skip to main content

Interaksi Antarwilayah dan Sebaran Covid-19 di Provinsi Kalimantan Barat

*Syaiful Muazir orcid scopus  -  Program Studi Arsitektur, Fakultas Teknik, Universitas Tanjungpura, Indonesia
L Lestari  -  Program Studi Arsitektur, Fakultas Teknik, Universitas Tanjungpura, Indonesia
Muhammad Ridha Alhamdani  -  Program Studi Arsitektur, Fakultas Teknik, Universitas Tanjungpura, Indonesia
Muhammad Nurhamsyah  -  Program Studi Arsitektur, Fakultas Teknik, Universitas Tanjungpura, Indonesia
Open Access Copyright (c) 2021 Jurnal Wilayah dan Lingkungan
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Citation Format:
Abstract

Covid-19 is a disease that attacks the respiratory tract that began to be identified in Wuhan, China. WHO then announced the condition as a pandemic that quickly spread throughout the world. The rapid spread of the Coronavirus Pandemic (COVID-19) also occurred in West Kalimantan, Indonesia. In a spatial-temporal perspective, the spread of infectious diseases can be happened by the interconnectivity or interaction between areas, populations, and transportation facilities that facilitate community mobility. This research aims to describe the interactions between regions in West Kalimantan and the relation to the spread of the Covid-19 pandemic. The method used centrality measurement and cluster analysis, where the results of these calculations are then described in line with the distribution of the Covid-19 case in West Kalimantan. From the justification, areas with high centrality in the network configuration tend to have the most confirmed cases compared to other areas. The character of these areas tends to be the main entrance (air/port), the provincial capital, and the hub area in West Kalimantan, which is also included as the same cluster. Another interesting finding is that areas with low centrality, and included in the same cluster, have several people under surveillance which is quite large compared to the previous cluster. These areas tend to have a dense population and are directly related to the Provincial Capital and neighboring countries (border).

Note: This article has supplementary file(s).

Fulltext View|Download |  Copyright Transfer Agreement
Copyright Transfer Agreement
Subject
Type Copyright Transfer Agreement
  Download (1MB)    Indexing metadata
Keywords: areas; Covid-19; West Kalimantan; interaction

Article Metrics:

