Scandinavian Working Papers in Economics

Research Reports,
University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law

No 2007:6: Statistical Surveillance of Epidemics: Peak Detection of Influenza in Sweden

David Bock (), Eva Andersson () and Marianne Frisén ()
Additional contact information
David Bock: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG
Eva Andersson: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG
Marianne Frisén: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG

Abstract: A statistical surveillance system gives a signal as soon as data give enough evidence of an important event. We consider on-line surveillance systems for detecting changes in influenza incidence. One important feature of the influenza cycle is the start of the influenza season, and another one is the change to a decline (the peak). In this report we discuss statistical methods for on-line peak detection. One motive for doing this is the need for health resource planning. Surveillance systems were adapted for Swedish data on laboratory verified diagnoses of influenza. In Sweden, the parameters of the influenza cycles vary too much from year to year for parametric methods to be useful. We suggest a non-parametric method based on the monotonicity properties of the increase and decline around a peak. A Monte Carlo study indicated that this method has useful stochastic properties. The method was applied to Swedish data on laboratory verified diagnoses of influenza for seven periods.

Keywords: Disease surveillance; Monitoring; Non-parametric; Order restrictions

JEL-codes: C10

16 pages, November 28, 2007

Full text files

7604 HTML file 

Download statistics

Questions (including download problems) about the papers in this series should be directed to Linus Schiöler ()
Report other problems with accessing this service to Sune Karlsson ().

This page generated on 2024-02-05 17:11:12.