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Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling

Author

Listed:
  • Mokhamad Nur Cahyadi

    (Geomatics Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
    Research Center Science Technology of Marine and Earth, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Hepi Hapsari Handayani

    (Geomatics Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • IDAA Warmadewanthi

    (Department of Environmental Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Catur Aries Rokhmana

    (Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta 5581, Indonesia)

  • Soni Sunarso Sulistiawan

    (Department of Anesthesiology and Reanimation, Faculty Of Medicine, Universitas Airlangga-Dr. Soetomo Hospital, Surabaya 60132, Indonesia)

  • Christrijogo Sumartono Waloedjo

    (Master Program in Disaster Management, Postgraduate School, Universitas Airlangga-Dr. Soetomo Hospital, Surabaya 60132, Indonesia)

  • Agus Budi Raharjo

    (Department of Informatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Endroyono

    (Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Mohamad Atok

    (Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Shilvy Choiriyatun Navisa

    (Geomatics Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Mega Wulansari

    (Geomatics Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia)

  • Shuanggen Jin

    (Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China)

Abstract

The coronavirus disease of 2019 (COVID-19) pandemic is currently a global challenge, with 210 countries, including Indonesia, seeking to minimize its spread. Therefore, this study aims to determine the spatiotemporal spread pattern of this virus in Surabaya using various data on confirmed cases from 28 April to 26 October 2021. It also aims to determine the relationship between pollutant parameters, such as carbon monoxide (CO), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and ozone (O 3 ), as well as the government’s high social restrictions policy in Java-Bali. Several methods, such as the weighted mean center, directional distribution, Getis–Ord Gi*, Moran’s I, and geographically weighted regression, were used to identify the spatial spread pattern of the virus. The weighted mean center indicated that the epicenter location of the outbreak moved randomly. The directional distribution demonstrated a decrease of 21 km 2 at the end of the study phase, which proved that its spread has significantly reduced in Surabaya. Meanwhile, the Getis–Ord Gi* results demonstrated that the eastern and southern parts of the study region were highly infected. Moran’s I demonstrate that COVID-19 cases clustered during the spike. The geographically weighted regression model indicated a number of influence zones in the northeast, northwest, and a few in the southwest parts at the peak of R 2 0.55. The relationship between COVID-19 cases and air pollution parameters proved that people living at the outbreak’s center have low pollution levels due to lockdown. Furthermore, the lockdown policy reduced CO, NO 2 , SO 2 , and O 3 . In addition, increase in air pollutants; namely, NO 2 , CO, SO 2 and O 3 , was recorded after 7 weeks of lockdown implementation (started from 18 August).

Suggested Citation

  • Mokhamad Nur Cahyadi & Hepi Hapsari Handayani & IDAA Warmadewanthi & Catur Aries Rokhmana & Soni Sunarso Sulistiawan & Christrijogo Sumartono Waloedjo & Agus Budi Raharjo & Endroyono & Mohamad Atok & , 2022. "Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling," IJERPH, MDPI, vol. 19(3), pages 1-20, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:3:p:1614-:d:739078
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    References listed on IDEAS

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    1. Guojun He & Yuhang Pan & Takanao Tanaka, 2020. "COVID-19, City Lockdowns, And Air Pollution: Evidence from China," HKUST IEMS Working Paper Series 2020-72, HKUST Institute for Emerging Market Studies, revised Mar 2020.
    2. Andy Haines & Markus Amann & Nathan Borgford-Parnell & Sunday Leonard & Johan Kuylenstierna & Drew Shindell, 2017. "Short-lived climate pollutant mitigation and the Sustainable Development Goals," Nature Climate Change, Nature, vol. 7(12), pages 863-869, December.
    3. Bin Wang & Wenzhong Shi & Zelang Miao, 2015. "Confidence Analysis of Standard Deviational Ellipse and Its Extension into Higher Dimensional Euclidean Space," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
    4. Arthur Getis & J. Keith Ord, 2010. "The Analysis of Spatial Association by Use of Distance Statistics," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 127-145, Springer.
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    1. Pavlov, Konstantin & Timiryanova, Venera & Yusupov, Kasim & Krasnoselskaya, Dina, 2022. "Анализ волн распространения Covid-19 в России [Analysis of Covid-19 wave distribution in Russia]," MPRA Paper 114637, University Library of Munich, Germany.

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