Bayesian Conditional Autoregressive (CAR) dengan Model Localised dalam Menaksir Risiko Relatif DBD di Kota Makassar

Rusydah Khaerati Bio | Andi Kresna Jaya Bio
Article History

Submited : February 6, 2020
Published : February 2, 2022

Bayesian Conditional Autoregressive (CAR) is used in disease mapping because it is able to model relative risks by taking into account the smoothing of the estimated relative risk and entering spatial information to reduce the errors of the estimated relative risk parameters so that a more reliable relative risk model is obtained. In this study, the relative risk value of the spread of dengue fever will be calculated using Bayesian CAR with the localised model. These results were obtained using the OpenBUGS program and are illustrated in the 2016 dengue fever case data. Based on the model, mapping of dengue fever in Makassar can be identified in each district and shows that Makassar City is still very vulnerable to dengue fever.

References

  1. Sandra, T., Sofro, AU Muchlis., Suhartono, Martini, & Hadisaputro, S. Faktor-Faktor yang Berpengaruh terhadap Kejadian Demam Berdarah Dengue pada Anak Usia 6-12 Tahun Di Kecamatan Tembalang. Jurnal Epidemiologi Kesehatan Komunitas, 4 (1), 2019.
  2. Respati, T., Raksanegara, A., Djuhaeni, H., Sofyan, A., Agustian, D., Faridah, L. & Sukandar, H. Berbagai Faktor yang Mempengaruhi Kejadian DBD di Kota Bandung. Aspirator, 9 (2), 2017.
  3. Climate Data. Iklim Makassar. 2018. https://id.climate-data.org/asia/ indonesia/south-sulawesi/makassar-3646/. [Accessed online 29 April 2019].
  4. Geografis Kota Makassar. Wilayah Kota Makassar. 2019. https://makassarkota. go.id/geografis/. [Accessed online 30 Januari 2020].
  5. Hidrologi dan Klimatologi. Iklim Makassar. 2017. https://makassarkota. go.id/hidrologi-dan-klimatologi/. [Accessed online 30 Januari 2020].
  6. Samat, N.A. & Mey, L.W. Malaria Disease Mapping in Malaysia based on Besag-York-Mollie (BYM) Model. Journal of Physics: Conference Series IOP Conf. Series: Journal of Physics: Conf. Series 890 012167, 2017.
  7. Lee, D., Rushworth, A. & Sahu, S.A. Bayesian Localized Conditional Autoregressive Model for Estimating the Health Efects of Air Pollution. Biometrics, 70, 419-429, 2014.
  8. Lee, D. & Sarran, C. Controlling for Unmeasured Confounding and Spatial Misalignment in Long-Term Air Pollution and Health Studies. Environmetrics 26: 477-487, 2015.
  9. Sunengsih, N., Jaya, I.G.N.M., Zulhanif & Tantular, B. Bayesian Conditional Autoregressive (CAR) dalam Menaksir Resiko Relatif Diare di Kota Bandung. Jurnal Matematika dan Pendidikan Matematika: 21-26, 2016.
  10. Venkatesan, P., Srinivasan, R., & Dharuman. Bayesian Conditional Auto Regressive Model For Mapping Tuberculosis Prevalence In India. International Journal of Pharmaceutical Studies and Research, 3 (1), 1-3. 2012.
  11. Wakefield, J. Disease Mapping and Spatial Regression with Count Data. Biostatistics, 8 (2), 158-183, 2006.

Downloads

Download data is not yet available.
Fulltext
statcounter