Data and Covid-19: Navigating Barriers to Data-based Policy-making
Written by SDSN TReNDS’ Expert Member, Jonathan Glennie
The Covid-19 crisis throws the data and science that underpin our political and societal decision-making into sharp relief. For the first time in most of our lifetimes, the general public has become acutely aware of the value of data. And in some cases, the detail of scientific analysis is being scrutinised not only by politicians, as they make major policy decisions, but also by the general public. At the same time, the inherent challenges of data collection and interpretation and the barriers to data-based policy-making have become clearer in the public eye.
Source: The Giving Compass
The first barrier highlighted by this pandemic is how hard it is to collect health data, let alone timely health data. This is partly down to the inherent difficulty of such a task, but some countries are managing better than others. The UK has ditched an app it spent three months developing for contact tracing because it didn’t work, and its testing scheme has been widely ridiculed. But other countries, like Germany, appear to have got both the contact tracing and testing processes right. Why? Because this isn’t just about technology or the right theoretical model; it’s about practical action. You need tests, testers, and testing stations, and these are hard to build from scratch, especially without the necessary infrastructure available.
The second barrier relates to what better data collection means for civil liberties. All the recent talk is of contact tracing, using mobile technology and big data, as well as possibly invasive interviews and surveys. But by definition, this is an obvious infringement of civil liberties that most people today consider the norm, from blood tests in Italy, to the “travelog” developed in South Korea, to Israel’s decision to use secret mobile data. Even at the height of a brutal pandemic, concerns are rightly being raised about the information the public is passing on to political and private organisations. It is well-known that crises offer opportunities for governments and businesses to instigate new ways of working that would be unacceptable in “peace-time” – and that they sometimes conveniently “forget” to go back to normal when the context improves. So how will the relationship between data and individual privacy change after the pandemic? How do we guard against the kind of mass surveillance state that was already a concern pre-Covid, and is even more so now?
Third, even the data we do collect is subject to interpretation. We depend on very experienced scientists to help do the technical work of telling us, but they can disagree. Sweden has embarked on very different quarantine policies than its neighbours Norway and Denmark, but both claim to be “following the science.” Who interprets data matters as much as the data itself. Anthony Costello, a global health expert, has written about how the UK’s science advisory team, for instance, lacked critical expertise on key issues, including public health epidemiology, nursing, and immunology.
Fourth, even when you have scientist-managed, meaningfully-presented health data to look at, there are tonnes of other bits of evidence to be considered before policy can be made. Scientific evidence is only one part of the policy-making mix. Other ingredients are economic and social analysis which help decision-makers, for instance, decide on the best way to handle a lockdown. Additionally, while the virus may act similarly in different contexts, the severity of the economic impact of a lockdown varies not only across countries but within countries. All of these factors are at play during the policy-making process.
The fifth and final barrier to good data-based policy-making is the hardest to tackle: the simple fact that science and data are not given the respect they deserve. This appears to be a growing problem across the world, as well-known leaders openly challenge scientific evidence, and in some of the worst cases of lazy communication, suggest quack medical responses with no evidence. The evidence culture matters as much as the evidence itself.
These barriers to data-based policy-making are serious. So how can they be overcome?
First, more investment is required as part of a greater focus on data collection. Given how hard it has been for relatively well-funded systems to collect and manage data successfully, the reality for much poorer countries is unsettling.
Second, more public debate and scrutiny are needed on the relationship between data collection for the public good and civil liberties. Each society will manage this differently – what is clear is that the debate must be had and an acceptable balance reached.
Third, scientific analysis and advice need to be independent of politics, insofar as possible. Firewalls need to be built between politicians, some of whom actively seek to undermine science, and the scientists on whom we all rely. Scientific advice received by governments should be published (save in exceptional circumstances) so that citizens can make up their own minds about it – until recently the UK public, for instance, was not even allowed to know who sat on the main scientific committee advising the government on Covid-19.
Easier said than done. What would a data-based approach look like? How can data be made more accessible to the general public, rather than furthering information inequality? Do countries need some kind of “data ombudsman” to oversee whether governments are really following the science? Do we need a supranational legal system to guide the balance between data gathering and civil liberties – Europe’s GDPR has reportedly proved useful in that regard during this pandemic.
All these questions, in my view, point to an expanded role for international institutions, and the UN, in particular. The UN needs to centre science ever more strongly. The threats facing the world all require a science and data-based response. UN institutions need to do more than pay lip service to science; they need to incorporate scientific councils into their governance structures and hold international meetings for scientists like the Intergovernmental Panel on Climate Change (IPCC), but for other themes as well.
Change happens, ultimately, at the national and sub-national levels. But international direction-setting can tip things the right way, influencing academics, policy-makers, and civil society. National-level civil registration vital statistics (CRVS) systems, for instance, have been significantly influenced and improved by work at the international level, and similar work could be done for other data issues – like how to invest and addressing civil liberty concerns. Communicating this science-approach to the general public across the world will be crucial as well, providing a counterweight to easy populism.
There are no easy solutions, but the UN and other multilateral entities, including at the regional level, are crucial to overcoming these barriers to data-based policy-making.
Will the Covid-19 moment be a tipping point? Experience has taught us to be wary of being overly-hopeful – the fact that these are complex areas leaves them easy prey for politicians who gain from obfuscation rather than clarification. But, with data and science under siege and a global pandemic raging, every effort must be made to turn the tide to ensure this decade is more data-based than the last.