Spatiotemporal analysis of air pollution and asthma patient visits in Taipei, Taiwan
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* Corresponding author: Jen-Hsiang Chuang jhchuang@cdc.gov.tw
1 National Health Command Center, Centers for Disease Control, Taipei, Taiwan, R.O.C
2 Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei, Taiwan, R.O.C
3 Institute of Environmental and Occupational Health Sciences & Department of Environmental and Occupational Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C
4 Department of Social Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C
5 Institute of Public Health, School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C
6 Institute of Health Care Administration, National Yang-Ming University, Taipei, Taiwan, R.O.C
7 Center for Health Policy Research and Development, National Health Research Institutes, Miaoli County, Taiwan, R.O.C
8 Bureau of National Health Insurance, Taipei, Taiwan, R.O.C
9 Institute of BioMedical Informatics, School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C
10 Institute of Information Science, Academia Sinica, Taipei, Taiwan, R.O.C
International Journal of Health Geographics 2009, 8:26 doi:10.1186/1476-072X-8-26
Published: 7 May 2009Additional files
Additional file 1:
Model parameters used in the Python script. Theses parameters used for automatic estimation of daily average concentration by Kriging method.
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Additional file 2:
Cross-validation of Kriging prediction. Cross-validation of Kriging prediction was measured by average prediction error (PE) and root mean square standardized (RMSS).
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Additional file 3:
an illustration of 10% increase of PM10. The 10% increase of air pollutant, PM10 was shown as an example to express the elevation of concentration in our effect's calculation.
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Additional file 4:
GAM model. The full models of GAM were listed. Model 1 was a single pollutant model. Model 2 was a four pollutants model.
Format: PDF Size: 85KB Download file
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