A systems analysis of the UK COVID 19 pandemic response: Part 2 - work as imagined vs work as done. (February 2022)

• Record Type: Journal Article
• Authors: Slater, David
• Is Part Of: Safety science. Volume 146(2022)
• Publication Date: 2022-02
• Subjects: Systems thinking -- COVID 19 -- Complex adaptive systems -- FRAM; Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2021.105526
• Languages: English
• ISSNs: 0925-7535

Abstract

Abstract: Modelling complex sociotechnical systems to try to understand how observed behaviours emerge from a network of interacting, interdependent and interrelated functions is a major challenge. Woods et al (Branlat, 2010), have pointed out that it is difficult to find a satisfactory current methodology. They suggested that perhaps the Functional Resonance Analysis Methodology developed by Hollnagel (Hollnagel, 2012) could be an appropriate approach to try. In Part 1 this approach was employed to build an overall model of the UK's COVID 19 response management system, which was constructed as a framework against which, a series of more detailed analyses of specific health care responses could be examined. This meant being conscious of the bigger picture of simultaneous activities and the dynamic emergence of unexpected developments. At that stage, it was of necessity a model of "work as imagined" from careful official and speculative media sources. Although, a full rigorous application will require a more authenticated, official (peer reviewed?), set of data, reports and evidence statements, which doubtless will be available eventually from the inevitable Public Inquiry, it seems a pity to delay gaining and applying any insights and adaptations from "work as (actually) done", that have been observed to date. The recent select committee evidence from people at the heart of the system, (Committee, 2021), which may, or may not be corroborated later, nevertheless now provides a provisional database, which can be utilised to test whether the FRAM model can produce such insights from the actual performance of this highly complex system. This paper has thus attempted a trial run and has found that it can produce a plausible set of insights, which can explain how the system behaved in practice. With such a serious challenge to Government systems worldwide, in all their advisory, operation and decision-making functions, such insights although provisional, could usefully be incorporated and formalised in the current systems rather than waiting for inquiry endorsed recommendations to be formally considered perhaps some years into the future. The paper thus sets out a set of conclusions and recommendations, caveated by emphasising the lack of fully authenticated public domain data on which it is based. The main conclusion however is that the current system appears not to have included any of the functions which could have provided the adaptability and resilience required by fast moving emergencies, such as pandemics. The exception noted was the establishment of a parallel, independent vaccine development and delivery function and it is hoped that at least this lesson from the work as done could be recognised as providing the type of adaptability required and incorporated without delay.