自2019年12月首次被發現以來 COVID-19 已經席捲各個國家，因其高度傳染性使得各國難以預防，當相關機構要執行防疫措施時，其執行的時間點需要更多資訊進行評估。COVID-19 主要透過飛沫傳染，因此本研究將人口流動視為其中的關鍵影響，但是增加傳染的風險並不局限於人口流動一種
。空氣汙染物也被認為與呼吸道相關疾病有著高度的相關性，先前研究也使用空氣品質以預測流感病毒爆發時間，此外研究也觀察到人口流動與空氣汙染物間存在一定的相關性，像是因為開車而造成 NO2 以及 PM2.5 的增加等。
本研究所選擇的影響因素可以觀察到相關機構的防疫措施對於這些因素的影響性，例如是否強制規定戴口罩、居家令的執行以及重新開放等相關防疫措施。戴口罩可以減少飛沫傳染的風險也較能減少空氣汙染物的影響，而居家令則是會減少人口的流動也減少人與外面空氣的接觸，重新開放則是使得人口流動恢復也增加空氣污染物。因此本研究希望能透過所提出的影響因素來協助評估目前疫情爆發的風險並做為防疫措施的一參考數值。
本研究使用美國加利福尼亞州、佛羅里達州、紐澤西州以及紐約州的人口流動、室外空氣汙染物及疫苗接種預測COVID-19 確診人數及活動病例，並以排隊理論預測其平均所需康復時間，將預測結果帶入的風險分析。最終以斜率來進行風險分析，獲取爆發閥值，預測可能存在的高風險時段，將這些時段與防疫措施結合，提供相關機構一個評估防疫措施的參考數據，期望達到對疫情有更好的控制。

COVID-19 has swept all countries since it was first discovered in December, 2019. The high infectivity of COVID-19 makes it more difficult to prevent it, and air quality has been considered to be highly correlated with respiratory diseases. Previous study shown that air quality has been used for influenza viruses outbreak time prediction, but air is not the only one that increases the risk of infection. Population movement is also one of the key influences. We have observed that population movement is also correlated with air pollutions. In addition, the study also observed a certain correlation between population movement and air pollutants, such as the increase in NO2 and PM2.5 caused by driving.
In addition, the government's epidemic prevention strategies are also one of the factors that affect the risk of infection, such as whether it is mandatory to wear masks or household orders, etc. Wearing masks can reduce the risk of droplet infection and the impact of air pollution, while household orders can reduce the mobility of the population and the contact between people and the outside air.
In this study, the number of COVID-19 cases and active cases will be predicted according to population flow, outdoor air pollutions and vaccination in California, Florida, New Jersey and New York, and the average recovery time will be predicted by queuing theory, and the predicted results will be brought into risk analysis. Finally, the slope is used to analyze the risk, predict the possible high-risk time periods, and combine these time periods with the epidemic prevention measures to provide a reference data for relevant institutions to evaluate the epidemic prevention measures, hoping to achieve better control of the epidemic situation.

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