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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90836
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DC 欄位值語言
dc.contributor.advisor詹長權zh_TW
dc.contributor.advisorChang-Chuan Chanen
dc.contributor.author張裕翔zh_TW
dc.contributor.authorYu-Hsiang Changen
dc.date.accessioned2023-10-03T17:50:22Z-
dc.date.available2025-12-31-
dc.date.copyright2023-10-03-
dc.date.issued2023-
dc.date.submitted2023-06-27-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90836-
dc.description.abstract背景:自 2020 年 1 月新冠肺炎 (Covid-19) 大流行以來新冠病毒 (SARS-CoV-2) 透過空氣傳播對全球各地的各個行業都產生影響,是大流行期間一項重要的職業衛生問題,其中特別是照顧新冠肺炎患者的第一線醫護人員感染新冠病毒的風險最受到重視,因此了解醫護在其工作場所暴露到新冠病毒的風險有其重要性。本研究在臺北市某醫學中心以空氣採樣評估該醫院內收治新冠肺炎患者病房外的護理站和走廊暴露新冠病毒的風險,並將監測結果和通風、污水採樣及疫情資料結合以分析期間的關係。
材料與方法:本研究在新冠病毒Omicron變異株流行期間的 2022 年 3 月 10 日至 2022 年 11 月 9 日於臺北市某醫學中心甲院區防疫專責病房進行環境監測。環境監測分成空氣監測與污水監測:空氣監測於防疫專責病房內護理站、走廊架設EAQ-T17室內空氣品質感測器進行 24 小時監測,並使用兩階段旋風分離TE-BC251生物氣膠採樣器來採集空氣,空氣粒徑樣本分成大於 4 μm、 1-4 μm、小於 1 μm,採樣頻率為每周一次。污水監測於防疫專責病房之污水匯流井中收集未經處理的污水,採樣頻率為每周一次。空氣與污水樣本進行核酸萃取並以即時定量聚合酶連鎖反應分析技術 (Real-time qPCR) 分析新冠病毒核酸,空氣樣本中每個粒徑樣本的陽性定義為循環數閥值 (CT value) 小於 38 ,我們將每次採樣的三個粒徑中任何一個粒徑空氣樣本是陽性時定義為該次空氣採樣為陽性。而污水樣本陽性定義為循環數閥值小於 40 。我們將空氣採樣的新冠病毒檢測資料連結室內二氧化碳濃度資料來研究空氣樣本陽性率與室內二氧化碳濃度之間的關聯性,並運用廢水監測資料連結醫學中心門診及住院新冠肺炎確診患者人數資料與中正區、臺北市及大臺北地區確診人數及死亡人數資料,來建構環境監測資料預測疫情確診人數與死亡人數的統計模型。
結果:在研究的八個月的期間內臺北市新冠肺炎確診病例數範圍介於 25 至 10872 例,死亡病例數範圍介於 0 至 30 例;中正區新冠肺炎確診病例數範圍介於 1 至 588 例,死亡病例數範圍介於 0 至 8 例;醫學中心新冠肺炎門診及住院確診病例總數介於 3 至 341 例。我們發現在 3 月 31 日至 11 月 9 日的研究期間護理站的 93 個空氣監測樣本中病毒核酸陽性率為 38 %,走廊的 342 個空氣監測樣本中病毒核酸陽性率為 40 %。護理站與走廊和空氣採樣同時間內的室內二氧化碳濃度範圍介於 400 至 770 ppm,顯示該區域二氧化碳濃度均低於美國疾病管制與預防中心於疫情期間所訂定的室內二氧化碳濃度建議值 800 ppm。我們也發現在 3 月 10 日至 10 月 25 日的研究期間,在 49 個污水監測樣本中病毒核酸陽性率為 100 %,污水病毒核酸濃度範圍介於 28 至 2,800 copies/L之間,相對訊號範圍介於 0.001 至 0.047 之間。
本研究發現空氣樣本核酸陽性率與室內二氧化碳濃度之間存在關聯性。護理站的空氣樣本核酸陽性率在室內二氧化碳濃度大於 582 ppm時顯著高於室內二氧化碳濃度低於 582 ppm時之空氣樣本核酸陽性率;在走廊空氣樣本核酸陽性率在室內二氧化碳濃度大於 447 ppm時顯著高於室內二氧化碳濃度低於 447 ppm時之空氣樣本核酸陽性率。本研究同時發現空氣檢測結果與污水檢測結果之間存在時序性關係,前一週污水病毒核酸濃度為高濃度組別時,空氣樣本核酸陽性率顯著高於前一週污水病毒核酸濃度為低濃度組別時之空氣樣本核酸陽性率。在污水監測中發現當日污水相對訊號與之後二週內醫學中心移動平均新增門診及住院確診總人數相關,也和醫學中心所在行政區每十萬人口移動平均新增確診人數與死亡人數相關。其中當日污水相對訊號與該醫學中心後十四日移動平均新增門診及住院確診總人數,與大臺北地區後八日每十萬人口移動平均新增確診人數,與臺北市後二日每十萬人口移動平均新增確診人數,也與中正區後五日每十萬人口移動平均新增確診人數等都有最佳的相關性。我們也發現當日污水相對訊號與後十四日大臺北地區每十萬人口移動平均新增死亡人數,與後十四日臺北市每十萬人口移動平均新增死亡人數,與後十四日中正區每十萬人口移動平均新增死亡人數等都有最佳的相關性。
結論:本研究發現在新冠肺炎Omicron病毒株流行期間且在符合室內二氧化碳標準的情況下,醫學中心防疫專責病房內護理站、走廊等醫護人員的工作環境中存在空氣傳播新冠病毒的風險,且通風越不好 (室內二氧化碳超過582 ppm) 傳播風險越高。污水病毒核酸濃度與一週後護理站及走廊區域空氣採樣的核酸陽性率相關;當日污水相對訊號和後一到十四天內醫學中心的逐日門診及住院確診總人數及醫學中心所在行政區的確診及死亡人數相關。本研究結果顯示在新冠疫情大流行期間有必要採取全面的職業衛生控制措施來降低醫療院所新冠病毒傳播風險。
