Distribution of Coronavirus Disease (Covid-19) in West Sumatra Province with Local Indicator of Spatial Association (LISA) Cluster Map
Abstract
The COVID-19 pandemic in West Sumatra Province indicates a greater number of cases and mortality. The spread of COVID-19 is related to the mobility of the population, so the potential for transmission between regions is difficult to control. This study aims to determine the local index used in evaluating the tendency for local spatial groupings and can show some form of spatial relationship. Spatial analysis were conducted on 2020 to analyze spatial distribution of Covid-19 in West Sumatera Province. Spatial relationship was assessed by Local Indicator of Spatial Association (LISA). Mapping can be done with the LISA cluster map. The data used is COVID-19 incidence data based on reports from district or city in West Sumatra Province in 4 June 2020. We used Open Geoda Software to analyze the spatial distribution. There is positive spatial autocorrelation and classification in hot spots, cold spots, and outliers in the spread of COVID-19 cases in West Sumatra Province. Hot spots were found in Padang City, Bukittinggi City, and Padang Panjang City. Cold spots also detected in several districts, that is West Pasaman, Pasaman, Payakumbuh, Solok, Padang Pariaman, Pariaman, Sawahlunto, and Sijunjung. The transmission of the COVID-19 case does not recognize regional boundaries, but the grouping of districts or cities based on regional vulnerability is important as part of local control efforts to allocate resources. Coordination and collaboration among local governments need to be strengthened in preventing transmission between regions and reducing the number of cases in vulnerable areas based on hot spots and cold spots from LISA cluster map. It’s necessary for intervention programs more focused and effectively.
Keywords: COVID-19, Mapping, Spatial, Vulnerability
Full Text:
PDFReferences
Adhisuwignjo, S., Imammuddin, A. M., & Astutik, S. (2012). The Spatial Modelling of Dengue Hemorrhagic Fever Incidence by using GIS in Malang City, Indonesia. European Journal of Scientific Research, 72, 447–459.
Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.
Anselin, L. (2019). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In Spatial analytical perspectives on GIS (pp. 111–126). Routledge.
Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2014). Hierarchical modeling and analysis for spatial data. CRC press.
Dray, S. (2011). A New Perspective about Moran’s Coefficient: Spatial Autocorrelation as a Linear Regression Problem. Moran. Geographical Analysis, 43(2), 127–141.
Fitri, W. (2020). Implikasi Yuridis Penetapan Status Bencana Nasional Pandemi Corona Virus Disease 2019 (COVID-19) Terhadap Perbuatan Hukum Keperdataan. Supremasi Hukum: Jurnal Kajian Ilmu Hukum, 9(1), 76–93.
Google. (2020). Community Mobility Reports.
Handayani, K. D. (2022). Masalah Kesehatan Mental di Tengah Pandemi Covid-19: Peningkatan Masalah Gangguan Kecemasan Dan Penanganannya Mental Health Problems in the Midst of the Covid-19 Pandemic. Contagion: Scientific Periodical Journal of Public Health and Coastal Health, 4(1), 56–66.
Hidayani, W. R. (2020). Faktor Faktor Risiko Yang Berhubungan Dengan COVID 19 : Literature Review | Hidayani | Jurnal Untuk Masyarakat Sehat (JUKMAS). Jurnal Untuk Masyarakat Sehat (JUKMAS), 4(2), 120–134. Retrieved from http://ejournal.urindo.ac.id/index.php/jukmas/article/view/1015/696
Isazadeh, V., Argany, M., Ghanbari, A., & Mohammadi, H. (2021). Temporal and spatial distribution modeling of corona virus spread (Case study: Qom and Mazandaran provinces). Environmental Management Hazards, 8(1), 81–98.
Kementrian Kesehatan RI. (2020). Pedoman Pencegahan dan Pengendalian Coronavirus Dieseas (COVID-19) (Revisi 4). Jakarta: Direktorat Jenderal Pencegahan dan Pengendalian Penyakit.
Masbiran Vivi Ukhwatul, K. (2020). Impact of the Covid-19 pandemic on west Sumatera tourism. Jurnal Pembangunan Nagari, 5(2), 148–164.
Nakhapakorn, K., & Jirakajohnkool, S. (2006). Temporal and spatial autocorrelation statistics of dengue fever.
Pemerintah Provinsi Sumatera Barat. (2020). Update Data Harian Kasus COVID-19.
Putra, M. R. B., Primawati, I., Putriyuni, A., & Hasni, D. (2022). Risiko Pribadi Penularan COVID-19 pada Masyarakat di Kota Padang, Sumatera Barat Tahun 2020. Jurnal Kedokteran Dan Kesehatan: Publikasi Ilmiah Fakultas Kedokteran Universitas Sriwijaya, 9(1), 29–42.
Rahmi, M. F., Prasetyo, P. S., Nurhabibah, R., Perdana, R., & Madjida, W. O. Z. (2021). Pengelompokkan Provinsi di Indonesia Berdasarkan Jumlah Kasus Covid-19 dan Fasilitas Kesehatan. Jurnal Aplikasi Statistika & Komputasi Statistik, 13(1), 47–56.
Salima, B. A., & Bellefon, M. D. (2018). Spatial autocorrelation indices. Handbook of Spatial Analysis: Theory Aplication with R, 51–68.
Saputro, D. R. S., Widyaningsih, P., Kurdi, N. A., & Hardanti, S. A. (2017). Local Indicator Of Spatial Association (LISA) Cluster Map untuk Identifikasi Penyebaran dan Pemetaan Penyakit Demam Berdarah Dengue (Dbd) di Jawa Tengah. In Seminar Matematika dan Pendidikan Matematika UNY. Yogyakarta.
Soehardi. (2020). Pengaruh Pandemik Covid-19 Terhadap Pendapatan Tempat Wisata dan Kinerja Karyawan Pariwisata di Jakarta. Jurnal Kajian Ilmiah, 1(1), 1–14. https://doi.org/10.31599/jki.v1i1.216
Susilo, A., Rumende, C. M., Pitoyo, C. W., Santoso, W. D., Yulianti, M., Herikurniawan, H., … Nelwan, E. J. (2020). Coronavirus disease 2019: Tinjauan literatur terkini. Jurnal Penyakit Dalam Indonesia, 7(1), 45–67.
Taufik, A., Harahap, S., Siregar, K. W., Hasibuan, Y. A., Fadilah, N., & Siregar, Y. H. (2022). Prevention Behavior of COVID -19 Transmission in Productive Age. Contagion: Scientific Periodical Journal of Public Health and Coastal Health, 4(2), 87–99.
World Health Organization. (2020a). Coronavirus disease (COVID-19) pandemic.
World Health Organization. (2020b). Novel Coronavirus (2019-nCoV): situation report, 1. Geneva PP - Geneva: World Health Organization.
Yang, W., Deng, M., Li, C., & Huang, J. (2020). Spatio-temporal patterns of the 2019-nCoV epidemic at the county level in Hubei Province, China. International Journal of Environmental Research and Public Health, 17(7), 2563.
Yuniarti, E., Indika, P. M., Dewata, I., Heldi, H., & Barlian, E. (2020). Komorbidity Mapping of COVID-19 Events in West Sumatera. Sumatra Journal of Disaster, Geography and Geography Education, 4(1), 11–16.
DOI: http://dx.doi.org/10.30829/contagion.v5i1.14959
Refbacks
- There are currently no refbacks.
Copyright (c) 2023 Yudi Pradipta, Defriman Djafri, Ade Suzana Eka Putri, Radian Ilmaskal
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.