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Spatial Analysis to Mitigate the Spread of Covid-19 Based on Regional Demographic Characteristics Mochamad Firman Ghazali; Anggun Tridawati; Mamad Sugandi; Aqilla Fitdhea Anesta; Ketut Wikantika
Forum Geografi Vol 35, No 1 (2021): July 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v35i1.12325

Abstract

COVID-19 is currently the hot topic of discussion by scientists because of its ability to quickly spread, in line with everyday human activities. One of the environmental factors related to climatic parameters, such as the air temperature, contributed to the spreading of COVID-19 in the last four months. Its distribution ability is no longer local as it successfully halts the important activities in many countries globally. This study aims to explain the opportunity of geospatial analysis in handling the COVID-19 distribution locally based on the characteristics of demographic data. Various data, including the confirmed positive for COVID-19, age-based population, and Landsat 8 satellite imagery data were used to determine the spatial characteristics of the COVID-19 distribution per September 2020 in Bandung, Indonesia. An inverse distance weighted (IDW), Moran's I index and local indicator spatial association (LISA), and a proposed ratio of the elderly population against the population with confirmed positive for COVID-19 (CoVE) were used as the approach to determine its distribution characteristics. The information derived from Landsat 8 satellite imagery, such as the residential area, surface temperature, and humidity based on the supervised classification, land surface temperature (LST), and the normalized difference water index (NDWI) was used to perform the analysis.  The results showed that the positive population of COVID-19 was concentrated in Bandung city. However, with a Moran's I value of 0.316, not all are grouped into the same category. There are only 8, 2, 5, and 3 districts categorized as HH, HL, LL, and LH. However, the areas with a large or small number of elderlies do not always correlate with the high number of confirmed positives for COVID-19. There are only 3, 1, and 3 districts classified as HH, HL, and LL. They were represented by the values of Moran's I, for about 0.057. The positive relationship between confirmed positive for COVID-19 and the built-up area, surface temperature, humidity, and the elderly population based on the coefficient of determination (R2) were 0.03, 0.28, 0.25, and 0.019, respectively. The study also shows that the vulnerability of those areas is relatively low. The study shows that the vulnerabilities in these areas are relatively low and the recommendation for COVID-19 widespread mitigation has to consider the demographic characteristics precisely in the large scale social restrictions (LSSR).
Co-Authors Abd. Rasyid Syamsuri Adhi Wibowo Adis Jayati Adriana Hiariej, Adriana Agung B. Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agung Budi Harto Agus Handoyo Harsolumakso Agus Sutanto Agus Sutanto Ahmad Luthfi Hadiyanto Akihiko Kondoh Aldyansyah, Muhammad Alex Tan Aminah Kastuari Anesta, Aqilla Fitdhea Anggun Tridawati Aqilla Fitdhea Anesta Armi Susandi Armi Susandi Ary Setijadi Prihatmanto Asep Saepuloh Asep Yusup Saptari Asmi M. Napitu Asmi M. Napitu Aswin Rahadian Bambang Widarsono Bobby S. Dipokusumo Dandy A. Novresiandi Darmawan S Darmawan S, Darmawan Dedi Irawadi Deni Suwardi Desti Ayunda Dudung M Hakim Dudung Muhally Hakim Dudung Muhally Hakim Fahmi, Muhammad Nurul Farah Nafisa Ariadji Fauziah, Afi Fenny M. Dwivany FENNY MARTHA DWIVANY Fitriani Agustin Ghazali, Mochamad Firman Ghozali, M. Firman Giasintha Stefani Golok Jaya, La Ode Muhammad Hary Nugroho Hary Nugroho Hasan Adi Nugraha Herru Lastiadi Setiawan Herru Lastiadi Setiawan Himasari Hanan Husna Nugrahapraja I Nyoman Dibia I NYOMAN RAI I Wayan Nuarsa Imam A. Sadisun Intan Fatmawati Irland Fardani Ishak H. Ismullah Jevon A. Telaumbanua Katmoko Ari Sambodo Katmoko Ari Sambodo, Katmoko Ari Kurdianto Kurdianto LILIK BUDIPRASETYO Lissa F. Yayusman Lissa Fajri Yayusman Luky Adrianto Lumbantobing, Marlonroi M. Angga Hadi Pratama M. Firman Ghozali Mamad Sugandi Marlonroi Lumbantobing Meitha, Karlia Mila Olivia Trianaputri Mirelva, Prima Rizky Mochamad Firman Ghazali Mochamad Firman Ghazali Muhammad Alsamtu Tita Sabila Pratama Suhartono Nengah Widiadnyana Nengah Widiadnyana Nisrina Sukriandi Prihanggo, Maundri Prila Ayu Dwi Prastiwi Purnama, Yustika Retno Dammayatri Rian Nurtyawan Riantini Virtriana S. Suliantara Saepuloh, Asep Sakti, Anjar Dimara Satria Bijaksana Satria Bijaksana Sayidah Sulma Shafarina Wahyu Trisyanti Sigit Nur Pratama Simarmata, nirmawana Soni Darmawan Sony Darmawan, Sony Sugandi, Mamad Sukristiyanti Sukristiyanti Sukristiyanti Sukristiyanti Suliantara Suliantara Supriadi A Supriadi A, Supriadi Susantoro, Tri Muji Suwardhi, Deni Tahjudil Witra Tan, Alex Tohir, Rizki Kurnia Tombayu A. Hidayat Topik Hidayat Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro Tri Muji Susantoro, Tri Muji Trianaputri, Mila Olivia Tridawati, Anggun Trika Agnestasia Tarigan Trilaksono, Nurjanna Joko Yayusman, Lissa Fajri Yudi Setiawan