At OSR we’ve long been concerned about the risks that a world of abundant information and misinformation could lead to a catastrophic loss of confidence in statistics and data – and that our public conversation, cut loose from any solid foundations of evidence and impartial measurement, would be immeasurably weakened as a result. That is, at root, what we exist to prevent. I have written about this before as a form of statistical Gresham’s Law – how the risk is that the bad data drive out the good, causing people to lose confidence in all the evidence that’s presented to them in the media and social media.
I’ve also said that this is not inevitable, and indeed we can easily envisage a reverse effect: the bad data being driven out by the good data – that is, the trustworthy, high quality, high value data.
What it takes to secure this positive outcome is a public sector statistical system focused on serving the public good. A system that does not regard official statistics as just a Number, shorn of context, calculated in the way it always has been done, some kind of dusty relic. Instead a system that regards the production of statistics as a social endeavour: engaging with users of statistics, finding out what they want and need to know, and responding in a flexible and agile way to meet those needs.
The pandemic has really tested the public sector statistical system and its ability to provide the good data, the trustworthy, high quality, high value data. The pandemic could have seen us being overwhelmed with data from a wide range of sources, some less reliable than others. It could also have seen Government statistics retreating to the Just a Number mindset – “we just count cases, it’s up to others to decide what the numbers mean”. But the system has not done this. Instead, as our report published today shows, the statistical system has passed the test with flying colours.
Statistical producers (producers) across the UK nations and system-wide have responded brilliantly. They have shown five attributes. It’s easy to see these attributes in the work of public health statisticians and ONS’s work on health and social care statistics. They have done great things. But what’s clear to us is that these attributes are system-wide – appearing in lots of producers of statistics and across lots of statistical areas.
Producers across the UK governments have been responsive, proactive and agile in producing data and statistics to support policy and to provide wider information to the public which really adds value. For example the ONS launched the Coronavirus (COVID-19) Infection Survey in swift response to the pandemic. The survey provides high-quality estimates of the percentage of people testing positive for coronavirus and antibodies against coronavirus. 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.
Producers have responded impressively to the need for very timely data to ensure that decisions around responses to the pandemic are based on the most up-to-date evidence. For example, the ONS published the first of its weekly Economic activity and social change in the UK, real-time indicators (previously called Coronavirus and the latest indicators for the UK economy and society) publications in April 2020, one month after the UK first went into lockdown and has continued to do so ever since. The publication contains a series of economic and social indicators (for example, card spend, road traffic and footfall), which come from a variety of different data sources. These assist policymakers with understanding the impact of the pandemic and gauging the level of overall economic activity. During the early weeks of the Covid-19 pandemic, the Department for Transport rapidly developed near-to-real-time statistics about Transport use during the coronavirus (COVID-19) pandemic. 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.
Collaboration and data sharing and linkage have been a key strength of both the UK statistical system and the wider analytical community over the past year. This more joined-up approach has improved our understanding of the impact of the pandemic both on public health and on wider areas such as employment and the economy. For example, during the pandemic, ONS and HMRC accelerated their plans to develop Pay as You Earn (PAYE) Real Time Information (RTI) estimates of employment and earnings. The Earnings and employment from PAYE RTI is now a joint monthly experimental release that draws from HMRC’s PAYE RTI system which covers all payrolled employees and therefore allows for more detailed estimates of employees, rather than a sample based approach, as well as information on pay, sector, age and geographic location.
We have seen some good examples of clearly presented and insightful statistics which serve the public good. For example, Public Health England (PHE) developed and maintain the coronavirus (COVID-19) UK dashboard. This dashboard is the official UK government website for epidemiological data and insights on coronavirus (COVID-19). The dashboard was developed at the start of the pandemic to bring together information on the virus into one place to make it more accessible. Initially it presented information for the UK as a whole and for the four UK countries individually. Over time it has developed so that data are now available at local levels. We have seen the increasing use of blogs to explain to users how the pandemic has affected data collection, changes to methodologies and bring together information available about the pandemic. For example, the Scottish Government has blogged about analysis and data around COVID-19 available for Scotland. We have also seen examples of statisticians engaging openly about data and statistics and their limitations, both within and outside government, helping the wider understanding of this data and statistics. For example, Northern Ireland Statistics and Research Agency (NISRA) statisticians have introduced press briefings to explain their statistics on weekly deaths due to COVID-19. The Welsh Government Chief Statistician’s blog is a regular platform for the Chief Statistician for Wales to speak on statistical matters, including providing guidance on the correct interpretation of a range of statistics about Wales.
For statistics to serve the public good they must be trustworthy, and this includes statistics being used and published in an open and transparent way. We have seen efforts to put information in the public domain and producers voluntarily applying the Code of Practice for Statistics (‘the Code’) to their outputs. For example, the Department of Health and Social Care (DHSC) publishes weekly statistics about the coronavirus (COVID-19) NHS test and trace programme in England. DHSC has published a description about how the pillars of the Code have been applied in a proportionate way to these statistics. However, inevitably the increased volume of and demand for data has placed a greater burden on producers and led to selected figures being quoted publicly when the underlying data are not in the public domain.
But our report also shows how the system cannot take these 5 attributes for granted. What has been achieved in the high pressure environment of a pandemic must be sustained as we ease out of being a pandemic society. New challenges – like addressing regional imbalances, or moving to a greener economy or addressing issues like loneliness and inequality – cannot be understood using objective statistics if the system retreats into the Just a Number mentality.
So, our report sets a number of recommendations. The recommendations aim to make sure that the statistical system we have seen in the pandemic is not an aberration, but is – in the classic pandemic phrase – the new normal. A system that can harness these five attributes is one that serves the public good. It is the best way to ensure that the bad data do not thrive and the good data shine out.