Data-Driven Decision Making in Response to the COVID-19 Pandemic: A City of Cape Town Case Study

Elmarie Nel, Andrew MacLachlan (), Ollie Ballinger, Hugh Cole and Megan Cole
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Elmarie Nel: Policy and Strategy Department, City of Cape Town, Cape Town 8000, South Africa
Andrew MacLachlan: The Centre for Advanced Spatial Analysis (CASA), University College London, London WC1E 6BT, UK
Ollie Ballinger: The Centre for Advanced Spatial Analysis (CASA), University College London, London WC1E 6BT, UK
Hugh Cole: Policy and Strategy Department, City of Cape Town, Cape Town 8000, South Africa
Megan Cole: Future Water Institute, University of Cape Town, Cape Town 7700, South Africa

Sustainability, 2023, vol. 15, issue 3, 1-18

Abstract: In the event of a crisis, such as COVID-19, the decisions and subsequent actions taken by the local government are one of the primary sources of support to the local population. Yet the processes through which these decisions are reached and the data engineering advancements made for and during events are poorly reported. Understanding the capabilities and constraints in which city officials operate is essential for impactful academic research alongside global city comparison and discussion on best practices in reaching optimal and data-informed decisions. This is especially pertinent for the global South, where informality in housing and the economy presents further challenges to appropriate resource distribution in a crisis. Here, we present insights into the City of Cape Town’s data-driven response and subsequent data engineering and analytical developments throughout the COVID-19 pandemic. This is based upon a review of internal documentation including a close-out report which summarised semi-structured interviews with staff involved in the data work stream. The paper reports on the deliverables produced during 2020 by the data work stream and outlines specific challenges the city faced and its data-informed response in the areas of (1) quantifying costs for COVID-19 initiatives, (2) dealing with a surge in fatalities, (3) guiding scarce public resources to respond to an evolving crisis, and (4) data sharing. We demonstrate the real-term value of incorporating data into the decision-making process and conclude by outlining key factors that cities and researchers must consider as a part of the usual business to effectively assist their populations during times of stress and crisis.

Keywords: data-driven policy; Cape Town; COVID-19 response; smart cities; urban spatial science; resilience (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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