  1. Bajardi, P., Poletto, C., Ramasco, J. J., Tizzoni, M., Colizza, V., & Vespignani, A. (2011). Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLOS ONE, 6(1), 1–8. doi: 10.1371/journal.pone.0016591
  2. Borgatti, S. (1995). Centrality and AIDS. Connections, 18(1), 111–113
  3. Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). UCINET for windows: Software for social network analysis
  4. Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing social networks (First Edit). SAGE Publications Ltd
  5. Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., Xia, J., Yu, T., Zhang, X., & Zhang, L. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet, 395(10223), 507–513. doi: 10.1016/S0140-6736(20)30211-7
  6. Dinas Kesehatan Provinsi Kalimantan Barat. (2020). Jumlah terpapar Covid-19 di Kalimantan Barat. https://dinkes.kalbarprov.go.id/covid-19/
  7. Downs, J. A., & Horner, M. W. (2012). Probabilistic potential path trees for visualizing and analyzing vehicle tracking data. Journal of Transport Geography, 23, 72–80. doi: 10.1016/j.jtrangeo.2012.03.017
  8. Dunn, F. L. (1958). Pandemic influenza in 1957: Review of international spread of new asian strain. Journal of the American Medical Association, 166(10), 1140–1148. doi: 10.1001/jama.1958.02990100028006
  9. Edmonds, E. A. (2007). Reflections on the nature of interaction. CoDesign International Journal of CoCreation in Design and the Arts, 3(3), 139–143. doi: 10.1080/15710880701251427
  10. Glasson, J., & Marshall, T. (2007). Regional planning. Routledge
  11. Grais, R. F., Ellis, J. H., & Glass, G. E. (2003). Assessing the impact of airline travel on the geographic spread of pandemic influenza. European Journal of Epidemiology, 18(11), 1065–1072. doi: 10.1023/a:1026140019146
  12. Guan, W., Ni, Z., Hu, Y., Liang, W., Ou, C., He, J., Liu, L., Shan, H., Lei, C., Hui, D. S. C., Du, B., Li, L., Zeng, G., Yuen, K. Y., Chen, R., Tang, C., Wang, T., Chen, P., Xiang, J., … Zhong, N. (2020). Clinical characteristics of coronavirus disease 2019 in China. New England Journal of Medicine, 382(18), 1708–1720. doi: 10.1056/NEJMoa2002032
  13. Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. University of California, Riverside. http://faculty.ucr.edu/~hanneman/
  14. Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., Cheng, Z., Yu, T., Xia, J., Wei, Y., Wu, W., Xie, X., Yin, W., Li, H., Liu, M., … Cao, B. (2020). Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet, 395(10223), 497–506. doi: 10.1016/S0140-6736(20)30183-5
  15. Inaida, S., Yasui, Y., Tada, Y., Taniguchi, K., & Okabe, N. (2011). Geographic trends and spread of the pandemic (H1N1) 2009 in the metropolitan areas of Japan studied from the national sentinel data. Japanese Journal of Infectious Diseases, 64(6), 473–481
  16. Kadi, N., & Khelfaoui, M. (2020). Population density, a factor in the spread of COVID-19 in Algeria: statistic study. Bulletin of the National Research Centre, 44(1), 138. doi: 10.1186/s42269-020-00393-x
  17. Kang, D., Choi, H., Kim, J.-H., & Choi, J. (2020). Spatial epidemic dynamics of the COVID-19 outbreak in China. International Journal of Infectious Diseases, 94, 96–102. doi: 10.1016/j.ijid.2020.03.076
  18. Kubota, Y., Shiono, T., Kusumoto, B., & Fujinuma, J. (2020). Multiple drivers of the COVID-19 spread: The roles of climate, international mobility, and region-specific conditions. PLOS ONE, 15(9), 1–15. doi: 10.1371/journal.pone.0239385
  19. Lau, H., Khosrawipour, V., Kocbach, P., Mikolajczyk, A., Ichii, H., Zacharski, M., Bania, J., & Khosrawipour, T. (2020). The association between international and domestic air traffic and the coronavirus (COVID-19) outbreak. Journal of Microbiology, Immunology and Infection, 53(3), 467–472. doi: 10.1016/j.jmii.2020.03.026
  20. Lawyer, G. (2016). Measuring the potential of individual airports for pandemic spread over the world airline network. BMC Infectious Diseases, 16(1), 70. doi: 10.1186/s12879-016-1350-4
  21. Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., Xing, X., Xiang, N., Wu, Y., Li, C., Chen, Q., Li, D., Liu, T., Zhao, J., Liu, M., … Feng, Z. (2020). Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. New England Journal of Medicine, 382(13), 1199–1207. doi: 10.1056/NEJMoa2001316
  22. Lobo-Guerrero, L. (2012). Connectivity as the strategization of space – the case of the Port of Hamburg. Distinktion: Scandinavian Journal OfSocial Theory, 13(3), 310–321. doi: 10.1080/1600910X.2012.697860
  23. Merler, S., & Ajelli, M. (2010). The role of population heterogeneity and human mobility in the spread of pandemic influenza. Proceedings. Biological Sciences, 277(1681), 557–565. doi: 10.1098/rspb.2009.1605
  24. Pemerintah Provinsi Kalimantan Barat. (2020). Satu data Kalbar. http://data.kalbarprov.go.id
  25. Ratcliffe, R. (2020). First coronavirus cases confirmed in Indonesia amid fears nation is ill-prepared for an outbreak. The Guardian. https://www.theguardian.com/world/2020/mar/02/first-coronavirus-cases-confirmed-in-indonesia-amid-fears-nation-is-ill-prepared-for-outbreak
  26. Reuters. (2020). Indonesia confirms first cases of coronavirus". Bangkok Post. Retrieved from https://www.bangkokpost.com/world/1869789/indonesia-confirms-first-cases-of-coronavirus
  27. Scott, N., Baggio, R., & Cooper, C. (2008). Network analysis and tourism: From theory to practice. Channel View Publications
  28. Sokol, M. (2009). Regional connectivity. In R. Kitchin & N. Thrift (Eds.), International Encyclopedia of Human Geography. Elsevier
  29. Staeheli, U. (2012). Listing the global: dis/connectivity beyond representation? Distinktion: Journal of Social Theory, 13(3), 233–246. doi: 10.1080/1600910X.2012.724646
  30. Tuncer, N., & Le, T. (2014). Effect of air travel on the spread of an avian influenza pandemic to the United States. International Journal of Critical Infrastructure Protection, 7(1), 27–47. doi: 10.1016/j.ijcip.2014.02.001
  31. Valleron, A.-J., Cori, A., Valtat, S., Meurisse, S., Carrat, F., & Boëlle, P.-Y. (2010). Transmissibility and geographic spread of the 1889 influenza pandemic. Proceedings of the National Academy of Sciences of the United States of America, 107(19), 8778–8781. doi: 10.1073/pnas.1000886107
  32. Vega, A. (2012). Accessibility and the local concentration of economic activity: A case study for county Galway. Irish Geography, 45(1), 25–44. doi: 10.1080/00750778.2012.729917
  33. Wang, C., Horby, P. W., Hayden, F. G., & Gao, G. F. (2020). A novel coronavirus outbreak of global health concern. The Lancet, 395(10223), 470–473. doi: 10.1016/S0140-6736(20)30185-9
  34. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge University Press
  35. Xie, Z., Qin, Y., Li, Y., Shen, W., Zheng, Z., & Liu, S. (2020). Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors. Science of The Total Environment, 744, 140929. doi: 10.1016/j.scitotenv.2020.140929
  36. Zhao, S., & Chen, H. (2020). Modeling the epidemic dynamics and control of COVID-19 outbreak in China. Quantitative Biology, 8(1), 11–19. doi: 10.1007/s40484-020-0199-0

Last update:

No citation recorded.

Last update:

No citation recorded.