An evaluative model for assessing pandemic resilience at the neighborhood level: The case of Tehran.

Abstract

The spread of the COVID-19 virus, which has caused abundant mortalities in human settlements, has drawn the attention of urban planners and policy-makers to the necessity of improving resilience to future pandemics. In this study, a set of indicators related to pandemic resilience were identified and used to develop a composite multi-dimensional pandemic resilience index for Tehran's neighborhoods. The physical, infrastructural, socio-economic, and environmental dimensions of pandemic resilience were defined considering the conditions of 351 neighborhoods through the exploratory factor analysis method. Accordingly, the pandemic resilience (PR) score of the neighborhoods was calculated. Furthermore, the Pearson correlation analysis was used to validate the PR scores by examining the correlation between the neighborhood PR scores and the number of confirmed cases. For this purpose, we used a sample consisting of 43,000 confirmed COVID-19 patients in the first five months of its spread. The test shows a statistically significant negative correlation between neighborhoods' resilience score and the cumulative number of confirmed patients in the neighborhoods (r= -.456, P<0.001). This study also tries to develop a new model to better understand health determinants of pandemic resilience. The proposed model can inform planners and policymakers to take appropriate measures to create more pandemic-resilient urban neighborhoods.