Mortality Rate due to Malaria in Thailand

Authors

  • Wattanavadee SRIWATTANAPONGSE Biostatistics and Applied Statistics Research Unit, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200
  • Sukon PRASITWATTANASEREE Biostatistics and Applied Statistics Research Unit, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200
  • Surin KHANABSAKDI Biostatistics and Applied Statistics Research Unit, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200

Keywords:

Forecasting, Mortality, Multivariate regression, Malaria.

Abstract

Malaria has been a leading cause of morbidity and mortality in Thailand for many decades. The purpose of this study was to model and forecast malaria mortality rate in Thailand using death certificate reports. A retrospective analysis of the malaria mortality rate was conducted. Data were obtained from the national vital registration database for the 10-year period from 2000 to 2009, provided by the Ministry of the Interior and coded as cause-of-death using ICD-10 by the Ministry of Public Health. Multivariate regression was used for modeling and forecasting age-specific malaria mortality rates in Thailand. Malaria mortality increased with increasing age for each sex and was also higher in the Central and Northern provinces. The trends of malaria mortality remained stable in most age groups with decreases in others and decreases during ten-year period (2000 to 2009). Malaria mortality was higher in males and increase with increasing age. There is need of malaria control measures to remain on a sustained and long-term basis for the high malaria burden rate of Thailand.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biographies

Wattanavadee SRIWATTANAPONGSE, Biostatistics and Applied Statistics Research Unit, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200

I have been lecturer in Statistics at Department of Statistics, Faculty of Science, and Chiang Mai University since 1983. I am 55 years old. Now, I am Associated Professor in Statistics and leads a research group of Biostatistics and Applies Statistics Research Unit. My research is in the field of Epidemiology of Infection disease such as malaria, DHF, pneumonia and AIDS/HIV. A major focus is modeling and forecasting of disease incidence. Furthermore, I was interested in research field of mortality due to road traffic accident. I received bachelor degree in Mathematics Education from Prince of Songkla University (1979) and master degree in Applied Statistics from NIDA (1983), and I just finish the Ph.D. in Research Methodology from Prince of Songkla University (2010).

Sukon PRASITWATTANASEREE, Biostatistics and Applied Statistics Research Unit, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200

Biostatistics and Applied Statistics Research Unit

Surin KHANABSAKDI, Biostatistics and Applied Statistics Research Unit, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200

Biostatistics and Applied Statistics Research Unit

References

WHO, Malaria Bulletin 2008, Available at: http://www.who.int/mediacentre/factsheets/fs310/en/index.html.

World malaria report 2011, Available at: http://www.who.int/malaria/world_malaria_report_2011/en/.

S Wibulpolprasert. Thailand Health Profile 2005-2007. In: The War Veterans Organization of Thailand, Printing Press, Bangkok, 2007.

Online Resources, Available at: http://en.wikipedia.org/wiki/Provinces_of_Thailand.

National Statistics Office. 100th anniversary of population censuses in Thailand: Population and housing census, 2010.

W Sriwattanapongse, M Kuning and N Jansakul. Malaria in North-Western Thailand. Songklanakarin J. Sci. Technol. 2008; 30, 207-14.

W Sriwattanapongse and M Kuning. Modeling malaria incidence in North-Western. Chiang Mai J. Sci. 2009; 36, 403-10.

RD Lee and LR Carter. Modeling and forecasting U.S. Mortality Am. Stat. Assoc. 1992; 87, 659-71.

RD Lee and T Miller. Evaluating the performance of the Lee-Carter method for forecasting mortality. Demography 2001; 38, 537-49.

Z Butt and S Haberman. A Collection of R Functions for Fitting a Class of Lee-Carter Mortality Models using Iterative Fitting Algorithms. Sir John Cass Business School, London, 2009.

WN Venables, DM Smith and the R Development Core Team. An Introduction to R: Notes on R:A Programming Environment for Data Analysis and Graphics Version 2.6.2, 2008.

JAC Sterne, IR White, JB Carlin, M Spratt, P Royston, MG Kenward, AM Wood and JR Carpenter. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. Br. Med. J. 2009, DOI: 10.1136/bmj.b2393.

H Booth, J Maindonald and L Smith. Applying Lee-Carter under conditions of variable mortality decline. Popul. Stud. 2002; 56, 325-36.

A Delwarde, M Denuit and P Eirlers. Smoothing the Lee-Carter and Poisson log-bilinear models for mortality forecasting. Stat. Model. 2007; 7, 29-48.

Downloads

Published

2012-06-15

How to Cite

SRIWATTANAPONGSE, W., PRASITWATTANASEREE, S., & KHANABSAKDI, S. (2012). Mortality Rate due to Malaria in Thailand. Walailak Journal of Science and Technology (WJST), 9(2), 135–139. Retrieved from https://wjst.wu.ac.th/index.php/wjst/article/view/296