Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/53913
標題: 考量資訊及風險下對H1N1新流感大流行疫苗需求之估計
Estimating the Demands of H1N1 Pandemic Influenza Vaccines with Considerations of the Information and Risks
作者: 曾偉君
關鍵字: 基礎研究
H1N1 new influenza
經濟學
H1N1 新流感
Binary choice models
資訊
Ordered data models
風險
疫苗需求
Binary choice models
Information
Ordered data models
Risk
Vaccine demand
摘要: 標題: 考量資訊及風險下對H1N1 新流感大流行疫苗需求之估計Title: Estimating the Demands of H1N1 Pandemic Influenza Vaccines with Considerations ofthe Information and Risks自2009 年春季起在全球造成大流行的新流感, 其疫苗接種規模是人類有史以來最大者。如同若干先進國, 我國疫苗接種人數(這個防疫成敗的關鍵)很可能係由需求面決定。因此, 本研究的目的擬探究各種資訊, 以及風險評估, 如何影響民眾的疫苗接種需求(包括接種行為及接種意願)。並探討性別, 城鄉, 南北, 懷孕, 以及接種優先順序等之差異。文獻上, 疫苗需求的研究主要在於用CVM, 來估計重大傳染病, 其尚未存在的疫苗之接種意願及潛在市場價值, 如瘧疾(Cropper et al., 2004)、SARS (Liu et al., 2005)、登革熱(Palanca-Tan, 2008) 以及AIDS(Bishai et al., 2004; Suraratdecha et al., 2005;Whittington et al., 2008)。本文則是探討正在進行中之重大傳染病, 其已存在之疫苗的需求。疫苗之接種行為有“已接種”及“未接種”兩類, 係屬於1 或是0 的二元選擇資料。本研究在“未接種”部份, 則進一步詢問其將來接種意願, 這是ordered data。因此, 本研究擬使用二元選擇模型(binary choice models), 排序性模型(ordered data models), 以及兩者之結合模型來估計, 並嘗試多種機率分配設定。本研究將有助於人們瞭解在疫苗供應充足的國家, 其接種人數是如何決定的, 並探討政策變數(如更充足資訊, 疫苗受害補貼)之作用, 有助於未來各國面對下一波或類似大流行之參考。因此本計劃在學術主題, 防疫政策, 及研究方法上, 將有所貢獻。
Title: Estimating the Demands of H1N1 Pandemic Influenza Vaccines withConsiderations of the Information and RisksThe H1N1 influenza pandemic has spread since 2009 spring. Its scale of inoculation is the largestin human history. Like several advanced countries, the number of people vaccinated (i.e. the keyfactor of success to to the pandemic prevention) of our country is likely determined by the demand.Therefore, the purpose of this research is to investigate how the various kinds of information andrisks are affecting the inoculation demand, including inoculation behaviors and attitude to bevaccinated. This study will also investigates the effects of gender, urban or rural areas, north andsouth, pregnant or not, and incubation priority on the inoculation demand. Literature of vaccinedemand mainly focuses on using CVM to estimate the willingness of inoculations and potentialmarket values of hypothetical vaccine of serious infectious diseases, such as the malaria(Cropper etal., 2004), SARS (Liu et al. , 2005 ), dengue fever (Palanca-Tan , 2008 ) and AIDS (Bishai et al.,2004; Suraratdecha et al., 2005; Whittington et al., 2008). In contrast, this study investigates thedemand of existing vaccines of on-going serious infectious disease. People's inoculation behavioris either inoculated or not inoculated, thus is belonged to the binary choice data of 1s or 0s. Forthose who are not inoculated, this study further asks their attitude of being inoculated in the future.This is ordered data. Therefore, this research plans to use binary choice models, ordered datamodels, and the combination model of the above two types of models in the estimations.Meanwhile, various probability distributions will be tested. This research will contribute to people'sunderstanding of how the number of persons inoculated is determined for those countries withsufficient supply of the vaccines. It also investigates how the policy variables, such as moresufficient information and the subsidy to victims of side effects of vaccines, affect the number ofpersons inoculated. Thus it will be reference to various countries in future waves of pandemics orpandemics in the future. Therefore, this project will contribute in the academic theme, on pandemicprevention policy, and on the research approach.
URI: http://hdl.handle.net/11455/53913
其他識別: NSC99-2410-H005-009
文章連結: http://grbsearch.stpi.narl.org.tw/GRB/result.jsp?id=2098282&plan_no=NSC99-2410-H005-009&plan_year=99&projkey=PF9906-1289&target=plan&highStr=*&check=0&pnchDesc=%E8%80%83%E9%87%8F%E8%B3%87%E8%A8%8A%E5%8F%8A%E9%A2%A8%E9%9A%AA%E4%B8%8B%E5%B0%8DH1N1%E6%96%B0%E6%B5%81%E6%84%9F%E5%A4%A7%E6%B5%81%E8%A1%8C%E7%96%AB%E8%8B%97%E9%9C%80%E6%B1%82%E4%B9%8B%E4%BC%B0%E8%A8%88
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