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  1. NTU Theses and Dissertations Repository
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96844
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dc.contributor.advisor吳亞克zh_TW
dc.contributor.advisorAndrei R. Akhmetzhanoven
dc.contributor.author杜曉丹zh_TW
dc.contributor.authorBianca Therese Navasero De Paduaen
dc.date.accessioned2025-02-24T16:13:27Z-
dc.date.available2025-02-25-
dc.date.copyright2025-02-24-
dc.date.issued2025-
dc.date.submitted2025-02-04-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96844-
dc.description.abstract引言:2022 年,烏干達爆發了蘇丹病毒病(SVD)疫情,該疫情為橫跨九個地區,為一起超級傳播事件,導致 164 名確診病例與 77 名死亡病例。在缺乏藥物介入的情況下,烏干達依靠的是快速的疫情應對和精準的封鎖策略。本研通過估算地區和全國層級的有效再生數(R_t),以比較控制措施實施前後的傳播動態,並評估介入效果。

方法:本研究估算了公共衛生介入實施前後的地區層級有效再生數 (R_t) 和全國層級控制再生數 (R_c (t))。R_t 是透過擬合每日新增病例與發病日資料,並利用更新方程 ( Renewal Equation )修正後,估算個案感染日期計算得出。考慮跨區域傳播的潛在影響下,進一步使用次世代矩陣(Next-Generation Matrix)方法,估計全國層級 R_c (t) 。

結果:疫情初期,估算的〖 R〗_t 約為 2,但在穆本德(Mubende)地區部署伊波拉應對團隊後,〖 R〗_t降至疫情閾值 1 以下。然而,地區間的傳播引發了其他地區疫情的蔓延,鄰近的卡桑達(Kassanda)地區的超級傳播事件,使得該地區的 〖 R〗_t大幅上升至約 9,隨後坎帕拉(Kampala)地區也出現了超級傳播,但未觀察到持續的本地傳播。在穆本德和卡桑達實施封鎖後,〖 R〗_t降至 1 以下。全國層級的 R_c (t) 也反映了與地區層級〖 R〗_t相似的傳播動態模式。

結論:本研究的估計顯示,地區間的傳播對 SVD 疫情擴散的具有顯著影響。儘管最初疫情流行的地區迅速地啟動了應對措施,但未能追蹤到的跨地區病例,仍會導致疫情進一步的向外擴散。因此在疫情嚴峻地區實施的封鎖,不僅有效抑制了該地區的疫情擴散,亦穩定了其他地區的傳播動態。
zh_TW
dc.description.abstractIntroduction: In 2022, Uganda faced a Sudan virus disease (SVD) outbreak with 164 cases and 77 deaths, marked by cross-border spread across nine districts and superspreading events. Without pharmaceutical interventions, Uganda relied on swift Ebola response measures and targeted lockdowns. This study evaluates the effectiveness of these interventions by estimating the time-varying reproduction number at district and national levels, comparing its dynamics before and after the control measures.

Methods: We estimated district-level effective reproduction number (R_t) and national-level control reproduction number (R_c (t)) in periods pre/post the implementation of public health interventions. R_t was estimated by date of infection by fitting daily incidence data based on symptom onset and revising the renewal equation. The Next-Generation Matrix method was employed to incorporate the potential impact of transmission between districts on R_t and estimate the national-level R_c (t).

Results: R_t was estimated to be around 2 in the early phase of the outbreak but went below the epidemic threshold of 1 after the deployment of initial response in the Mubende district, which was the epicenter of the epidemic. However, transmission between districts during this period triggered a superspreading event in the neighboring Kassanda district, reflected by the large increase in R_t up to around 9 within this district. Superspreading also occurred in the Kampala district due to spillover, though no local transmission was observed. R_t decreased below 1 after the implementation of lockdown in Mubende and Kassanda. The national-level R_c (t) reflects similar patterns in transmission dynamics as the district-level R_t.

Conclusions: Our estimates highlight the significant impact of between-district transmission on the spread of SVD during the outbreak. Despite the prompt launch of local response measures in the epicenter district, untraced cases crossing district borders have caused the outbreak to spread beyond the epicenter. The implementation of lockdown in the most affected districts effectively averted the continued expansion of the outbreak by preventing further spread both within and between districts.
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dc.description.tableofcontentsVerification Letter from the Oral Examination Committee for Master’s Students i
Acknowledgements ii
Abstract (Chinese) iii
Abstract (English) iv
1 Introduction 1
1.1 History of Ebola Outbreaks 1
1.2 Clinical Characteristics of Ebola 2
1.3 Epidemiological Characteristics of Ebola 4
1.4 Estimating the Effective Reproduction Number 5
1.5 Public Health Responses to Ebola 7
1.6 Sudan Virus Disease Outbreak in Uganda, 2022 8
1.7 Research Objectives 9
2 Methods 11
2.1 Data Collection 11
2.2 Statistical Framework 12
2.2.1 Bayesian Statistics and Markov Chain Monte Carlo Sampling 12
2.2.2 Estimation of Epidemiological Time Intervals 13
2.3 Transmission Dynamics Within and Between Districts 14
2.3.1 Modified Renewal Equation 15
2.3.2 Next Generation Matrix 15
3 Results 17
3.1 Time Interval Distributions 17
3.1.1 Incubation Period of Ebola 17
3.1.2 Time Between Onset of Symptoms and Transmission (TOST) of Ebola 17
3.2 Transmission dynamics 17
4 Discussion 19
References 27
Appendix 33
Tables & Figures 34
-
dc.language.isoen-
dc.title2022年烏干達蘇丹病毒疫情之介入效果量化分析zh_TW
dc.titleQuantifying the efficiency of interventions during the Sudan virus outbreak in Uganda, 2022en
dc.typeThesis-
dc.date.schoolyear113-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee方啓泰;Jonathan Dushoffzh_TW
dc.contributor.oralexamcommitteeChi-Tai Fang;Jonathan Dushoffen
dc.subject.keyword伊波拉,蘇丹病毒,有效再生數,烏干達 2022 年疫情,伊波拉應對團隊,封鎖,超級傳播事件,次世代矩陣,介入效果,傳播動態,zh_TW
dc.subject.keywordEbola,Sudan virus,effective reproduction number,Uganda outbreak 2022,Ebola response,lockdown,superspreading events,Next-Generation Matrix,intervention efficiency,transmission dynamics,en
dc.relation.page37-
dc.identifier.doi10.6342/NTU202500308-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2025-02-05-
dc.contributor.author-college公共衛生學院-
dc.contributor.author-dept全球衛生學位學程-
dc.date.embargo-lift2025-02-25-
顯示於系所單位:全球衛生學位學程

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