The Covid-19 pandemic has affected the world with devastating speed. While most will be impacted in some way, the peculiarities of the disease itself and the socio-economic fallout create uneven vulnerabilities. There are multiple interrelated factors that potentially exacerbate the social, economic and health shocks of Covid-19. Using knowledge of the disease and early evidence of the social and economic consequences, it is possible to develop risk models to better prepare less resilient communities. This policy paper outlines the application of a GIS (Geographical Information System) multi-criteria analysis to model the relative impacts of Covid-19 to identify vulnerable communities in Malaysia. The model outputs show while the denser urban areas are more likely to experience an outbreak, the peri-urban and remote areas are more vulnerable to the mid- and long-term impacts of the pandemic. This exercise demonstrates the crucial role of data in addressing the uncertainties surrounding the pandemic and gaps in developing adaptive response plans and policies.
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