Climatic Factors Affecting Influenza Cases in Southern Thailand

This study investigated climatic factors associated with influenza cases in Southern Thailand. The main aim for use regression analysis to investigate possible causual relationship of climatic factors and variability between the border of the Andaman Sea and the Gulf of Thailand. Southern Thailand had the highest Influenza incidences among four regions (i.e. north, northeast, central and southern Thailand). In this study, there were 14 climatic factors: mean relative humidity, maximum relative humidity, minimum relative humidity, rainfall, rainy days, daily maximum rainfall, pressure, maximum wind speed, mean wind speed, sunshine duration, mean temperature, maximum temperature, minimum temperature, and temperature difference (i.e. maximum – minimum temperature). Multiple stepwise regression technique was used to fit the statistical model. The results indicated that the mean wind speed and the minimum relative humidity were positively associated with the number of influenza cases on the Andaman Sea side. The maximum wind speed was positively associated with the number of influenza cases on the Gulf of Thailand side.

Authors:

• S. Youthao
• M. Jaroensutasinee
• K. Jaroensutasinee

Keywords:

• Influenza
• Climatic Factor
• Relative Humidity
• Rainfall
• Pressure
• Wind Speed
• sunshine duration
• Temperature
• Andaman Sea
• Gulf of Thailand
• Southern Thailand.

References:

[1] N. M. Ferguson, A. P. Galvani, and R. M. Bush, "Ecological and
immunological determinants of influenza evolution," Nature, vol. 422,
pp. 428-433, 2003.
[2] J. P. Fox, C. E. Hall, M. K. Cooney and H. M. Foy, "Influenza virus
infections in Seattle families, 1975-1979. I. Study design, methods and
the occurrence of infections by time and age," Am. J. Epidemiol., vol.
116, pp. 212-227, 1982.
[3] A. Flahault, F. V. Dias, P. Chaberty, K. Esteves, A. J. Valleron, and D.
Lavanchy, "Flu Net as a tool for global monitoring of influenza on the
web," J. Am. Med. Ass., vol. 280, pp. 1330-1332, 1998.
[4] N. J. Cox and K. Subbarao, "Global epidemiology of influenza: past and
present," An. Rev. Med., vol. 51, pp. 407-421, 2000. PubMed ID:
20236288.
[5] General Accounting Office, "National Technical Information Service
Springfield report", Virginia, Washington, DC, 2005.
[6] Bureau of Epidemiology, "Reported online influenza cases,"
www.cdc.moph.go.th, Department of Disease Control, Ministry of
Public Health Thailand, 2006, unpublished.
[7] H. Sahai and M. Ageel, The Analysis of Variance: Fixed, Random and
Mixed Models. Boston: Birkhauser, 2000.
[8] J. D. Jobson, Applied Multivariate Data Analysis Volume 1: Regression
and Experimental Design. New York: Springer-Verlag, 1991.
[9] A. S. Mugglin, N. Cressie and I. Gemmell, "Hierarchical statistical
modeling of influenza epidemic dynamics in space and time," Stat. Med.,
vol. 21, pp. 2703-2721, 2002.
[10] G. Pyle, "Applied Medical Geography," in Scribe Series in Geography,
R. Lonsdale, Ed. New York: V.H Winston & Sons, 1979.
[11] A. Cliff, P. Haggett and J. Ord, Spatial Aspects of Influenza Epidemics,
London: Page Bros, 1986.
[12] R. E. Hope-Simpson, The Transmission of Epidemic Influenza. New
York: Plenum Press, 1992.
[13] R. Parmenter and E. P. Yadav, "Incidence of Plague Associated with
Increased Winter-Spring Precipitation in New Mexico," Am. Soc. Trop.
Med. Hygiene, vol. 61 (5), pp. 814-821, 1999.
[14] M. Meade and R. Earickson, Medical Geography, 2nd ed., New York:
The Guilford Press, 2000.
[15] C. A. Mills, Medical Climatology. Baltimore: Charles C. Thomas, 1939.
[16] S. Licht, Medical Climatology. S. Licht, ed. New Haven: Elizabeth Licht
Publisher, 1964.