A space-time permutation scan statistic for disease outbreak detection

被引:852
|
作者
Kulldorff, M [1 ]
Heffernan, R
Hartman, J
Assunçao, R
Mostashari, F
机构
[1] Harvard Univ, Sch Med, Dept Ambulatory Care & Prevent, Boston, MA 02115 USA
[2] Harvard Pilgrin Hlth Care, Boston, MA 02115 USA
[3] New York City Dept Hlth & Mental Hyg, New York, NY USA
[4] New York Acad Med, New York, NY USA
[5] Univ Fed Minas Gerais, Dept Estat, Belo Horizonte, MG, Brazil
关键词
D O I
10.1371/journal.pmed.0020059
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background The ability to detect disease outbreaks early is important in order to minimize morbidity and mortality through timely implementation of disease prevention and control measures. Many national, state, and local health departments are launching disease surveillance systems with daily analyses of hospital emergency department visits, ambulance dispatch calls, or pharmacy sales for which population-at-risk information is unavailable or irrelevant. Methods and Findings We propose a prospective space-time permutation scan statistic for the early detection of disease outbreaks that uses only case numbers, with no need for population-at-risk data. It makes minimal assumptions about the time, geographical location, or size of the outbreak, and it adjusts for natural purely spatial and purely temporal variation. The new method was evaluated using daily analyses of hospital emergency department visits in New York City. Four of the five strongest signals were likely local precursors to citywide outbreaks due to rotavirus, norovirus, and influenza. The number of false signals was at most modest. Conclusion If such results hold up over longer study times and in other locations, the space-time permutation scan statistic will be an important tool for local and national health departments that are setting up early disease detection surveillance systems.
引用
收藏
页码:216 / 224
页数:9
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