Determinants of Multidrug-Resistant Pulmonary Tuberculosis in Indonesia: A Spatial Analysis Perspective
Keywords:
Multidrug Resistant Tuberculosis, Tuberculosis, Binomial Negatif, Spatial Regression, Heterogeneity, Geographically Weighted Negative Binomial Regression
Abstract
Tuberculosis is caused by Mycobacterium Tuberculosis (MT). MT usually attacks the lungs and causes pulmonary-tuberculosis. Tuberculosis cases in Indonesia keep increasing over the years. The presence of Multidrug-Resistant Tuberculosis (MDR-TB) has been one of the main obstacles in eradicating tuberculosis because it couldn’t be cured using standard drugs. In fact, the success rate of MDR-TB treatment in 2019 at the global level was only 57 percent. Research on MDR-TB can be related to the spatial aspect because this disease can be transmitted quickly. This study aims to obtain an overview and model the number of Indonesia’s pulmonary MDR-TB cases in 2019 using the Geographically Weighted Negative Binomial Regression (GWNBR) method. The independent variables used in the model are population density, percentage of poor population, health center ratio per 100 thousand population, the ratio of health workers per 10 thousand population, percentage of smokers, percentage of the region with PHBS policies, and percentage of BCG immunization coverage. The finding reveals that the model forms 12 regional groups based on significant variables where GWNBR gives better results compared to NBR. The significant spatial correlation implies that the collaboration among regional governments plays an important role in reducing the number of pulmonary MDR-TB.
References
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Zulaikha, E. et al. (2018). Pemetaan dan analisis faktor-faktor yang mempengaruhi tuberkulosis menggunakan geographically
weighted regressionregress
relationships to socio-economic, demographic and household factors in northwest ethiopia. PloS one, 12(2):e0171800.
Anselin, L. (1988). Spatial econometrics: methods and models, volume 4. Springer Science & Business Media.
Anselin, L. and Rey, S. J. (2007). Perspectives on spatial data analysis. In Perspectives on spatial data analysis. Springer.
Breusch, T. S. and Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica: Journal
of the econometric society, pages 1287–1294.
Briassoulis, G., Karabatsou, I., Gogoglou, V., and Tsorva, A. (2005). Bcg vaccination at three different age groups: response and
effectiveness. Journal of Immune Based Therapies and Vaccines, 3(1):1–12.
Bustaman, U., Sofa, W. A., Larasati, D. N., Sari, A. K., Yuniarti, Saryono, Hidayah, Z., Oktaviana, S., Andriani, V. R., and Saryono
(2013). Penggunaan Metode GWR untuk Analisis Data Sosial dan Ekonomi (M. Romzi & U. Bustaman (eds.)). Badan Pusat
Statistik.
Cameron, A. C. and Trivedi, P. K. (2013). Regression analysis of count data, volume 53. Cambridge university press.
Chakaya, J. M., Harries, A. D., and Marks, G. B. (2020). Ending tuberculosis by 2030pipe dream or reality? International Journal
of Infectious Diseases, 92:S51–S54.
Chung-Delgado, K., Guillen-Bravo, S., Revilla-Montag, A., and Bernabe-Ortiz, A. (2015). Mortality among mdr-tb cases: comparison with drug-susceptible tuberculosis and associated factors. PloS one, 10(3):e0119332.
Collins, S. M. (2010). An application of geographically weighted poisson regression. PhD thesis, Memorial University of Newfoundland.
Da Silva, A. R. and Rodrigues, T. C. V. (2014). Geographically weighted negative binomial regressionincorporating overdispersion.
Statistics and Computing, 24(5):769–783.
Devi, A. U., Cahyo, K., and Shaluhiyah, Z. (2019). Faktor-faktor yang berhubungan dengan perilaku pasien tb mdr dalam pencegahan
penularan tb mdr di wilayah kerja puskesmas kota semarang. Jurnal Kesehatan Masyarakat (Undip), 7(1):442–452.
Fotheringham, A. S., Brunsdon, C., and Charlton, M. (2003). Geographically weighted regression: the analysis of spatially varying
relationships. John Wiley & Sons.
Gill, J., Gill, J. M., Torres, M., and Pacheco, S. M. T. (2019). Generalized linear models: a unified approach, volume 134. Sage
Publications.
Gomes, M. J. T. L., Cunto, F., and da Silva, A. R. (2017). Geographically weighted negative binomial regression applied to zonal
level safety performance models. Accident Analysis & Prevention, 106:254–261.
Gujarati, D. N. (2011). Econometrics by example, volume 1. Palgrave Macmillan New York.
Hapsari, B. A. P., Wulaningrum, P. A., and Rimbun, R. (2021). Association between smoking habit and pulmonary tuberculosis at
dr. soetomo general academic hospita. Biomolecular and Health Science Journal, 4(2):90–94.
Hilbe, J. M. (2011). Negative binomial regression. Cambridge University Press.
Irawansa, O. H. Y., Bhaskoro, Y., Maulana, A. R., and Setyawan, F. E. B. (2020). Model tatalaksana komprehensif tuberculosis
multidrug-resistant (tb-mdr) melalui pendekatan provider pelayanan kesehatan. CoMPHI Journal: Community Medicine and
Public Health of Indonesia Journal, 1(2):51–57.
