COVID-19 is a worldwide transmitted pandemic that has brought a threatening challenge to Indian society and the economy. The disease has become a public health disaster, which has no effective medication. However, proper management and planning, which includes understanding the transmitting pattern, number of containment zones, vulnerable factors, and level of risk, may break the chain of transmission and reduce the number of cases. Hence, this study has attempted to model the COVID-19 vulnerability using an integrated fuzzy multi-criteria decision-making (MCDM) approach, namely fuzzy-analytical hierarchy process (AHP) and fuzzy-technique for order preference by similarity to ideal solution (TOPSIS) for West Bengal, India, through geographic information system (GIS). A total of 15 parameters were utilised to model the COVID-19 vulnerability, which was further categorised into three criteria: social vulnerability, epidemiological vulnerability, and physical vulnerability. The final vulnerability mapping has been done using these three criteria through the GIS platform. This study reveals that COVID-19 infection highly threatens about 20% of the total area of West Bengal, 23.42% moderately vulnerable, and 57.03% of the area comes under low vulnerability. The highly vulnerable region includes the Kolkata, South 24 Paraganas, and North 24 Paraganas, which are considered highly populated districts of West Bengal. Therefore government agencies should be more focused and plan accordingly to safeguard the community, especially the region with very high COVID-19 vulnerability, from further spreading the infection.

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Himalaya is one of the most seismo-tectonically active mountain on the surface of the earth.Recurring moderate and high magnitude earthquakes are not uncommon in this region. This paper maps the earthquake vulnerability in the Himalayan seismo-tectonic zone using integrated multi-criteria decision models. Several factors influence the earthquake vulnerability in a region, such as the social, geotechnical, structural, and physical parameters. We have used the analytical hierarchy process (AHP) approach to determine the weights of various parameters, which have been further used in the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Grey Relational Analysis (GRA) method to develop earthquake vulnerability maps for the study area. The map generated by AHP-VIKOR reveals that 12.93% of the Himalayan region is highly vulnerable, 26.39% moderately vulnerable, and 60.67% of the area is relatively low vulnerable. On the other hand, the AHP-GRA method reveals that 9.75% of the region is high vulnerability zone, 20.26% moderate, 70% as a relatively low vulnerable zone. A high correlation between the final vulnerability maps generated from AHP-VIKOR and AHP-GRA further validates our result. The results of this paper may be useful for the various hazard mitigation and infrastructure planning agencies in the Himalayan seismicity zone.

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