A district-level vulnerability assessment of next COVID-19 variant (Omicron BA.2) in Uttarakhand using quantitative SWOT analysis

Zainab Khan, Sk Ajim Ali (), Mohd Mohsin, Farhana Parvin, Syed Kausar Shamim and Ateeque Ahmad
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Zainab Khan: Aligarh Muslim University
Sk Ajim Ali: Aligarh Muslim University
Mohd Mohsin: Aligarh Muslim University
Farhana Parvin: Aligarh Muslim University
Syed Kausar Shamim: Aligarh Muslim University
Ateeque Ahmad: Aligarh Muslim University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 1, No 27, 657-686

Abstract: Abstract COVID-19 has had an impact on the entire humankind and has been proved to spread in deadly waves. As a result, preparedness and planning are required to better deal with the epidemic’s upcoming waves. Effective planning, on the other hand, necessitates detailed vulnerability assessments at all levels, from the national to the state or regional. There are several issues at the regional level, and each region has its own features. As a result, each region needs its own COVID-19 vulnerability assessment. In terms of climate, terrain and demographics, the state of Uttarakhand differs significantly from the rest of India. As a result, a vulnerability assessment of the next COVID-19 variation (Omicron BA.2) is required for district-level planning to meet regional concerns. A total of 17 variables were chosen for this study, including demographic, socio-economic, infrastructure, epidemiological and tourism-related factors. AHP was used to compute their weights. After applying min–max normalisation to the data, a district-level quantitative SWOT is created to compare the performance of 13 Uttarakhand districts. A COVID-19 vulnerability index (normalised Ri) ranging between 0 and 1 was produced, and district-level vulnerabilities were mapped. Quantitative SWOT results depict that Dehradun is a best performing district followed by Haridwar, while Bageshwar, Rudra Prayag, Champawat and Pithoragarh are on the weaker side and the normalised Ri proves Dehradun, Nainital, Champawat, Bageshwar and Chamoli to be least vulnerable to COVID-19 (normalised Ri ≤ 0.25) and Pithoragarh to be the most vulnerable district (normalised Ri > 0.90). Pauri Garwal and Uttarkashi are moderately vulnerable (normalised Ri 0.50 to 0.75).

Keywords: COVID-19; Quantitative SWOT; Vulnerability assessment; Vulnerability index (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-022-02727-3

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