Commons Sense

House of Commons · Westminster Hall

Covid-19: Forecasting and Modelling

18 January 2022 · 7 other contributors · 9,831 words

Opened by Bob Seely Con Isle of Wight

Responding minister: Maggie Throup

NHS

Summarised by AI from the official record, so it can contain mistakes.

Read the full transcript on Parliament.uk

At a glance

Bob Seely raised concerns about covid-19: forecasting and modelling in Westminster Hall. A government minister responded.

Key points

  • Bob Seely expresses concern over the impact of questionable modelling on public health policy during the Covid pandemic.
  • Seely references peer-reviewed studies that cast doubt on the validity and ethical implications of such modelling.
  • Seely asks the Government to explain its reliance on worst-case scenario predictions from modellers like Imperial College London.

Key requests to Government

Seely asks the Government to explain why they relied heavily on doomsday scenarios provided by modellers like Imperial College London. He also questions the BBC's role in presenting these forecasts without sufficient challenge, and calls for an end to the normalisation of worst-case scenarios that have led to a loss of trust in government institutions.

How the debate unfolded

MPs spoke in turn to share their views and ask questions. Here's what each person said.

Opened the debate

Bob Seely Con Isle of Wight

Bob Seely is concerned about the influence of questionable modelling on public health policy during the Covid pandemic. He cites instances where models have been poorly presented, misrepresented, and used to drive lockdown measures and create a climate of fear. Seely references peer-reviewed studies that question the validity and ethical implications of such modelling, especially regarding the foot-and-mouth disease epidemic in 2001 and more recent predictions by Imperial College London.

Other contributors (7)
  • Aaron Bell Con Wrexham

    Mr Bell defended modelling, drawing on his experience as a software engineer. He noted the difficulty in accurately predicting human behaviour during pandemics and highlighted issues with inaccurate parameters used in models, such as vaccine effectiveness data not being up to date when decisions were made.

  • Anne Marie Morris LD Newton Abbot

    The hon. Member raised the issue of preparing for crises using a playbook approach instead of traditional models, which were rigid and limited to covid-related data. She highlighted that modelling failed to account for the broader impacts on health, wealth, society, communities, and the economy due to lockdown measures.

  • Brendan O'Hara SNP Argyll, Bute and South Lochaber

    Brendan O'Hara thanked scientists and medical professionals for their efforts during the pandemic. He emphasised that health is devolved in Scotland and criticised those who attacked scientists for their modelling predictions. He cited Professor Chris Whitty's statement that advice was based on observable data rather than forecasting models alone, and argued against the libertarian critique of public health measures. O'Hara also highlighted the success of the first lockdown in saving lives.

  • Fleur Anderson Lab Putney

    The speaker paid tribute to public servants and Government scientists who worked tirelessly during the pandemic. She criticized the debate's ideological bent, arguing that it was unfair to attack those who have been trying to keep people safe. She emphasized the importance of modelling as a tool for managing epidemics and highlighted issues with communication and accountability in government decision-making.

  • Greg Smith Con Mid Buckinghamshire

    Greg Smith intervened to ask if Brendan O'Hara would give way. Asked the Minister if they would give way, seeking to address questions or concerns raised during the debate.

  • Miriam Cates Con Isle of Wight

    Criticised the repeated failures in modelling throughout the pandemic, highlighting issues with assumptions not being questioned and challenges in accurately predicting real-world outcomes. Emphasized the need for better understanding of social science factors in modelling, questioning why certain impacts on education, child abuse, poverty, loneliness, despair, and fear were not modelled.

  • Steven Baker Con Devon, South Hams

    Expressed gratitude for the mention of his constituent Raghib Ali and highlighted Ali's contributions during the pandemic. Emphasised that no one can speak on behalf of Raghib regarding his opinion on modelling. Expressed concern over the institutional reform of how modelling informs public policy, highlighting overly pessimistic projections leading to severe lockdown measures. Advocated for an office of research integrity demanding higher quality assumptions and model methodologies. Asked about the repeatability of scientific experiments in models, noting that multithreading can lead to non-repeatable outputs. Mr Baker sought an intervention from Mr Bell. Steven Baker intervened to ask if Brendan O'Hara would give way for a question and clarified that his points did not require ideological justification, disputing O'Hara's claim about libertarian political philosophy being necessary for criticism of public health measures. I am grateful to the Minister for giving way. She heard what I said about my conversation with the Prime Minister—it is, of course, a true account of what happened. The reality is that the Prime Minister was shown a terrifying model that subsequently proved to be wildly incorrect, but he took away freedoms from tens of millions of people on that basis.

Government Response

Maggie Throup

It is a pleasure to serve under your chairmanship. I thank my hon. Friend for introducing today's debate and all hon. Members for their contributions. Throughout the pandemic, we have been supported by world-leading scientists, epidemiologists, and modellers who worked tirelessly around the clock. During the fast-moving and uncertain pandemic, this support has been critical to ensuring that the Government had access to the latest and most reliable scientific advice. The UK is fortunate to have such strong academic expertise. Scientific advice from disciplines ranging from immunology through to behavioural science played a role in understanding how different variants behave in the body and advising on higher risks for patient groups. Epidemiology and infection disease modelling help understand the spread of covid-19 across the population and its impact. It is important, however, to remember that such modelling is a tool enabling Ministers to make evidence-based decisions. Modelling provides a good way of understanding possible futures; identifying what will determine which future we face; and exploring how different policies could influence outcomes. Models cannot perfectly predict the future, but they provide assessments of uncertainty and how results might change as new evidence emerges. Central to modelling advice is an assessment of this uncertainty, with modellers looking at a wide range of possibilities and assumptions to advise policy makers on principles. One example is a model in December that considered omicron's intrinsic severity ranging from 10% to 100% of delta's. Fortunately, severity is not at the upper end of this range, and models have been updated as new evidence emerges. Encouraging diverse opinions and interpretations of data is part of the process. SPI-M-O and SAGE do not rely on just one model or group but look at advice from a number of independent institutions. Robust scientific challenge has been vital to the quality of SAGE advice, with modelling papers regularly released online for everyone to challenge and bring forward other evidence. Hard data on what is actually happening to patients and to the population as a whole is an essential part of the advice given. Modelling helps understand possible risks from the spread of covid-19 but must be balanced against other health, economic and societal impacts. Comparisons between past scenarios and reality should be made with caution. Past modelling has proved remarkably accurate in many cases. Lessons will be learned. Finally, I would like to thank hon. Members for their participation in today's debate.

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