title: The effects of synoptic weather on influenza infection incidences: a retrospective study utilizing digital disease surveillance.
abstract: The environmental drivers and mechanisms of influenza dynamics remain unclear. The recent development of influenza surveillance--particularly the emergence of digital epidemiology--provides an opportunity to further understand this puzzle as an area within applied human biometeorology. This paper investigates the short-term weather effects on human influenza activity at a synoptic scale during cold seasons. Using 10 years (2005-2014) of municipal level influenza surveillance data (an adjustment of the Google Flu Trends estimation from the Centers for Disease Control's virologic surveillance data) and daily spatial synoptic classification weather types, we explore and compare the effects of weather exposure on the influenza infection incidences in 79 cities across the USA. We find that during the cold seasons the presence of the polar [i.e., dry polar (DP) and moist polar (MP)] weather types is significantly associated with increasing influenza likelihood in 62 and 68% of the studied cities, respectively, while the presence of tropical [i.e., dry tropical (DT) and moist tropical (MT)] weather types is associated with a significantly decreasing occurrence of influenza in 56 and 43% of the cities, respectively. The MP and the DP weather types exhibit similar close positive correlations with influenza infection incidences, indicating that both cold-dry and cold-moist air provide favorable conditions for the occurrence of influenza in the cold seasons. Additionally, when tropical weather types are present, the humid (MT) and the dry (DT) weather types have similar strong impacts to inhibit the occurrence of influenza. These findings suggest that temperature is a more dominating atmospheric factor than moisture that impacts the occurrences of influenza in cold seasons.
authors.affiliation: Department of Geosciences, Texas Tech University, Lubbock, TX, USA.|Center for Geospatial Technology, Texas Tech University, Lubbock, TX, USA.
authors.forename: Naizhuo
authors.initials: N
authors.lastname: Zhao
authors.affiliation: Department of Geosciences, Texas Tech University, Lubbock, TX, USA. Guofeng.cao@ttu.edu.|Center for Geospatial Technology, Texas Tech University, Lubbock, TX, USA. Guofeng.cao@ttu.edu.
authors.forename: Guofeng
authors.identifier: http://orcid.org/0000-0003-4827-1558
authors.initials: G
authors.lastname: Cao
authors.affiliation: Department of Geosciences, Texas Tech University, Lubbock, TX, USA.|Climate Science Center, Texas Tech University, Lubbock, TX, USA.
authors.forename: Jennifer K
authors.initials: JK
authors.lastname: Vanos
authors.affiliation: Climate Science Lab, Department of Geography, Texas A&M University, Lubbock, TX, USA.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Vecellio
mesh_terms: D062665:Epidemiological Monitoring; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology*; D012189:Retrospective Studies; D014887:Weather
keywords: Biometeorology; Environmental health; Google Flu Trends (GFT); Influenza; Spatial synoptic classification (SSC)