Evaluation of Vulnerability Status of the Infection Risk to COVID-19 Using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA): A Case Study of Addis Ababa City, Ethiopia

Hizkel Asfaw; Shankar Karuppannan; Tilahun Erduno; Hussein Almohamad; Ahmed Abdullah Al Dughairi; Motrih Al-Mutiry; Hazem Ghassan Abdo

doi:10.3390/ijerph19137811

Evaluation of Vulnerability Status of the Infection Risk to COVID-19 Using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA): A Case Study of Addis Ababa City, Ethiopia

Int J Environ Res Public Health. 2022 Jun 25;19(13):7811. doi: 10.3390/ijerph19137811.

Authors

Hizkel Asfaw¹, Shankar Karuppannan², Tilahun Erduno¹, Hussein Almohamad^{3

4}, Ahmed Abdullah Al Dughairi³, Motrih Al-Mutiry⁵, Hazem Ghassan Abdo^{6

7

8}

Affiliations

¹ Department of Geomatics Engineering, School of Civil Engineering and Architecture, Adama Science and Technology University, Adama P.O. Box 1888, Ethiopia.
² Department of Applied Geology, School of Applied Natural Science, Adama Science and Technology University, Adama P.O. Box 1888, Ethiopia.
³ Department of Geography, College of Arabic Language and Social Studies, Qassim University, Burayda 51452, Saudi Arabia.
⁴ Department of Geography, Justus Liebig University of Giessen, 35390 Giessen, Germany.
⁵ Department of Geography, College of Arts, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
⁶ Geography Department, Faculty of Arts and Humanities, University of Tartous, Tartous P.O. Box 2147, Syria.
⁷ Geography Department, Faculty of Arts and Humanities, University of Damascus, Damascus P.O. Box 30621, Syria.
⁸ Geography Department, Faculty of Arts and Humanities, University of Tishreen, Lattakia P.O. Box 2237, Syria.

Abstract

COVID-19 is a disease caused by a new coronavirus called SARS-CoV-2 and is an accidental global public health threat. Because of this, WHO declared the COVID-19 outbreak a pandemic. The pandemic is spreading unprecedently in Addis Ababa, which results in extraordinary logistical and management challenges in response to the novel coronavirus in the city. Thus, management strategies and resource allocation need to be vulnerability-oriented. Though various studies have been carried out on COVID-19, only a few studies have been conducted on vulnerability from a geospatial/location-based perspective but at a wider spatial resolution. This puts the results of those studies under question while their findings are projected to the finer spatial resolution. To overcome such problems, the integration of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) has been developed as a framework to evaluate and map the susceptibility status of the infection risk to COVID-19. To achieve the objective of the study, data like land use, population density, and distance from roads, hospitals, bus stations, the bank, markets, COVID-19 cases, health care units, and government offices are used. The weighted overlay method was used; to evaluate and map the susceptibility status of the infection risk to COVID-19. The result revealed that out of the total study area, 32.62% (169.91 km²) falls under the low vulnerable category (1), and the area covering 40.9% (213.04 km²) under the moderate vulnerable class (2) for infection risk of COVID-19. The highly vulnerable category (3) covers an area of 25.31% (132.85 km²), and the remaining 1.17% (6.12 km²) is under an extremely high vulnerable class (4). Thus, these priority areas could address pandemic control mechanisms like disinfection regularly. Health sector professionals, local authorities, the scientific community, and the general public will benefit from the study as a tool to better understand pandemic transmission centers and identify areas where more protective measures and response actions are needed at a finer spatial resolution.

Keywords: COVID-19; GIS; MCDA; proximity analysis; weighted overlay.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19* / epidemiology
Decision Support Techniques
Disease Susceptibility
Ethiopia / epidemiology
Geographic Information Systems
Humans
SARS-CoV-2

Grants and funding

This project is funded by Princess Nourah bint Abdulrahman University Researches Supporting Project number (PNURSP2022R241), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. The article processing charge was funded by the Deanship of Scientific Research, Qassim University.