目標：本研究探討世界各國COVID-19流行初期第一波疫情之每日新增確診人數趨勢型態及其相關背景因素。方法：本研究納入151個國家為研究對象，研究基準日為首次每日新增確診人數7天移動平均值≥100人，並自研究基準日起，對每一個國家觀察了60及90天。以時間序列階層群集分析（Time-series hierarchical clustering）將研究的國家進行趨勢型態分類，再以多項邏輯斯迴歸（Multinomial logistic regression）探討與此趨勢型態相關的背景因素。結果：COVID-19流行初期每日新增確診人數趨勢型態可歸類為「成長型」、「消退型」及「平緩消退型」三種。肥胖人口比例≥25.60%（勝算比=6.69，p值=0.004）相較於9.60-20.79%的國家更傾向「成長型」疫情趨勢型態。國內生產總值≥34,341美元（勝算比=0.10，p值=0.001）相較於5,277-14,932美元的國家更傾向於「消退型」疫情趨勢型態。結論：COVID-19防疫政策應參考如國家的肥胖人口比例與國內生產總值等特性差異來擬定。

Objectives: We analyzed global trends in the daily number of new cases during the first wave of COVID-19 and factors associated with these trends. Methods: Data from 151 countries were analyzed. The index date for each country was set with consideration for a 7-day moving average (MA7) of ≥100 people. Data were collected for 60 and 90 days from the index date. Time-series hierarchical clustering was used to analyze the trends in the number of new cases in each country on the basis of their MA7 values. Multinomial logistic regression was performed to identify factors associated with these trends. Results: The trends in the daily number of new cases in the early stage of COVID-19 were classified into growth, declines, and smooth declines. The number of cases in countries with ≥25.60% residents with obesity (odds ratio = 6.69; p = 0.004) was more likely to exhibit growth than were those with obesity of 9.60-20.79%. The number in countries with a GDP of ≥US$34,341 (odds ratio = 0.10; p = 0.001) was more likely to exhibit a decline than were those with a GDP of US$5,277–14,932. Conclusions: COVID-19 epidemic prevention policies should account for country-specific characteristics such as the proportion of residents with obesity and GDP.