Poor data flows and a failure to capitalise on UK strengths in data science have bedevilled the governments response to the Covid-19 pandemic, a House of Commons Science and Technology Committee has found.
The committees 92-page report, The UK response to Covid-19: use of scientific advice, published 8 January, is focused on how the government has obtained and made use of scientific advice during the pandemic.
It notes that the remarkable achievement of developing and being in a position to deploy multiple vaccines against a deadly and virulent virus that was completely unknown a little over a year ago ranks as one of the most outstanding scientific accomplishments of recent years.
It recollects that the first two cases of Covid-19 were confirmed in the UK, in England, on 31 January 2020, less than a year ago. The first death from Covid-19 in the UK, in England, was announced on 5 March. As of 18 December, the total number of deaths since then, where Covid-19 is mentioned on the death certificate, is 82,624. On 06 January, another 1,041 deaths were reported.
The committee, chaired by Conservative MP Greg Clark, said in its report: A fully effective response to the pandemic has been hampered by a lack of data. For a fast-spreading, invisible, but deadly infection, data is the means of understanding and acting upon the course of the virus in the population.
The early shortage of testing capacity restricting testing only to those so ill that they were admitted to hospital had the consequence of limiting knowledge of the whereabouts of Covid-19. The ONS Infection survey did not begin until May, and the fragmentation of data across public organisations has impeded the agility and precision of the response.
The report laments the failures in data management in the governments response to the pandemic, and notes these are all the more damning given a national comparative advantage in the field.
Given the UKs strengths in statistical analysis and data science, it is regrettable that poor data flows, delays in data-sharing agreements and a general lack of structuring and data integration across both the health and social care sectors have throttled timely data sharing and analysis.
For example, it is unacceptable that detailed public health data was only made available to modellers from March. The potential consequences of this will undoubtedly include slower and less effective decision-making.
It finds solace in the establishment of the Joint Biosecurity Centre as an effort to centralise data flows to manage the pandemic, but notes it is unfortunate that no central mechanism to coordinate data was in place at the start of the pandemic.
The committee exhorts the Department of Health and Social Care (DHSC) to set out an action plan that describes what efforts have been made, and will be made, during the pandemic to address the poor data access issues raised by the scientific community and Sage [the Scientific Advisory Group for Emergencies] and its sub-groups.
This plan should, said the report, cover agreements and incentives for data sharing and data integration across the health and social care sectors and across the four nations of the UK.
The early shortage of testing capacity restricting testing only to those so ill that they were admitted to hospital had the consequence of limiting knowledge of the whereabouts of Covid-19 The Science and Technology Committee
The report points out that the line between advice and decision-making was tested on one signally important occasion, when the Prime Minister announced plans for a second stay at home order on 31 October.
Although the chief medical officer and government chief scientific adviser presented modelling data at the press conference alongside the Prime Minister, the data underlying this was only made public three days later and was subject to extensive criticism, including that the data was out of date, it added.
More positively, the report stated: The Office for National Statistics [ONS] is now conducting a very important sampling exercise in which data on the prevalence of Covid-19 in the UK population will be gathered and reported twice-weekly.
It is of great importance in providing data on the spread of diseases, its impact on the different demographic groups and geographies, the incidence of asymptomatic transmission and even the reproduction or R number which the government has made key to easing some social distancing restrictions.
In evidence to the committee, the national statistician, Ian Diamond, gave an impressive account of the speed in which his team had been able to organise and implement a significant testing programme.
The report quotes Diamond as having said: The fact that we came into it on a Thursday and, with the University of Oxford, put together the design and protocoland put it to medical ethics the following Monday and data ethics on Tuesday, with letters out to potential participants on the Wednesday, seems to me to be one of the most rapid surveys I have ever in my life seen go into the field.
However, he also told the committee that the request to put together such a testing programme was made only on 17 April 2020.
It was also drawn to the committees attention that data on the ethnicity of those dying from Covid-19 was not systematically collected.
The committee is recommending that government should consider how ethnicity data on those dying as a result of Covid-19 could be systematically recorded, and it notes that there are significant unexplained differences in the death rates in the UK of Black, Asian and minority ethnic [BAME] groups compared to the population as a whole.
The report also brings out a structural over-emphasis on epidemiological data, as opposed to broader data about the impact of the pandemic on the economy, mental health and other areas.
The report adduces public comments made by Mark Woolhouse, a professor and one of the epidemiologists advising the Scientific Pandemic Influenza Group on Modelling (SPI-M) and the Scottish Government Covid-19 Advisory Group, that he thought scientific advice was driven far too much by epidemiology.
Speaking to the committee in June, Woolhouse said: In the early stages of the epidemic, before we had large amounts of [public health] data, [advice] was largely on the basis of modelling, and that is all right and proper and as it should be, but we are looking literally at only one side of the equation when we do that.
He suggested, according to the report, that the other side of the equation included the harms done by lockdown, including impacts on mental health and social wellbeing, the education of our children, and our economy.
The report noted: While the experience of no country is perfectly comparable with others, it will be important to understand the reasons for [comparatively poor performance in relation to peer nations] to learn lessons for the future.
In this report, there are questions of how quickly scientific analysis could be translated into government decisions; whether full advantage had been taken of learning from the experience of other countries; and the extent to which scientific advice took as a given operational constraints, such as testing capacity, or sought to change them.
For any emergency situation, data systems need to be in place up front to be able to give the information to make the analysis and make the decisions Patrick Vallance, Government Office for Science
Patrick Vallance, the governments chief scientific adviser, told the committee, in registering the importance of data: One lesson that is very important to learn from this pandemic, and for emergencies in general, is that data flows and data systems are incredibly important. You need the information to be able to make the decisions. Therefore, for any emergency situation, those data systems need to be in place up front to be able to give the information to make the analysis and make the decisions.
He told the committee that this was not limited to testing data, but also encompassed basic information flows around patients in hospital, rates of admission and rates of movement.
The report added that Vallance suggested that a principal issue in managing the pandemic was that at the beginning, there were definitely times when we would have liked data that was difficult to getdata flows are getting much better now, but the NHS does not have centralised data flows on everything you need.
As an example, comprehensive data on Covid-19 in care homes were not available to the government in the early months of the pandemic. At a Sage meeting on 15 March, it was noted that because of a 5 to 7 day lag in data provision for modelling, Sage now believes there are more cases in the UK than Sage previously expected at this point, and we may therefore be further ahead on the epidemic curve.
The committee is calling on the government to publish the advice it has received on indirect effects of Covid-19 (including impacts on mental health and social wellbeing, education and the economy) and work to improve transparency around the operation of the Joint Biosecurity Centre.
Measures taken to contain the pandemic [have] had wider and indirect effects, such as on peoples livelihoods, educational progress and mental and emotional wellbeing, said the committee.
The assessment of these wider impacts was and remains much less transparent than the epidemiological analysis; the people conducting the analysis and giving advice are less visible than epidemiological modelling advisers; and its role in decision-making opaque.
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