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Quantifying the role of weather on seasonal influenza

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  • Quantifying the role of weather on seasonal influenza

    BMC Public Health. 2016 May 26;16(1):441. doi: 10.1186/s12889-016-3114-x.
    Quantifying the role of weather on seasonal influenza.

    Roussel M1,2, Pontier D3,4, Cohen JM5, Lina B6,7, Fouchet D3,4.
    Author information

    Abstract

    BACKGROUND:

    Improving knowledge about influenza transmission is crucial to upgrade surveillance network and to develop accurate predicting models to enhance public health intervention strategies. Epidemics usually occur in winter in temperate countries and during the rainy season for tropical countries, suggesting a climate impact on influenza spread. Despite a lot of studies, the role of weather on influenza spread is not yet fully understood. In the present study, we investigated this issue at two different levels.
    METHODS:

    First, we evaluated how weekly (intra-annual) incidence variations of clinical diseases could be linked to those of climatic factors. We considered that only a fraction of the human population is susceptible at the beginning of a year due to immunity acquired from previous years. Second, we focused on epidemic sizes (cumulated number of clinical reported cases) and looked at how their inter-annual and regional variations could be related to differences in the winter climatic conditions of the epidemic years over the regions. We quantified the impact of fifteen climatic variables in France using the R?seau des GROG surveillance network incidence data over eleven regions and nine years.
    RESULTS:

    At the epidemic scale, no impact of climatic factors was highlighted. At the intra-annual scale, six climatic variables had a significant impact: average temperature (5.54 ? 1.09 %), absolute humidity (5.94 ? 1.08 %), daily variation of absolute humidity (3.02 ? 1.17 %), sunshine duration (3.46 ? 1.06 %), relative humidity (4.92 ? 1.20 %) and daily variation of relative humidity (4.46 ? 1.24 %). Since in practice the impact of two highly correlated variables is very hard to disentangle, we performed a principal component analysis that revealed two groups of three highly correlated climatic variables: one including the first three highlighted climatic variables on the one hand, the other including the last three ones on the other hand.
    CONCLUSIONS:

    These results suggest that, among the six factors that appeared to be significant, only two (one per group) could in fact have a real effect on influenza spread, although it is not possible to determine which one based on a purely statistical argument. Our results support the idea of an important role of climate on the spread of influenza.


    PMID: 27230111 [PubMed - in process] PMCID: PMC4881007 Free PMC Article
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