Jenkins, H. E., Plesca, V., Ciobanu, A., Crudu, V., Galusca, I., Soltan, V., Serbulenco, A., Zignol, M., Dadu, A., Dara, M., et al.
(2013). Assessing spatial heterogeneity of multidrug-resistant tuberculosis in a high-burden country. European Respiratory Journal, 42(5):1291–1301.
Kemenkes RI (2020). Pokok-Pokok Renstra Kemenkes 2020-2024. Pokja Renstra Kemenkes 2020-2024.
Kurniawansyah, K. R. (2007). Efektifitas imunisasi bcg terhadap penyakit tuberkulosis paru pada anak di smf anak rsud dr. soebandi
jember.
Li, D., Ge, E., Shen, X., and Wei, X. (2016). Risk factors of treatment outcomes for multi-drug resistant tuberculosis in shanghai,
2009-2012. Procedia environmental sciences, 36:12–19.
Manjelievskaia, J., Erck, D., Piracha, S., and Schrager, L. (2016). Drug-resistant tb: deadly, costly and in need of a vaccine.
Transactions of the Royal Society of Tropical Medicine and Hygiene, 110(3):186–191.
Marks, S. M., Flood, J., Seaworth, B., Hirsch-Moverman, Y., Armstrong, L., Mase, S., Salcedo, K., Oh, P., Graviss, E. A., Colson,
P. W., et al. (2014). Treatment practices, outcomes, and costs of multidrug-resistant and extensively drug-resistant tuberculosis,
united states, 2005–2007. Emerging infectious diseases, 20(5):812.
Marselia, R. (2017). Hubungan antara lama terapi terhadap tingkat gejala depresi pada pasien tb paru di unit pengobatan penyakit
paru-paru pontianak. Jurnal Mahasiswa PSPD FK Universitas Tanjungpura, 3(3).
McCullagh, P. and Nelder, J. A. (2019). Generalized linear models. Routledge.
Mulyanto, H. (2014). Relationship five behavioral indicators and healthy living with tuberculosis multidrug-resistant. Jurnal Berkala
Epidemiologi, 2(3):355–367.
Mumtaz, T. and Utomo, A. P. (2018). Modelling the number of new pulmonary tuberculosis cases with geographically weighted
negative binomial regression method. Indonesian Journal of Statistics and Its Applications, 2(2):77–92.
Murniasih, E. (2007). Livana. hubungan pemberian imunisasi bcg dengan kejadian tuberkulosis paru pada anak balita di balai
pengobatan penyakit paru-paru ambarawa tahun 2007. Jurnal Kesehatan Surya Medika Yogyakarta.
Narasimhan, P., Wood, J., MacIntyre, C. R., and Mathai, D. (2013). Risk factors for tuberculosis. Pulmonary medicine, 2013.
Nelder, J. A. and Wedderburn, R. W. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General),
135(3):370–384.
Nisa, C., Aidi, M. N., and Sumertajaya, I. M. (2020). Geographically weighted negative binomial regression modeling of tuberculosis
cases with distribution evaluation.
Prakash, R., Kumar, D., Gupta, V. K., Jain, S., Chauhan, D. S., Tiwari, P. K., and Katoch, V. M. (2016). Status of multidrug resistant
tuberculosis (mdr-tb) among the sahariya tribe of north central india. Journal of Infection and Public Health, 9(3):289–297.
Pratama, W. (2015). Pemetaan dan pemodelan jumlah kasus penyakit tuberculosis (tbc) di provinsi jawa barat dengan pendekatan
geographically weighted negative binomial regression (gwnbr). Jurnal SainsDanSeniITS.
Pratiwi, L. P. S., Hendayanti, N. P. N., and Suniantara, I. K. P. (2020). Perbandingan pembobotan seemingly unrelated regression–
spatial durbin model untuk faktor kemiskinan dan pengangguran. Jurnal Varian, 3(2):51–64.
Rahajoe, N. N., Supriyatno, B., and Setyanto, D. B. (2010). Buku ajar respirologi anak edisi I. Badan Penerbit Ikatan Dokter Anak
Indonesia (IDAI).
Suryani, I., Yasin, H., and Kartikasari, P. (2021). Pemodelan jumlah kasus demam berdarah dengue (dbd) di jawa tengah dengan
geographically weighted negative binomial regression (gwnbr). Jurnal Gaussian, 10(1):136–148.
WHO (2020). Global tuberculosis report 2020. World Health Organization
Yang, Y., Zhou, C., Shi, L., Meng, H., and Yan, H. (2014). Prevalence and characterization of drug-resistant tuberculosis in a local
hospital of northeast china. International Journal of Infectious Diseases, 22:83–86.
Zuardy, M. A., Fadilah, M., and Roflin, E. (2020). Analisis Efektivitas Vaksin BCG Terhadap Pencegahan Kejadian Tuberkulosis
Pada Anak Di Puskesmas 7 Ulu Kota Palembang. PhD thesis, Sriwijaya University.
Zulaikha, E. et al. (2018). Pemetaan dan analisis faktor-faktor yang mempengaruhi tuberkulosis menggunakan geographically
weighted regressionregress
Published
2022-11-13
How to Cite
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N. L. Andini and S. Oktora, “Determinants of Multidrug-Resistant Pulmonary Tuberculosis in Indonesia: A Spatial Analysis Perspective”, Jurnal Varian, vol. 6, no. 1, pp. 35 - 48, Nov. 2022.
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