Modelling the Number of Cases of Dengue Hemorragic Fever with Mixed Geographically Negative Binomial Regression in West Java Province
DOI:
https://doi.org/10.32628/IJSRSET196124Keywords:
Dengue hemorrhagic fever, GWNBR, MGWNBRAbstract
Dengue hemorrhagic fever (DHF) is an infectious disease caused by the dengue virus of the genus Flavivirus, which is transmitted by the bite of the Aedes Aegypti. Different regional demographics cause the number of DHF cases to differ in each region following by environmental conditions in the area. The model applied is GWNBR (Geographically Weigthed Negative Binomial Regression) due to count data outcome affected by geographical effect. In some instances not all in the GWNBR model have spatial effects, sometimes the estimate parameter are constant, so the GWNBR model can be developed using a mixed model to become MGWNBR. Determination of global and local parameters using the confidence interval. This study aims to analyze the factors that influence the number of dengue cases in West Java Province in 2015 using the MGWNBR approach. Based on the comparison of AIC values, the MGWNBR model has a smaller AIC value compared to the negative binomial regression model. The variables that significant globally are population density (X1) and health worker (X2)The variables that significant locally are number of health facilities (X3) PHBS (X4) and healthy homes (X5)
References
- [BPS] Badan Pusat Statistik Provinsi Jawa Barat. 2016. Provinsi Jawa Barat Dalam Angka. Pemerintah Provinsi Jawa Barat.
- [DINKES] Dinas Kesehatan Provinsi Jawa Barat. 2015. Profil Kesehatan Provinsi Jawa Barat. BPS Provinsi Jawa Barat.
- Evadianti E, Purhadi. 2014. Pemodelan Jumlah Kematian Ibu di Jawa Timur dengan Pendekatan Geographically Weigthed Negative Binomial Regression. Jurnal Seni dan Sains ITS. Vol 3 (2): 2337-3539.
- Fotheringham A, Brunsdon C, Charlton M. 2002. Geographically Weighted Regression. Chichester (UK) : John Wiley & Sons Ltd.
- Hilbe MJ. 2011. Negative Binomial Regression:2nd. New York (USA): Cambridge University Press.
- [Kemenkes] Kementrian Kesehatan Indonesia. 2014. Profil Kesehatan Indonesia 2014. Jakarta : Kemetrian Kesehatan Republik Indonesia.
- [Kemenkes] Kementrian Kesehatan Indonesia. 2015. Profil Kesehatan Indonesia 2015. Jakarta : Kemetrian Kesehatan Republik Indonesia.
- Kusuma AP, Sukendra DM. 2016. Analisis Spasial Kejadian DBD Berdasarkan Kepadatan Penduduk. Unnes Journal of Public Health. 5(2016).
- Mar’ah Z, Djuraidah A, Wigena AH. 2017. Pemodelan Regresi Terboboti Geografi Semiparametrik dengan Model Koregionalisasi. International Journal and Sciences: Basic and Applied Research. 34(2017):178-186.
- Muliansyah, Baskoro T. 2016. Analisis Pola Sebaran Demam Berdarah Dengue Terhadap Penggunaan Lahan Dengan Pendekatan Spasial di Kabupaten Banggai Provinsi Sulawesi Tengah Tahun 2011-2013. Journal of Information Systems for Public Health. 1(2016):47-54.
- Nakaya T, Fotheringham AS, Brunsdon C. 2005. Geographically Weigthed Poisson for disease association mapping. Statist. Med. 24(2005): 2696-2717.
- Pongoh F. 2015. Regresi Terboboti Geografis dan Regresi Terboboti Geografis Campuran. [tesis]. Bogor (ID) : Institut Pertanian Bogor.
- Respati T, Raksanegara A, Djuhaeni H, Sofyan A, Agustian D, Faridah L, Sukandar H. 2017. Berbagai Faktor yang Mempengaruhi Kejadian Demam Berdarah Dengue di Kota Bandung. ASPIRATOR.9(2017):91-96
- Ruliansyah A, Yuliasih Y, Ridwan W, Kusnandar AJ. 2017. Analisis Spasial Sebaran Demam Berdarah Dengue di Kota Tasikmalaya Tahun 2011 – 2015. ASPIRATOR. 9(2):85-90.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET

This work is licensed under a Creative Commons Attribution 4.0 International License.