PANDEMICSCOVID: How Incorrect Assumptions and Poor Foresight Hampered the U.K. Pandemic Preparedness
In 2016, the UK government engaged in a series of exercises including Cygnus to assess their preparedness and response to a pandemic outbreak of a pandemic. No planning exercise can cover all eventualities. But a key requirement for policymakers should be to learn as fast and effectively as possible while events unfold. The business concept of “dynamic capability” – that is, an organization’s ability to configure and reconfigure its assets, processes and capabilities so as to respond effectively to rapidly changing external circumstances – is useful here. Building and strengthening this capability should be a prerequisite for policymakers and planners in government.
Matt Hancock, the former health secretary, has told the recently opened COVID-19 Inquiry that the UK’s pandemic planning was “completely wrong”. According to Hancock, the doctrine was “to plan for the consequences of a disaster” rather than stopping or containing the virus in the first place.
While there is truth in this claim, it doesn’t give us the whole picture. Hancock was repeatedly asked during his appearance about something called Exercise Cygnus. In 2016, the UK government engaged in a series of exercises including Cygnus to assess their preparedness and response to a pandemic outbreak of influenza.
As the global scale of the COVID pandemic was starting to become apparent in the first half of February 2020, the UK applied the lessons from these exercises to plan for a wide range of scenarios. Based on the scientific evidence available at that time, they anticipated that a “reasonable worst-case scenario” could involve up to 80% of the UK population being infected (with only 50% of those infected showing symptoms). However, it was hoped that the majority of cases would have relatively mild disease.
This information was contained in planning assumptions labelled “officially sensitive” that were shared between a range of healthcare authorities and that I had access to at the time. Some of the figures were also published in the media.
The concept of “herd immunity” played a key role in the existing mathematical models. Herd immunity is the idea that once a sufficiently large proportion of the susceptible population is infected and subsequently acquires immunity, the whole population becomes protected. The thinking was that herd immunity for COVID might be achieved once 80% of the UK population had been infected, or perhaps even earlier.
Underlying all this was the assumption that, in the absence of effective vaccines at that time, the case fatality rate from the new virus (the proportion of infected people who end up dying) would not be so high that herd immunity could only be achieved at the cost of many lives.
Unfortunately, the actual COVID mortality figures – first from China, then other east and southeast Asian countries, and by the second half of February 2020 also from Italy – showed that the initial case fatality rate of COVID was much higher than had been modelled in the UK scenarios.
Without effective vaccines, any attempt at herd immunity had to be abandoned as too many people would have died in the meantime.
