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How do we think about the UK lockdown debate?
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We must trust Neil Ferguson's model

The implications of Neil Ferguson's model are clear: lockdown or death on a catastrophic scale. It was Ferguson's forecasting of up to 500,000 UK deaths which resulted in lockdown. If this is the most accurate model we have, it is imperative that we trust it to guide us.
Coronavirus Government Health Lockdown United Kingdom


Neil Ferguson has guided the government's coronavirus policies because he is trusted and reliable. We need to accept that his models have been selected for a reason and follow their guidance.[1]

The Argument

When the mathematical epidemiologist at Imperial College London, Neil Ferguson, was tasked with advising the British government on their response to the SARS-CoV-2 viral pandemic, his models painted a grim picture.[2] His modeling of the spread of contagion and the cases of COVID-19—the disease caused by the virus—predicted that 500,000 British residents may perish if no actions were taken. With this in mind, the British government took justified action in deciding to lock down the country. The human toll that the disease would have borne meant that no action would have been negligent. The chaos in Italy, Spain, and now the United States all serve as warnings of the impact the virus can have on healthcare systems, the sick and elderly, and supply chains. The lockdown ensures that the spread of the disease is slowed as much as possible and gives vital infrastructure time to prepare. Furthermore, it prevents the public from engaging in behavior and activities that risk spreading the virus, such as large social gatherings, travel, and non-essential services. These actions likely prevented a more calamitous outcome from the pandemic, and therefore justify the degree of restrictions placed on the country. Even though the disease has begun to slow, lifting the lockdown too early would give up precious progress made in fighting the pandemic. Lifting restrictions before a vaccine or treatment is available could result in another exponential growth in cases. Many nations are far from herd immunity and therefore are poised to face an overflow of cases. As Ferguson suggests, lifting measures too early could still result in as many as 100,000 deaths in the UK. Even with the lockdown in place, the UK is approaching 50,000 deaths and has hundreds of thousands of cases. While a crisis may be unavoidable, Ferguson's model gives the country the time to prepare for a long battle ahead, and also protects the public from avoidable deaths and suffering. We should trust Ferguson's model, knowing that any deviance from extreme caution could result in catastrophe.

Counter arguments

Putting faith in the modeling of a single scientist for a global crisis is foolish. Other scientists have challenged Ferguson's findings and critics have described his handling of the foot in mouth crisis years ago as alarmist. Additionally, we adopted Ferguson's model as the paradigm for reacting to the virus before much of the current data and information about the contagion was available. We should trust the most recent findings because these are bound to be more accurate. Lastly, the lockdown does not consider the tradeoffs that governments must take in how to deal with the economic blow caused by shutting down society. Only considering the spread of the disease ignores other significant costs that society must bear during a crisis and puts people at risk of economic ruin, degrading emotional health, and lost academic and professional opportunities.[3]



[P1] Neil Ferguson modeled the potential threats of no lockdown or an early lifting of the lockdown. [P2] Lifting the lockdown would result in avoidable deaths and suffering.

Rejecting the premises

[Rejecting P1] Other scientists have suggested less drastic measures and outcomes as a result of the virus, and criticized Ferguson's handling of previous epidemics. [Rejecting P2] The suffering caused by prolonged lockdown due to economic, professional, and social stagnation may be worse than the disease.


This page was last edited on Monday, 26 Oct 2020 at 14:47 UTC

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