Maximum linkage space-time permutation scan statistics for disease outbreak detection

International Journal of Health Geographics

Volumn 13, Issue , 2014, Pages

  Costa, Marcelo A ^a   Kulldorff, Martin ^b  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Sequential Monte Carlo; Space time permutation; Spatial scan statistics

Indexed keywords

CLUSTER ANALYSIS; DISEASE PREVALENCE; DISEASE SPREAD; GEOMETRY; HEALTH IMPACT; MONTE CARLO ANALYSIS; NUMERICAL MODEL; POPULATION OUTBREAK; SPATIAL ANALYSIS;

ADOLESCENT; ADULT; AGED; ARTICLE; EPIDEMIC; FEMALE; HEALTH SURVEY; HUMAN; INFLUENZA; MALE; METHODOLOGY; MIDDLE AGED; MONTE CARLO METHOD; PROSPECTIVE STUDY; SPATIOTEMPORAL ANALYSIS; STATISTICS; UNITED STATES; VERY ELDERLY; YOUNG ADULT;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; DISEASE OUTBREAKS; FEMALE; HUMANS; INFLUENZA, HUMAN; MALE; MIDDLE AGED; MONTE CARLO METHOD; NEW ENGLAND; POPULATION SURVEILLANCE; PROSPECTIVE STUDIES; SPATIO-TEMPORAL ANALYSIS; YOUNG ADULT;

EID: 84903308318     PISSN: None     EISSN: 1476072X     Source Type: Journal    
DOI: 10.1186/1476-072X-13-20     Document Type: Article

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