Mortality Rate due to Malaria in Thailand
Keywords:Forecasting, Mortality, Multivariate regression, Malaria.
AbstractMalaria 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.
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.
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