Modeling Annual Parasite Incidence of Malaria in Indonesia of 2017 using Spatial Regime
Anik Djuraidah(1*), Pika Silvianti(2), Bimandra Djaafara(3), Siti Nur Laila(4)
(1) Departement of Statistics, Bogor Agricultural University, Kampus IPB Dramaga, West Java, Indonesia.
(2) Departement of Statistics, Bogor Agricultural University, Kampus IPB Dramaga, West Java, Indonesia.
(3) Eijkman Institute for Molecular Biology, Jakarta, Indonesia
(4) Departement of Statistics, Bogor Agricultural University, Kampus IPB Dramaga, West Java, Indonesia.
(*) Corresponding Author
Abstract
Malaria is an infectious disease caused by the Plasmodium parasite and transmitted through infected female Anopheles mosquitoes. The morbidity of malaria is determined by Annual Parasite Incidence (API) per year. A region with high malaria cases can spread malaria to other regions. Therefore, the purpose of this study is to determine the spatial regimes and factors that significantly influence the spread of malaria in Indonesia of 2017. Spatial regime is a method obtained by clustering the coefficient values from the well-known method in modeling spatial varying relationship namely geographically weighted regression (GWR). The data used in this study are malaria Passive Case Detection (PCD) from Puskesmas throughout Indonesia in 2017. The results show three groups which can be classified as regencies/cities with low, medium moderate and high API, while slide positivity rate and annual blood examination are predictors who influent API numbers in Indonesia significantly.
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Anselin L. (1988). Spatial Econometrics: method and models. Dodrecht: Kluwer Academic Publishers.
Departemen Kesehatan RI. (2010). Riset Kesehatan Dasar, RISKESDAS 2010. Jakarta: Badan Penelitian dan Pengembangan Kesehatan, Kementerian Kesehatan RI.
Ellyvon P. (2020). Tren Kasus Malaria Meningkat, Ibu Hamil dan Balita Perlu Waspada. Jakarta: KOMPAS (https://www.kompas.com/sains/read/2020/08/23/115611923/tren-kasus-malaria-meningkat-ibu-hamil-dan-balita-perlu-waspada?page=all accessed 21 june 2021)
Fotheringham A.S., Brunsdon C., & Chartlon M. (2002). Geographically Weighted Regression: the analysis of spatially varying relationships. West Sussex: John Wiley & Sons, LTD.
Gwitira I., Mukonoweshuro M., Mapako G., Shekede M.D., Chirenda J., & Mberikunashe J. (2020). Spatial and spatio-temporal analysis of malaria cases in Zimbabwe. Infect Dis Poverty, 9:146 (https://doi.org/10.1186/s40249-020-00764-6 pp 1-14).
Hakim L. (2011). Malaria: Epidemiologi dan Diagnosis. ASPIRATOR, Jurnal Penelitian Penyakit Tular Vektor-Journal
of Vector-borne Disease Studies, 3(2), 107-116.
Johnson R., & Wichern D. (2007). Applied Multivariate Statistical Analysis. New Jersey: Prentice Hall.
Juhairiyah, Waris L., & Hairani B. (2014). Knowledge and behaviour society against malaria in Malinau District East Kalimantan. Jurnal BUSKI, 5(1), 7-16.
[KEMENKES RI] Kementrian Kesehatan Republik Indonesia. (2016). Inilah Fakta Keberhasilan Pengendalian Malaria (https://www.kemkes.go.id/article/view/1605020-0003/inilah-fakta-keberhasilan-pengendalian-malaria.html accessed 19 June 2021)
______________ [KEMENKES RI] Kementrian Kesehatan Republik Indonesia. (2017). Profil kesehatan Indonesia. Jakarta: KEMENKES RI.
______________. (2019). Buku Saku Tatalaksana Kasus Malaria. Jakarta: Subdit Malaria Direktorat P2PTVZ, KEMENKES.
Lestari A., & Salamah M. (2014). Faktor-faktor yang mempengaruhi penyakit malaria pada ibu hamil di Provinsi Nusa Tenggara Barat, Nusa Tenggara Timur, Maluku, Maluku Utara, Papua, dan Papua Barat. JURNAL SAINS DAN SENI POMITS, 3(2), 2337-3520.
Madhulatha T.S. (2012). An overview on clustering techniques based on elbow method and k-means in WSN. IOSR Journal of Engineering, 2(4), 719-725 .
Mendenhall W, Sincich T. (2014). A Second Course in Statistics: Regression Analysis. Seventh Edition. London: Pearson Education Limited.
Miranti I., Djuraidah A., & Indahwati. (2015). Modeling of malaria prevalence in Indonesia with geographically weighted regression. KESMAS, 2(9), 109-118.
Muharom A. (2016). Analisis kecepatan penyembuhan penderita malaria dengan menggunakan regresi Cox [skripsi]. Bogor: Institut Pertanian Bogor.
Nababan R., & Umniyati S.R. (2018). Faktor lingkungan dan malaria yang memengaruhi kasus malaria di daerah endemis tertinggi di Jawa Tengah: analisis sistem informasi geografis. BKM (Journal of Community Medicine and Public Health), 34(1), 11-18.
[PUSDATIN KEMENKES RI] Pusat Data dan Informasi Kementrian Kesehatan Republik Indonesia. (2016). InfoDATIN Malaria. Jakarta: KEMENKES RI.
Sopi I.I.P.B., & Patanduk Y. (2015). Malaria pada Anak di Bawah Umur Lima Tahun. Jurnal Vektor Penyakit, 9(2), 65–72.
Siswanto, Aidi M.N., & Djuraidah A. (2017). Conditional Autoregressive (CAR) Modeling Uses Weighted Matrix to First and Second Order (Case Study: Malaria Disease in Papua Province). International Journal of Engineering and Management Research, 7(4), 297-301.
Sunarsih E., Nurjazuli, & Sulistyani. (2009). Faktor risiko lingkungan dan perilaku yang berkaitan dengan kejadian malaria di Pangkalbalam Pangkalpinang. Jurnal Kesehatan Lingkungan Indonesia, 8(1), 1-9.
[WHO] World Health Organization. (2018). World Malaria Report 2018. Geneva: World Health Organization.
Yeshiwondim A.K., Gopal S., Hailemariam A.T., Dengela D.O., & Patel H.P. (2009). Spatial analysis of malaria incidence at the village level in areas with unstable transmission in Ethiopia. International Journal of Health Geographics, 8:5 (https://doi:10.1186/1476-072X-8-5).
Zhang W., Wang L., Fang L., Ma J., Xu Y., Jiang J., Hui F., Wang J., Liang S., Yang H., & Cao W. (2008). Spatial analysis of malaria in Anhui province, China. Malaria Journal, 7:206 (https://doi:10.1186/1475-2875-7-206).
Zhao X., Thanapongtharm W., Lawawirojwong S., Wei C., Tang Y., Zhou Y., Sun X., Cui L., Sattabongkot J., & Kaewkungwal J. (2020). Malaria Risk Map Using Spatial Multi-Criteria Decision Analysis along Yunnan Border During the Pre-elimination Period. Am. J. Trop. Med. Hyg., 103(2), 793–809 (https://doi:10.4269/ajtmh.19-0854).
DOI: https://doi.org/10.22146/ijg.53290
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Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)
ISSN 2354-9114 (online), ISSN 0024-9521 (print)
IJG STATISTIC