Journal Article

Prediction of the Spread of Influenza Epidemics by the Method of Analogues

Cécile Viboud, Pierre-Yves Boëlle, Fabrice Carrat, Alain-Jacques Valleron and Antoine Flahault

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 158, issue 10, pages 996-1006
Published in print November 2003 | ISSN: 0002-9262
Published online November 2003 | e-ISSN: 1476-6256 | DOI:
Prediction of the Spread of Influenza Epidemics by the Method of Analogues

More Like This

Show all results sharing this subject:

  • Public Health and Epidemiology


Show Summary Details


This study was designed to examine the performance of a nonparametric forecasting method first developed in meteorology, the “method of analogues,” in predicting influenza activity. This method uses vectors selected from historical influenza time series that match current activity. The authors applied it to forecasting the incidences of influenza-like illnesses (ILI) in France and in the country’s 21 administrative regions, using a series of data for 938 consecutive weeks of ILI surveillance between 1984 and 2002, and compared the results with those for autoregressive models. For 1- to 10-week-ahead predictions, the correlation coefficients between the observed and forecasted regional incidences ranged from 0.81 to 0.66 for the method of analogues and from 0.73 to –0.09 for the autoregressive models (p < 0.001). Similar results were obtained for national incidence forecasts. From the results of this method, maps of influenza epidemic forecasts can be made in countries in which national and regional data are available.

Keywords: communicable disease control; diffusion; epidemiologic methods; forecasting; influenza; statistics, nonparametric; Abbreviations: CV, cross-validation; ILI, influenza-like illnesses.

Journal Article.  5176 words.  Illustrated.

Subjects: Public Health and Epidemiology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.