zh_TW
dc.description.abstractBackground: Since the Coronavirus Disease-2019 (Covid-19) pandemic began in January 2020, airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had impacts on various industries worldwide. It has become a significant occupational health issue during the pandemic. Particularly, first-line healthcare workers caring for Covid-19 patients are at the highest risk of contracting the virus. Therefore, understanding the risk of healthcare workers being exposed to the virus in their workplace is crucial. This study aims to assess the risk of SARS-CoV-2 exposure in nursing stations and corridors outside the wards where Covid-19 patients are admitted to a Medical Center in Taipei through air sampling. The environmental monitoring results were analyzed with ventilation, wastewater sampling, and epidemic data during the study period to explore their relation.
Material and Methods: We conducted environmental surveillance on the floor of isolation wards for Covid-19 patients in a Medical Center in Taipei during the 2022 pandemic of Omicron variant in Taiwan. Environmental surveillance included air and wastewater surveillance from March 10, 2022 to November 9, 2022. We used EAQ-T17 monitors to continuously measure indoor air quality (IAQ) in nursing station and corridors outside the isolation wards. We deployed two-stage cyclonic TE-BC251 bioaerosol samplers to collect air samples during the working hours in these locations once a week. The airborne particulates were collected at three-size ranges: greater than 4 μm, 1-4 μm, and less than 1 μm in each of our smaplers. Untreated hospital wastewater samples were collected from a sampling site representing wastes from the wards once a week. Extracted RNA from both air and wastewater samples underwent real-time reverse transcription polymerase chain reaction for the selected envelope gene of SARS-CoV-2, with a positive a diagnosis of Ct values less than 38 for air samples and Ct values less than 40 for wastewater samples. We defined air pamples as positive when any one of three staged samples were positive. We further examined the association between positivity rates of air samples and indoor CO2 concentrations to evaluate ventilation effects on air borne transmission of SARS-CoV-2. Waste water surveillenace of relative viral loads data were used to construct models for predicting daily numbers of outpatient and in-patient Covid-19 cases in the Medical Center and daily Covid-19 cases and deaths in the Zhongzheng District and Taipei City, where the Medical Center was situated.
