Monday, 7 January 2013
Exhibit Hall 3 (Austin Convention Center)
Human health is affected by a complex and coordinated action of many factors: Atmospheric, physiological, and behavioral, placing humans into different scenarios of sensible stress, that immediately impact the response of human beings to these external forcing. Asthma, a respiratory disorder characterized by airways inflammation and shortness of breath is an example of a human response to adverse environmental conditions conditioned by a genetic predisposition of individuals. Different triggering mechanisms have been considered by epidemiologists and medical doctors, with emphasis on aeroallergens (pollens, molds, sea aerosols, and dust) and anthropogenic irritant compounds (ozone, nitrous oxides, carbon monoxide, sulfur, and soot). However, changing weather conditions may also exacerbate asthma episodes and modify the concentrations of aeroallergen and pollutants in such a way that, they will reinforce the triggering of asthma. In portions of United States, time series of asthma cases show a clear seasonal pattern with a maximum starting in fall and extending to the second half of December and early January, followed by a substantial drop between April and June. A similar comprehensive study is missing in Florida, and in particular South Florida. Motivated by these facts, six years of weather data (time series) acquired from Earth-networks (Weatherbug) and including, air temperature (Ta), barometric pressure (P), relative humidity (RH), wind speed and direction (v and è), as well as the minimum and maximum values, the average for a day and a month, and the range of these magnitudes are used to estimate a group of weather indexes showing some potential for synoptic forecasting of asthma episodes. Indexes include those classified into relative and absolute, passive or active, as well as stress and strain. Wind roses are computed intra-monthly as well as for the whole month year round. As a result, fluctuations in monthly and weekly wind patterns have emerged and are contrasted with time periods when episodes of asthma are more likely to occur. Additionally, the time series of ground level Ozone (O3) and Particulate Matter (PM2.5) are analyzed in conjunction with weather parameters. From the statistical analysis a weak correlation is clear between the number of cases with asthma and individual weather parameters and air quality conditions; however when they are combined into some of the weather indexes suggested in the literature (Cumulative Index of Stress, Environmental Stress Index, Index of Thermal Stress, Maximum Exposure Time, Outdoor Thermal Environment Index, Physiological Index of Strain, Physiological Subjective Temperature, and Respiratory Heat Loss) correlations between the number of asthma cases and these indexes are shifting to the range of moderate and strong correlations. It is suggested that an asymmetric V (or U) shaped relationship should be at work between weather and air conditions variability and asthma cases. It seems that the above mentioned variability may not be the causal factor initiating lung diseases but a symptom trigger. Noteworthy, the statistical analysis is very sensitive to the temporal resolution of the data. When the number of patients reported with asthma is defined for time scales of more than every seven days, the process of weather averaging negatively impact the process of finding possible correlations. This fact is important for the process of smoothing the time series data with filters as well as for the lag-analysis. Relative indexes appear more suitable when data from different geographical and climatic zones are compared to each other, and the relationship between the cold weather stress and the physiological elasticity appears to be the leading factors in the immune response during asthma episodes triggering the hyper responsiveness and inflammatory pattern seen in patients. Studies such as this will help health general practitioners to anticipate increases in consultation rates associated with asthma, as well as to better manage medical resources.
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