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A Nice Day for an Infection? Weather Conditions and Social Contact Patterns Relevant to Influenza Transmission

Overview of attention for article published in PLOS ONE, November 2012
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Title
A Nice Day for an Infection? Weather Conditions and Social Contact Patterns Relevant to Influenza Transmission
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0048695
Pubmed ID
Authors

Lander Willem, Kim Van Kerckhove, Dennis L. Chao, Niel Hens, Philippe Beutels

Abstract

Although there is no doubt that significant morbidity and mortality occur during annual influenza epidemics, the role of contextual circumstances, which catalyze seasonal influenza transmission, remains unclear. Weather conditions are believed to affect virus survival, efficiency of transmission and host immunity, but seasonality may also be driven by a tendency of people to congregate indoors during periods of bad weather. To test this hypothesis, we combined data from a social contact survey in Belgium with local weather data. In the absence of a previous in-depth weather impact analysis of social contact patterns, we explored the possibilities and identified pitfalls. We found general dominance of day-type (weekend, holiday, working day) over weather conditions, but nonetheless observed an increase in long duration contacts ([Formula: see text]1 hour) on regular workdays with low temperatures, almost no precipitation and low absolute humidity of the air. Interestingly, these conditions are often assumed to be beneficial for virus survival and transmission. Further research is needed to establish the impact of the weather on social contacts. We recommend that future studies sample over a broad spectrum of weather conditions and day types and include a sufficiently large proportion of holiday periods and weekends.

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Geographical breakdown

Country Count As %
France 2 2%
Vietnam 2 2%
Italy 1 1%
Austria 1 1%
Israel 1 1%
United Kingdom 1 1%
United States 1 1%
Unknown 90 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 21%
Student > Ph. D. Student 20 20%
Student > Master 12 12%
Student > Doctoral Student 10 10%
Student > Bachelor 6 6%
Other 19 19%
Unknown 11 11%
Readers by discipline Count As %
Medicine and Dentistry 27 27%
Agricultural and Biological Sciences 15 15%
Mathematics 8 8%
Social Sciences 7 7%
Computer Science 4 4%
Other 24 24%
Unknown 14 14%