Space-time statistical models for detecting emerging outbreaks of rare events.
| Project/Area Number |
20300101
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | National Institute of Public Health |
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Principal Investigator |
TANGO Toshiro National Institute of Public Health, 生活機構研究科, 客員教授 (70124477)
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| Co-Investigator(Renkei-kenkyūsha) |
TAKAHASHI Kunihiko 国立保健医療科学院, 技術評価部, 主任研究官 (50323259)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥15,210,000 (Direct Cost: ¥11,700,000、Indirect Cost: ¥3,510,000)
Fiscal Year 2010: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2009: ¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2008: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
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| Keywords | 空間・環境統計 / 症侯サーベイランス / 空間疫学 / 疾病集積性 / 尤度比検定 / ボアッソン分布 / ポアッソン分布 |
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| Research Abstract |
We have developed new statistical models as important tools for detecting emerging outbreaks of rare events threatening human health. The existing methods cannot detect irregularly shaped outbreak areas timely and appropriately. First, we developed a new restricted likelihood ratio to avoid the property of existing scan statistics that tend to detect the cluster much larger than the true cluster by swallowing neighboring regions with non-elevated risk. Second, we developed a new space-time scan statistic which compares the observed number of cases with the unconditional expected number of cases, takes a time-to-time variation of Poisson mean into account and implements an outbreak model to capture localized emerging disease outbreaks more timely and correctly. The proposed models are illustrated with data from weekly surveillance of the number of absentees in primary schools in Kita-Kyushu, Japan, 2006.
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Report
(4 results)
Research Products
(19 results)
