Coronavirus (COVID-19): Density risk mapping using Population and Housing Census of Malaysia 2010

Coronavirus (COVID-19): Pemetaan risiko kepadatan menggunakan data Banci Penduduk dan Perumahan Malaysia 2010

  • Yaakub Nur Faziera Centre for Spatially Integrated Digital Humanities , Faculty of Social Sciences and Humanities , Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia
  • Epa Ailis Elizabeth Department of Geography, School of Humanities, Universiti Sains Malaysia, Pulau Pinang, Malaysia
  • Chabo Danggat Centre for Spatially Integrated Digital Humanities , Faculty of Social Sciences and Humanities , Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia
  • Masron Tarmiji Centre for Spatially Integrated Digital Humanities , Faculty of Social Sciences and Humanities , Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia
Keywords: Aging population, population density, different age groups, census, COVID-19, Geographic Information Systems (GIS) & risk mapping


The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the Coronavirus Disease 2019 (COVID-19) is a newly discovered severe and contagious disease. Due to its seriousness, the rapid spread of the virus has awakened worldwide attention in a short time. Due to the scarcity of effective treatment options for the rising positive cases worldwide, the risk of COVID-19 is observed serious for the infected persons with chronic diseases as well as vulnerable populations including infants and aging groups. By applying the spatial-based solution tool of Geographic Information Systems (GIS), this paper aims to localize the spatial distribution of cumulative COVID-19 cases and the density of different age groups of all districts for both West and East Malaysia. The non-spatial data used in this research paper were the cumulative number of COVID-19 positive cases on 25th of January, 15th of February, 21st of March, 31st of March, 14th of April & 12th of May 2020 and the total number of population in Malaysia sourced from Population and Housing Census of Malaysia 2010. The population was divided into three (3) different age groups. The three (3) age groups indicate the level of population density of a district. While the spatial data were district boundaries across Malaysia. The results geovisualized that big cities with a high density of population such as the Federal Territory of Kuala Lumpur, Petaling, Johor Bahru, Kuching, Miri, Sibu and Kota Kinabalu experienced a high number of COVID-19 positive cases.


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How to Cite
Nur Faziera, Y., Ailis Elizabeth, E., Danggat, C., & Tarmiji, M. (2020). Coronavirus (COVID-19): Density risk mapping using Population and Housing Census of Malaysia 2010. GEOGRAFI, 8(2), 21-47.