Results: During the eight months of environmental surveillance, the number of Covid-19 cases ranged from 25 to 10,872 cases and the number of Covid-19 deaths ranged from 0 to 30 deaths in Taipei City; the number of Covid-19 cases ranged from 1 to 588 cases, the number of Covid-19 deaths ranged from 0 to 8 deaths in Zhongzheng District; the total number of outpatient and inpatient Covid-19 confirmed cases ranged from 3 to 341 cases at the Medical Center. The positive rate was 38% of the 93 air samples collected from the nursing station and was 40 % of the 342 air samples collected from the corridors durin the 8-month surveillance period. Indoor CO2 concentrations at the nursing station and corridors reanged from 400 to 770 ppm during the same study period, which were all below the threshold value of 800 ppm proposed by the US-CDC in this pandemic. All wastewater samples were tested positive for SARS-CoV-2 RNA, with viral loads ranging from 28 to 2,800 copies/L and relative viral loads ranging from 0.001 to 0.047.
Our findings showed statistically significant correlation between the positivity rates of air samples and indoor CO2 concentrations. At the nursing station, the positivity rate of air samples was significantly highe when indoor CO2 concentrations were greater than 582 ppm. At the corridors, the positivity rate of air samples was significantly higher when indoor CO2 concentrations were greater than 447 ppm. We also identified a temporal relationship between air and wastewater sampling results of SARS-CoV-2 RNA analyses. Viral loads of SARS-CoV-2 in wastewater were positive associated with positive rates of air samples at the corridors in the following week with the highest significant level at the 7th day. We found that relative viral loads in wastewater had significant correlation with Covid-19 cases per 100,000 population at 1 to 14 days moving averages in the Medical Center, the District and the City afterwards. The highest correlation levels were found for moving averages at 8 days in Taipei Metro Area, 2 days in Taipei City, 5 days in Zhongzheng District, and 14 days in the Medical Center. We also found significant correlation between relative viral loads in wastewater and Covid-19 deaths per 100,000 population at 1 to 14 days moving averages in Taipei Metro Area, Taipei City, and Zhongzheng District.
Conclusion: During the Omicron variant pandemic period in Taiwan, the airborne transmission risk of SARS-CoV-2 remains relatively high in the workplace nearing Covid-19 patient wards even though indoor CO2 concentrations were below 800 ppm during the working hours. The airborne transmission risk became even greater when indoor CO2 concentrations exceeded 582 ppm. The wastewater viral load in Medical Center was related to the positive rate of air samples in the next week, while relative viral loads were correlated with total numbers of confirmed outpatients and inpatients within two weeks in the Medical Center and numbers of confirmed cases and deaths within two weeks in the administrative areas where the Medical Center was situated. Our findings suggest comprehensive occupational health control measures shoud be applied to reduce the risk of SARS-CoV-2 transmission in healthcare facilities during the pandemic.
