1. Responsive and proactive

For statistics to serve the public good, they should support society’s needs for information.  

Since the start of the pandemic, producers across the UK have been responsive and proactive in producing data and statistics to support policy and to provide wider information to the public. New data collections have been established at pace, existing collections have been amended, added to or paused to focus on higher priorities, and data sources have been linked together in new ways to provide additional insight. These have covered both topics related directly to the virus itself, as well as those looking at the wider impacts of the pandemic. 

Many outputs have been developed to provide new insights to help understand the pandemic and its implications. One high profile example is the coronavirus (COVID-19) infection survey, carried out by the ONS in conjunction with partners.

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Case Study 1: Coronavirus (COVID-19) Infection Survey

The ONS launched the Coronavirus (COVID-19) Infection Survey in swift response to the pandemic, just weeks after the first UK lockdown in March 2020. Over the following months, ONS increased the study from a survey of around 28,000 people in England, to over 150,000 people from across the UK by October 2020. It is the largest and only representative survey of COVID-19 infections in the community and follows up participants for up to 16 months. The survey provides high-quality estimates of the percentage of people testing positive for coronavirus and antibodies against coronavirus. As such, these statistics provide vital insights into the pandemic for a wide range of users, including government decision-makers, scientists, the media and the public that are essential for understanding the spread of the virus, including the new variants.

Of particular note was the speed at which resources were reprioritised within ONS to allow staff to work on the survey, and the strong working relationships established between ONS analysts, the analytical teams across the devolved nations, the survey contractor IQVIA, and the academic partners at the Universities of Oxford and Manchester. ONS both responded to user needs (e.g. through responding to user requests) and proactively anticipated what would be of interest in the future and should be included in the survey (e.g. cases of long covid or statistics on antibodies and vaccinations).


Other examples of new data sources that have been established quickly in response to the pandemic include statistics on the Coronavirus Job Retention Scheme and the Self-Employment Income Support Scheme, both published by HM Revenue and Customs (HMRC). 

We have also seen examples of producers amending existing data sources and using them in innovative ways. One such example is the Department for Transport’s (DfT) statistics on Transport use during the coronavirus (COVID-19) pandemic. 


Case study 2: Transport use during the coronavirus (COVID-19) pandemic

During the early weeks of the Covid-19 pandemic, the Department for Transport rapidly developed statistics about Transport use during the coronavirus (COVID-19) pandemic. The Department brought together and adapted a wide range of existing National Statistics data sources and operational data to produce near-to real-time statistics, including identifying a new data source for statistics on bus use outside of London, and developing much more timely data on car use.

The statistics were regularly used by No10 press conferences (example in slide 2) to show the change in transport trends across Great Britain and gave an indication of compliance with social distancing rules.

The Department was proactive in producing timely data to meet user needs. It initially produced daily data to meet regular requests for data, moving to weekly data when daily data were no longer required. Ahead of schools returning in September it returned to providing daily data, in anticipation of heightened interest and increased travel.


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There have also been many examples of smarter working to enable the production of new data and continuation of existing data given the constraints that have existed. This has included the use of new methods of data collection to replace key face-to-face surveys that have had to pause. Perhaps the most notable example of adapting to allow work to continue is that of the Census in England, Wales and Northern Ireland, which still went ahead this year despite the pressures and constraints of the pandemic.

Within the OSR, we have also been responsive to the needs of the statistical system during the pandemic and have granted exemptions to the release times of outputs. It is really important that there is equality of access to statistics and that some do not get to see statistics before others. Consequently, we expect all producers of statistics to release their statistics at the same time (09:30) on the day that they say the statistics are ready for release. However, due to Covid-19 we granted exemptions to the release times of some outputs – for example, to allow some COVID-19 related statistics to be released as soon as prepared and quality assured, with release times of noon and 2pm. This enables them to feed more promptly into decision-making in a transparent way.

As we emerge from the pandemic it will be important to consider how to sustain this agile and responsive approach while at the same time being mindful of the additional strain this has inevitably placed on many individuals. Departments have acknowledged that much of the additional work has taken place without any corresponding increase in resources. In some areas we have heard of staff working long hours including weekends, and being unable to take leave. This is unsustainable in the long run. Although the demand for additional data is likely to slow down or even stop in some areas, it will be important to reflect on what steps can be taken to maintain an agile approach going forwards.

Another key question is around the gaps in data as a result of different limitations and data needs during the pandemic. For example, while the Census will offer rich insight into the populations of England, Wales and Northern Ireland in March 2021, it will be hard to disentangle which aspects relate to the pandemic and which relate to more long-term changes to society. As an example of this, the Census question on travel to work asks those working at the time to answer reflecting current circumstances. Those on Furlough were asked to answer based on how they used to travel to their main place of work.

In some areas it will be difficult to tease out separately the impacts that changes to methods versus changes to behaviour have on estimates. For example, the International Passenger Survey (IPS) was suspended between March and December 2020 due to the pandemic. No IPS data were collected for the period when the survey was not operational, and estimates were instead based on administrative sources and modelling. At the same time, international travel itself was clearly very limited. ONS is very clear in its Overseas travel and tourism: 2020 release that the results are indicative and should be interpreted with caution.

Looking to the future

The UK statistical system should maintain the responsive and proactive approach we have seen, and look to do this in a sustainable way. Improvements to data infrastructure, processes, and systems could help to maintain this responsiveness and agility in a sustainable way. It is now important to question what elements of the new approaches should remain, which should change, and how data infrastructures can be set up to support a more agile approach.

For example, when and how best should data collection return to face to face household surveys? Should legacy surveys like the Annual Business Survey continue or should there be a move to new platforms or administrative data? How can the new data sources that have now come on stream be exploited even more? Is there a case for synthetic data to enhance existing data to help phase out large and expensive surveys? Can new survey platforms be used to answer short-term questions to help manage the impacts of the pandemic? Does the 9.30am release time stated in the Code meets today’s needs?

In OSR we have been looking at how to make improvements more sustainable – for example, championing the use of the Reproducible Analytical Pipeline (RAP) as a means of achieving more efficient and sustainable processes. We consider that RAP principles support all three principles of the Code of Practice for Statistics. We recently published our report detailing the findings of our RAP review. This report details our recommendations to enhance the trustworthiness, quality and value of official statistics through increased use of RAP principles, and to see RAP become the default approach to statistics. We are also carrying out a review into the 9.30 release time to ensure that the approach maintains confidence in the integrity of the official statistics and in their independence, while best serving the public good.

The UK statistical system should develop its capability to horizon-scan to identify existing and future data gaps and consider how these gaps should be addressed. For example, what data and statistics are needed related to the Government’s Build Back Better plan and Levelling Up agenda? What data gaps now exist because of changes to data collection through the pandemic and how best to respond to these gaps? This will help to both fully understand the consequences of the pandemic and to answer society’s future key questions.

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