Abstract

A pandemic devastates the lives of global citizens and causes significant economic, social, and political disruption. Evidence suggests that the likelihood of pandemics has increased over the past century because of increased global travel and integration, urbanization, and changes in land use with a profound affectation of society–nature metabolism. Further, evidence concerning the urban character of the pandemic has underlined the role of cities in disease transmission. An early assessment of the severity of infection and transmissibility can help quantify the pandemic potential and prioritize surveillance to control highly vulnerable urban areas in pandemics. In this paper, an Urban Vulnerability Assessment (UVA) methodology is proposed. UVA investigates various vulnerability factors related to pandemics to assess the vulnerability in urban areas. A vulnerability index is constructed by the aggregation of multiple vulnerability factors computed on each urban area (i.e., urban density, poverty index, informal labor, transmission routes). This methodology is useful in a-priori evaluation and development of policies and programs aimed at reducing disaster risk (DRR) at different scales (i.e., addressing urban vulnerability at national, regional, and provincial scales), under diverse scenarios of resources scarcity (i.e., short and long-term actions), and for different audiences (i.e., the general public, policy-makers, international organizations). The applicability of UVA is shown by the identification of high vulnerable areas based on publicly available data where surveillance should be prioritized in the COVID-19 pandemic in Bogotá, Colombia.

Highlights

  • Pandemics are intercontinental-scale outbreaks of infectious diseases that increase morbidity and mortality over a big geographic area and cause significant social, political, and economical disruption [1,2]

  • The method chosen in this study was to build an estimation of the Probability Density Function (PDF) of the data, and transform it via its Cumulative Density Function (CDF), so intervals with higher likelihood of containing data are assigned to higher portion of the normalized interval [0,1]

  • The results show how vulnerable areas found with Urban Vulnerability Assessment (UVA) overlap with urban areas with more COVID-19 cases

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Summary

Introduction

Pandemics are intercontinental-scale outbreaks of infectious diseases that increase morbidity and mortality over a big geographic area and cause significant social, political, and economical disruption [1,2]. A conceptual framework for Urban Vulnerability Assessment (UVA) for pandemics is proposed This UVA conducted a comprehensive review of relevant literature to identify vulnerability factors influencing pandemics. These were condensed into an index that allowed us to establish and rank potentially vulnerable urban areas. Using public available data of Bogotá, UVA creates a spatially explicit description of vulnerability for COVID-19 pandemic. This modeling application study provides a potential tool to inform policymakers to prioritize resource allocation and devise effective mitigation and reconstruction strategies for affected populations in Bogotá.

Vulnerability Assessment
Literature Review
Main Findings
Literature review and expert elicitation
Statistical Data Analysis
Cluster Analysis
Create Vulnerability Index
Study Area and Data Sources
Vulnerability Domains
Vulnerability Analysis
Vulnerability Index
Conclusions and Future Work
Full Text
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