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dc.description.tableofcontents致謝 I
中文摘要 II
Abstract V
目錄 VIII
圖目錄 X
表目錄 XI
第一章 文獻回顧 1
1.1嚴重特殊傳染性肺炎 (Coronavirus Disease-2019, Covid-19) 1
1.2臺灣新冠肺炎疫情概況 5
1.3新型冠狀病毒傳播途徑 14
1.4新冠肺炎與職業暴露、職業衛生 17
1.5新型冠狀病毒空氣監測之探討 22
1.6新型冠狀病毒污水監測之探討 25
1.7研究目的 28
第二章 材料與方法 29
2.1研究架構 29
2.2研究地區與空氣採樣點基本資料 30
2.3環境採樣方法 32
2.3.1空氣採樣前置作業 32
2.3.2空氣樣本採樣 33
2.4室內空氣品質監測 36
2.5空氣採樣樣本運送與處理 37
2.6空氣樣本新冠病毒核酸萃取 38
2.7空氣樣本分析 39
2.8採樣器清洗流程 40
2.9實驗QA與QC 41
2.9.1樣本保存 41
2.9.2檢量線製作 41
2.10外部資料庫數據使用 42
2.10.1醫學中心污水新冠病毒監測數據 42
2.10.2醫學中心院內醫療整合資料庫 42
2.10.3疾病管制署資料開放平台 43
2.10.4各行政區人口數 43
2.11資料處理與統計分析 44
2.11.1新冠肺炎疫情指標整理 44
2.11.2空氣病毒核酸陽性率與室內二氧化碳濃度統計分析 47
2.11.3空氣樣本與污水病毒量之時序性統計分析 48
2.11.4空氣病毒核酸陽性率與醫學中心門診及住院新冠肺炎確診總人數統計分析 49
2.11.5空氣病毒核酸陽性率與社區疫情指標統計分析 50
2.11.6污水病毒核酸濃度與醫學中心門診及住院新冠肺炎確診總人數統計分析 51
2.11.7污水病毒核酸濃度與社區疫情指標統計分析 52
第三章 結果 53
3.1空氣環境採樣之描述性統計 53
3.2污水環境採樣之描述性統計 61
3.3空氣病毒核酸陽性率與室內二氧化碳濃度 63
3.4空氣樣本與污水病毒濃度之時序性 65
3.5空氣病毒核酸陽性率與醫學中心門診及住院新冠肺炎確診總人數 67
3.6空氣病毒核酸陽性率與社區新冠肺炎疫情指標 71
3.7污水病毒核酸濃度與醫學中心門診及住院新冠肺炎確診總人數相關性模型 86
3.8污水病毒核酸濃度與社區疫情指標相關性模型 88
第四章 討論 98
4.1新型冠狀病毒空氣實測情況之討論 98
4.2新型冠狀病毒空氣與污水之時序性討論 106
4.3空氣新型冠狀病毒與醫學中心確診指標及社區疫情指標之討論 108
4.4新型冠狀病毒污水實測情況之討論 110
4.5研究限制 114
第五章 結論 115
第六章 建議 116
參考文獻 117
附錄 138
附錄一、各空氣採樣日期與採樣點設置 138
附錄二、各採樣點新冠病毒核酸平均循環數閾值檢測分析結果 141
附錄三、ROC曲線分析圖 144
附錄四、空氣樣本新冠病毒核酸萃取步驟 168
附錄五、空氣採樣相關文獻回顧之採樣設計差異統整 170
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dc.language.isozh_TW-
dc.subject新冠病毒zh_TW
dc.subject污水監測zh_TW
dc.subject新冠肺炎zh_TW
dc.subject空氣傳播zh_TW
dc.subject空氣監測zh_TW
dc.subjectair surveillanceen
dc.subjectSARS-CoV-2en
dc.subjectairborne transmissionen
dc.subjectCovid-19en
dc.subjectwastewater surveillanceen
dc.title某醫學中心在新冠肺炎Omicron病毒株流行期間環境監測之調查研究zh_TW
dc.titleEnvironmental surveillance in a medical center during the SARS-CoV-2 Omicron variant pandemicen
dc.typeThesis-
dc.date.schoolyear111-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee蘇大成;張淑媛;陳佳堃zh_TW
dc.contributor.oralexamcommitteeTa-Chen Su;Sui-Yuan Chang;Jia-Kun Chenen
dc.subject.keyword新冠病毒,新冠肺炎,污水監測,空氣監測,空氣傳播,zh_TW
dc.subject.keywordCovid-19,SARS-CoV-2,air surveillance,wastewater surveillance,airborne transmission,en
dc.relation.page172-
dc.identifier.doi10.6342/NTU202301189-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2023-06-27-
dc.contributor.author-college公共衛生學院-
dc.contributor.author-dept環境與職業健康科學研究所-
dc.date.embargo-lift2028-06-27-
顯示於系所單位:環境與職業健康科學研究所

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