COVID-19-Adapted Multi-Functional Corniche Street Design Assessment Model: Applying Global Sensitivity Analysis (GSA) and Adaptability Analysis Methods

Abstract

The world-shaking communicable coronavirus disease (i.e., COVID-19) has become a pandemic threat to a healthy built environment. This study aimed to develop the COVID-19-adapted multi-functional corniche street design (Ca-MCSD) assessment model. Accordingly, this study identified variables coordinating the local environmental, physical, social, cultural, and political mediations of multi-functional corniche street design. Secondly, it measured the weight of every single variable through confirmatory analysis, normalization, and standardization techniques, and an expert-input study then developed the MCSD model and Ca-MCSD model. This study validated the models through a case study (i.e., Al Wakrah corniche street in Dubai, Qatar) and conducted ANOVA regression analysis and global sensitivity analysis (GSA). The Ca-MCSD model evaluates the design quality of a corniche street across five criteria—inclusiveness, desirable activities, safety, comfort, and pleasurability—and forty-two sub-criteria. The regression analysis determined that the MCSD model and Ca-MCSD model are linearly and positively correlated (Y = 0.811777X + 0.383401), where the Pearson regression coefficient (r) equaled 0.903729, r2 equaled 0.816727, and the p-value was 0.025 with 95% confidence intervals. The research found that, before the COVID-19 pandemic, microclimate comfort (avWSc.3.4 = 7.880), community gathering places (Sc.2.1), availability of foods (Sc.2.4), appropriate maintenance and physical condition (Sc.3.6), and attractiveness of space (Sc.5.8) (avW = 6.000) played critical roles in designing a multi-functional corniche street. However, after the onset of the COVID-19 pandemic, the key drivers changed to microclimate comfort (favWSc.3.4 = 12.632), appropriate maintenance and physical condition (favWSc.3.6 = 9.618), physical/visual connection or openness to adjacent spaces (favWSc.4.1 = 4.809), and over-securitization (favWSc.4.1 = 4.287).