Driving factors of influenza transmission in the Netherlands

Am J Epidemiol. 2013 Nov 1;178(9):1469-77. doi: 10.1093/aje/kwt132. Epub 2013 Sep 12.

Abstract

Influenza epidemics in temperate regions show a characteristic seasonal pattern with peak incidence occurring in winter. Previous research has shown that low absolute humidity and school holidays can both affect influenza transmission. During an epidemic, transmission is strongly influenced by the depletion of susceptibles (i.e., increase in the number of those immune). To assess how much variability in influenza transmission intensity is due to each of these driving factors, we used a long time series of the number of weekly visits to general practitioners for influenzalike illness in the Netherlands from 1970-2011 and transformed this into a time series of weekly influenza reproduction numbers, which are a measure of transmission intensity. We used statistical regression techniques to quantify how the reproduction numbers were affected by each driving factor. We found a clear ranking of importance of driving factors in explaining the variation in transmission intensity. Most of the variation (30%) was explained by the depletion of susceptibles during the season, 27% was explained by between-season effects, and 3% was explained by absolute humidity. School holidays at the Christmas period did not have a statistically significant effect on influenza transmission. Although the influence of absolute humidity was small, its seasonal fluctuations may determine when sustained influenza transmission is possible and may thus drive influenza seasonality.

Keywords: epidemic modeling; influenza; seasonality; transmission dynamics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease Susceptibility / epidemiology
  • Epidemics
  • General Practitioners / statistics & numerical data
  • Holidays
  • Humans
  • Influenza, Human / epidemiology*
  • Influenza, Human / transmission*
  • Netherlands / epidemiology
  • Schools / statistics & numerical data
  • Seasons
  • Time Factors
  • Weather