|
UPSI Digital Repository (UDRep)
|
|
| ||||||||||||||||
| Abstract : |
| Disease mapping is the visual representation of the geographical distribution which give an overview info about the incidence of disease within a population through spatial epidemiology data. Based on the result of map, it helps in monitoring and planning resource needs at all levels of health care and designing appropriate interventions, tailored towards areas that deserve closer scrutiny or communities that lead to further investigations to identify important risk factors. Therefore, the choice of statistical model used for relative risk estimation is important because production of disease risk map relies on the model used. This paper proposes Besag-York-Mollie (BYM) model to estimate the relative risk for Malaria in Malaysia. The analysis involved using the number of Malaria cases that obtained from the Ministry of Health Malaysia. The outcomes of analysis are displayed through graph and map, including Malaria disease risk map that constructed according to the estimation of relative risk. The distribution of high and low risk areas of Malaria disease occurrences for all states in Malaysia can be identified in the risk map. |
| References |
1. Goovaerts, P., Gebreab, S. How does Poisson kriging compare to the popular BYM model for mapping disease risks? (Open Access) (2008) International Journal of Health Geographics, 7, art. no. 6. Cited 32 times. doi: 10.1186/1476-072X-7-6 View at Publisher 2. Hassan, H., Shohaimi, S., Hashim, N.R. Risk mapping of dengue in Selangor and Kuala Lumpur, Malaysia (2013) Geospatial Health, 7 (1), pp. 21-25. Cited 19 times. http://www.geospatialhealth.unina.it/articles/v7i1/gh-v7i1-03-hassan.pdf 3. Lawson, A.B., Williams, F.L.R. (2001) An Introductory Guide to Disease Mapping. Cited 62 times. (Chichester, UK: John Wiley and Sons, Ltd) 4. Lawson, A.B., Browne, W.J., Vidal Rodeiro, C.L. Disease Mapping with WinBUGS and MLwiN (2004) Disease Mapping with WinBUGS and MLwiN, pp. 1-279. Cited 117 times. http://onlinelibrary.wiley.com/book/10.1002/0470856068 ISBN: 978-047085606-2; 0470856041; 978-047085604-8 doi: 10.1002/0470856068 5. Lawson, A.B., Biggeri, A.B., Boehning, D., Lesaffre, E., Viel, J.-F., Clark, A., Schlattmann, P., (...), Divino, F. Disease mapping models: An empirical evaluation: Disease mapping collaborative group (2000) Statistics in Medicine, 19 (17-18), pp. 2217-2241. Cited 142 times. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0258 doi: 10.1002/1097-0258(20000915/30)19:17/18<2217::AID-SIM565<3.0.CO;2-E 6. Lekdee, K., Sammatat, S., Boonsit, N. (2014) International Journal of Medical, Health, Pharmaceutical and Biomedical Engineering, 8. 7. Of Health Malaysia, M. (2013) Management Guidelines of Malaria in Malaysia 8. Mohamad Imam Ma'Arof, S.H., Samat, N.A. (2014) Journal of Science and Mathematics JSM in press Print 9. Mohamad Imam Ma'Arof, S.H., Samat, N.A. (2014) Journal of Science and Mathematics JSM in press Print 10. Samat, N.A., Percy, D.F. Vector-borne infectious disease mapping with stochastic difference equations: An analysis of dengue disease in Malaysia (2012) Journal of Applied Statistics, 39 (9), pp. 2029-2046. Cited 12 times.doi: 10.1080/02664763.2012.700450 11. Spiegelhalter, D. (2003) WinBUGS User Manual Version 1.4. Cited 1415 times. (Cambridge, UK: MRC Biostatistics Unit) |
| This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials. You may use the digitized material for private study, scholarship, or research. |