How fair were COVID-19 restriction decisions? A data-driven investigation of England using the dominance-based rough sets approach

TL;DR

This paper uses a data-driven approach to analyze the fairness of COVID-19 restriction decisions in England, revealing regional inconsistencies and demonstrating the method's potential for transparent policy analysis.

Contribution

It introduces the dominance-based rough set approach to interpret and evaluate the fairness of tiered restriction allocations during COVID-19 in England.

Findings

Identified regional disparities in restriction allocations

Revealed a north-south divide driven mainly by London

Demonstrated the approach's usefulness for policy transparency

Abstract

During the COVID-19 pandemic, several countries have taken the approach of tiered restrictions which has remained a point of debate due to a lack of transparency. Using the dominance-based rough set approach, we identify patterns in the COVID-19 data pertaining to the UK government's tiered restrictions allocation system. These insights from the analysis are translated into "if-then" type rules, which can easily be interpreted by policy makers. The differences in the rules extracted from different geographical areas suggest inconsistencies in the allocations of tiers in these areas. We found that the differences delineated an overall north south divide in England, however, this divide was driven mostly by London. Based on our analysis, we demonstrate the usefulness of the dominance-based rough sets approach for investigating the fairness and explainabilty of decision making regarding COVID-19 restrictions. The proposed approach and analysis could provide a more transparent approach to localised public health restrictions, which can help ensure greater conformity to the public safety rules.