A SEASONAL INFLUENZA THEORY AND MATHEMATICAL MODEL INCORPORATING METEOROLOGICAL AND SOCIO-BEHAVIORAL

来源 :Journal of Tropical Meteorology | 被引量 : 0次 | 上传用户:liteary
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On the basis of a comprehensive literature review and data analysis of global influenza surveillance, a transmission theory based numerical model is developed to understand the causative factors of influenza seasonality and the biodynamical mechanisms of seasonal flu. The model is applied to simulate the seasonality and weekly activity of influenza in different areas across all continents and climate zones around the world. Model solution and the good matches between model output and actual influenza indexes affirm that influenza activity is highly auto-correlative and relies on determinants of a broad spectrum. Internal dynamic resonance; variations of meteorological elements (solar radiation, precipitation and dewpoint); socio-behavioral influences and herd immunity to circulating strains prove to be the critical explanatory factors of the seasonality and weekly activity of influenza. In all climate regions, influenza activity is proportional to the exponential of the number of days with precipitation and to the negative exponential of quarter power of sunny hours. Influenza activity is a negative exponential function of dewpoint in temperate and arctic regions and an exponential function of the absolute deviation of dewpoint from its annual mean in the tropics. Epidemics of seasonal influenza could be deemed as the consequence of the dynamic resonance and interactions of determinants. Early interventions (such as opportune vaccination, prompt social distancing, and maintaining incidence well below a baseline) are key to the control and prevention of seasonal influenza. Moderate amount of sunlight exposure or Vitamin D supplementation during rainy and short-day photoperiod seasons, more outdoor activities, and appropriate indoor dewpoint deserve great attention in influenza prevention. To a considerable degree, the study reveals the mechanism of influenza seasonality, demonstrating a potential for influenza activity projection. The concept and algorithm can be explored for further applications. On the basis of a comprehensive literature review and data analysis of global influenza surveillance, a transmission theory based numerical model is developed to understand the causative factors of influenza seasonality and the biodynamical mechanisms of seasonal flu. The model is applied to simulate the seasonality and weekly activity of influenza in different areas across all continents and climate zones around the world. Model solution and the good matches between model output and actual influenza indexes affirm that influenza activity is highly auto-correlative and relies on determinants of a broad spectrum. ; variations of meteorological elements (solar radiation, precipitation and dewpoint); socio-behavioral influences and herd immunity to circulating Prove to be the critical explanatory factors of the seasonality and weekly activity of influenza. In all climate regions, influenza activity is proportional to the exponential of the number of days with precipitation and to the negative exponential of quarter power of sunny hours. Influenza activity is a negative exponential function of dewpoint in temperate and arctic regions and an exponential function of the absolute deviation of dewpoint from its annual mean in the tropics. Epidemics of seasonal influenza early warnings (such as opportune vaccination, prompt social distancing, and maintained incidence well below below a baseline) are key to the control and prevention of seasonal influenza. Moderate amount of sunlight exposure or Vitamin D supplementation during rainy and short-day photoperiod seasons, more outdoor activities, and appropriate indoor dewpoint deserve great attention in influenza prevention. To a considerable degree, the study reveals the mechanism of influenza seasonality, demonstrating a potential for influenza activity projection The concept and algorithm can be explored for further applications.
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