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dc.contributor.advisor李美慧zh_TW
dc.contributor.advisorMei-Hui Lien
dc.contributor.authorAsma Nassor Salimzh_TW
dc.contributor.authorAsma Nassor Salimen
dc.date.accessioned2025-08-18T00:52:21Z-
dc.date.available2025-08-18-
dc.date.copyright2025-08-15-
dc.date.issued2025-
dc.date.submitted2025-08-06-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98558-
dc.description.abstract猴痘(mpox) 是一種再現的人畜共通傳染病,目前更在非洲中部和西部地區引發公共健康關注。本研究採用生態棲位模型(ecological niche modeling,ENM)以預測人類猴痘的潛在地理分布,並識別高風險外溢區域。本研究分析2010年至2022年間相關報告確認的人類猴痘病例之550地點,並結合從最初33個環境變數經相關矩陣分析後,篩選出的16個變數進行 最大熵模型( maximum entropy model, MaxEnt)建模分析。這些變數包括氣候資料、土地覆蓋類型、海拔高度、人口數量、人類足跡,以及三種已知囓齒類自然宿主物種(Cricetomys、Funisciurus 和 Graphiurus 屬)的分布情形。最大熵模型建模的表現良好(平均AUC值為0.867),並指出海拔高度、人口數量、最冷季節的降水量(BIO19)、葉面積指數以及Graphiurus屬為最具影響力的預測因子。高風險區主要集中在剛果民主共和國、奈及利亞南部、喀麥隆、賴比瑞亞以及獅子山共和國。整合人口資料後發現,剛果民主共和國有超過2,900萬人、奈及利亞有1,300萬人居住於高度適合猴痘傳播的環境區域內。本研究強調將宿主物種納入風險模型的重要性,因為其存在對空間預測結果具有顯著影響。研究結果顯示,結合生態、環境與人口統計數據,有助於識別優先監測區域並制定公共衛生預防措施。zh_TW
dc.description.abstractMpox is re-emerging zoonotic disease with increasing public health concern across Central and West Africa. This study used ecological niche modeling (ENM) to predict the potential geographic distribution of human mpox and identify areas at high risk of spillover. A total of 550 confirmed mpox case locations reported between 2010 and 2022 were analyzed using maximum entropy model (MaxEnt), along with 16 environmental variables selected from an initial set of 33 following a correlation matrix analysis. These variables included climate data, land cover types, elevation, population count, human footprint, and distributions of three known rodent reservoir species (Cricetomys, Funisciurus, and Graphiurus spp.). Maxent model performed well (mean AUC = 0.867) and identified elevation, population count, precipitation of the coldest quarter (BIO19), leaf area index and Graphiurus spp. as the most influential predictors. High-risk zones were concentrated in the Democratic Republic of the Congo (DRC), southern Nigeria, Cameroon, Liberia, and Sierra Leone. Integrating population data revealed that over 29 million individuals in the DRC and 13 million in Nigeria reside in zones of high environmental suitability for mpox transmission. This study emphasizes the importance of including reservoir host species in risk models, as their presence significantly shaped the spatial predictions. These findings demonstrate the value of combining ecological, environmental, and demographic data to identify priority areas for surveillance and public health intervention.en
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dc.description.tableofcontentsCertificate of thesis approval from oral defense committee i
Acknowledge ii
Dedication iii
摘要 iv
Abstract v
Table of Content vi
List of Figures viii
List of Tables ix
Chapter 1 Introduction 1
Chapter 2 Literature Review 4
2.1 Brief historical of mpox 4
2.1.1 Origins and early outbreaks (1958-1970s) 4
2.1.2 Regional endemicity and neglect (1980s-1990s) 4
2.1.3 Global emergence and expansion (2000s-2010s) 5
2.1.4 Current outbreak 5
2.2 Possible drivers of mpox transmission 6
2.2.1 Ecological and environmental drivers 8
2.2.1.1 Climate and ecological change 8
2.2.2 Biological and zoonotic drivers 9
2.2.2.1 Trapping, hunting and consumption of bushmeat 9
2.2.2.2 Animal trade 9
2.2.3 Human behavioral and social drivers 10
2.2.3.1 Travelling and large scale events 10
2.2.3.2 Transmission within household 10
2.2.3.3 Human behavioural transmission 11
2.2.4 Healthcare and public health drivers 11
2.2.4.1 Healthcare settings 11
2.2.5 Immunological and historical drivers 11
2.2.5.1 Decline in smallpox vaccine immunity 11
2.3 Reservoir host 13
2.4 Environmental and climate influences 14
2.5 Ecological niche modeling 16
2.5.1 Ecological niche concept 16
2.5.2 A practical framework of ENM 17
2.5.3 Application of ENM in mpox research 18
2.5.4 Maxent: A robust tool for modelling mpox distribution 18

Chapter 3 Materials and Methods 20
3.1 Study area 21
3.2 Data collection 21
3.2.1 Human mpox cases data 21
3.2.2 Reservoir host occurrence 22
3.2.3 Environmental variables 25
3.2.3.1 Climate data 30
3.2.3.2 Elevation 30
3.2.3.3 Leaf area index 31
3.2.3.4 Land cover 31
3.2.3.5 Population count 32
3.2.3.6 Human footprint 32
3.2.3.7 Reservoir host species layers 33
3.3 Ecological niche modeling (ENM) 33
3.3.1 Software and modelling approach 33
3.3.2 Model evaluation 34
3.3.3 Risk mapping and interpretation 36
Chapter 4 Results and Discussion 38
4.1 Geographic distribution of human mpox cases (2010–2022) 38
4.2 Environmental and host variable importance in mpox distribution 39
4.3 Predicted suitability and high-risk zones 45
4.4 Population exposure and public health implications 47
4.5 Limitations and uncertainties 48
4.6 Strengths of this study 50
Chapter 5 Conclusion 52
References 54
Appendices 70
Appendix 1 Human mpox case locations used in ENM 70
Appendix 2 Overview of MPXV infection in identified reservoir host species 75
Appendix 3 Summary of ecological factors used in previous mpox modeling studies.. 76
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dc.language.isoen-
dc.subject人類猴痘zh_TW
dc.subject生態棲位模型zh_TW
dc.subject最大熵模型zh_TW
dc.subject自然宿主物種zh_TW
dc.subject外溢風險。zh_TW
dc.subjectspillover risken
dc.subjectecological niche modelingen
dc.subjectmaximum entropy modelen
dc.subjectreservoir host speciesen
dc.subjecthuman mpoxen
dc.title非洲人類猴痘的地理分布:運用生態棲位模型理解環境變數與自然宿主物種zh_TW
dc.titleGeographic Distribution of Human Mpox in Africa: Understanding Environmental Variables and Reservoir Host Species Using Ecological Niche Modelingen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee丁照棣;溫在弘zh_TW
dc.contributor.oralexamcommitteeChau-Ti Ting;Tzai-Hung Wenen
dc.subject.keyword人類猴痘,生態棲位模型,最大熵模型,自然宿主物種,外溢風險。,zh_TW
dc.subject.keywordhuman mpox,ecological niche modeling,maximum entropy model,reservoir host species,spillover risk,en
dc.relation.page81-
dc.identifier.doi10.6342/NTU202503300-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2025-08-09-
dc.contributor.author-college共同教育中心-
dc.contributor.author-dept生物多樣性國際碩士學位學程-
dc.date.embargo-lift2025-08-18-
顯示於系所單位:生物多樣性國際碩士學位學程

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