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Prediction of the Spread of Influenza Epidemics by the Method of Analogues
Author(s) -
Cécile Viboud,
PierreYves Boëlle,
Fabrice Carrat,
AlainJacques Valleron,
Antoine Flahault
Publication year - 2003
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwg239
Subject(s) - autoregressive model , nonparametric statistics , autoregressive integrated moving average , incidence (geometry) , statistics , econometrics , series (stratigraphy) , seasonal influenza , time series , geography , mathematics , covid-19 , medicine , biology , paleontology , geometry , disease , infectious disease (medical specialty)
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.

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