入個案型介入，會有較佳的效果，而若疫苗能有效降低染疫後住院率，應優先提高疫苗覆蓋率而非追求疫苗避免感染有效性，以減緩對醫療量能的衝擊。結論：在鬆綁個案型介入的過程中，需考量是否已有一定群體型介入的支持，同時若希望能控制中重症與住院人數，須提高疫苗覆蓋率而不是以追求疫苗避免感染有效性為優先事項。

Objectives: Interventions for controlling COVID-19 can be classified into case-based (e.g., contact tracing and quarantining) and population-based (e.g., using masks and receiving vaccines) measures. The objective of pandemic control has now shifted from reducing the daily number of cases to reducing that of hospitalizations through vaccination. COVID-19 has started exhibiting flu-like characteristics. Therefore, in this study, we compared different measures in terms of their effectiveness in reducing the daily number of moderate to severe cases of COVID-19. Methods: The branching model developed by Hellewell (2020) was used for simulation. The epidemiological data of the Omicron variant and various hypothetical scenarios were analyzed. The outcome variable of our study was the daily number of hospitalizations under different measures and their combinations. Results: Population-based measures were more effective than case-based measures; however, their combination led to the best outcomes. If vaccination reduced the number of COVID-19-related hospitalizations, the focus was on increasing vaccine coverage to increase medical capacity rather than enhancing vaccine efficacy. Conclusions: While loosening case-based measures, the government must consider whether population-based measures can support this change. Furthermore, to reduce the daily number of moderate to severe cases of COVID-19, vaccine coverage, rather than vaccine efficacy, must be improved.