The COVID-19 pandemic demonstrated the potential strengths and existing weaknesses of open science practices and open data sharing to addressing urgent social and technological challenges. In this post, Lucia Loffreda and Rob Johnson present a new report from the UK Government’s Department for Business Energy and Industrial Strategy, highlighting how support for open data and science practices can contribute to increased preparedness in the face of future crises.
The COVID-19 crisis saw pathogen genomic data deployed worldwide to characterise virus outbreaks, track the mutation and spread of the virus, and develop public health responses to the COVID-19 pandemic. At the same time, it has shone a light on the practices, incentives and infrastructures that enable data sharing and re-use. As nations look to emerge from the crisis, five key lessons can be learnt to enable preparedness for future pandemics.
In a new report, commissioned by the UK Government’s Department for Business, Energy & Industrial Strategy (BEIS), these lessons are explored through an in-depth case study of viral genomic data sharing during COVID-19. The report follows a commitment made during the UK’S G7 Presidency, as published in the G7 Research Compact, and was designed to add depth and precision to existing recommendations on data sharing across borders, and related research practice and cultural issues. The findings presented in this BEIS-commissioned case study are also closely aligned to those outlined in the World Health Organization’s recently published guiding principles for pathogen genome data sharing. It is hoped that both documents can provide valuable lessons to support equitable and efficient responses future crises. Our full report, including detailed findings, is now publicly available to view here.
The full report brings together an evidence base of 295 sources, the views of 24 interviewees, and insights from 18 international peer reviewers, but those of you looking for a bitesize summary of the lessons learnt can find them below.
Invest for the long term
Effective emergency responses rely on long-term investments in open data infrastructures, standards, skills, and public health. In other words, if we think of sequencing capacity as a pipeline, requiring investments at each stage of the process (acquiring necessary funding, accessing relevant samples and reagents, leveraging latest technologies, and deploying sufficiently trained staff), then the successful creation, sharing and analysis of sequencing data can be enabled.
Unfortunately, the COVID-19 pandemic exposed fundamental weaknesses in pandemic preparedness across global health systems that can be attributed to a lack of sustained investment across the sequencing pipeline. The inconsistent access to the elements outlined above has led to variability in sequencing capability, availability, and quality. In turn, we have been left with gaps in the global knowledge base around how COVID-19 mutated and spread.
To overcome these challenges, and to avoid them resurfacing in future emergencies, a long-term commitment by governments and funders is needed to invest in science, research, and public health infrastructure. Alongside this, there should be a recognition of the critical importance of open, scalable data infrastructure, software, standards, and skills.
“It will be very good for the world if, even in developing countries, we could have a continuous source of funding for studies on infectious diseases and emergence… This will have connections with the sharing of data as one of the requirements [of funding] could be that you have to share your data.”
Take a global perspective
Data sharing is often constrained more by a lack of underlying research capacity, and various political tensions, than by a lack of willingness to adopt open sharing practices. Interventions designed to improve the availability of data must therefore ensure they address the root of the problem.
In our study, we highlight that not all countries or regions have sufficient data-generating capacity, or trained human resources, to collect, disseminate, and analyse viral genomic data. As a result, global sequencing datasets are heavily skewed towards the global north which, during the pandemic, led to dark spots in sequencing capacity and virus tracking. We also note that nations in the global south were seen to be more at risk of facing adverse political and economic consequences from data sharing, thus creating a disincentive to share data as it emerges. We illustrate this through the case of South Africa, where the timely sharing of the Omicron variant had negative impacts on the country’s tourism industry.
With these barriers in mind, and with an understanding that tackling global challenges like COVID-19 relies on representative data from all parts of the world, policymakers and international infrastructures must make efforts to be aware of and responsive to the needs of a diverse and evolving community of users.
“If the world keeps punishing Africa for the discovery of Omicron and ‘global health scientists’ keep taking the data, who will share early data again?”
Professor Tulio de Oliveira (via Twitter)
Create incentives for equitable data-sharing
As actors worldwide began responding to the evolving pandemic, opportunities to improve existing data sharing cultures in academia and public health became apparent. At the heart of the issue is a need for reformed incentives that promote data-sharing across boundaries.
In the case of data generators, recognition and reward are key. We identified a need to continue with ongoing efforts to reward the sharing of reusable data, code, other research objects and accompanying metadata. In addition, the pandemic exposed an opportunity to re-evaluate data access agreements to promote equitable data sharing in emergency situations. There is a need to clarify expectations around speed, quality, and transparency for data generators in differing contexts, such as routine surveillance in public health.
The pandemic highlighted that interactions between actors in research and public health communities are key to maximizing the combination and re-use of scientific and clinical data. To enable these collaborations in the future, ongoing efforts around incentive reform should continue. Policymakers seeking to encourage the early sharing of genomic viral data must also be prepared to adapt their approaches to the needs of different communities, taking appropriate account of their differing incentives and priorities.
“In pathogen genomic data very specifically it’s clear to me that the predominant paradigm is inadequate. We need the data to be available way before any associated publications.”
Adapt to changing circumstances
The COVID-19 pandemic has created an opportunity to re-assess established norms for data sharing. A significant part of this re-assessment can be addressed through ongoing efforts to reform academic incentives. This should also be accompanied by corresponding work to incentivise sharing by public health actors, with strengthened expectations for data-sharing by all parties in an emergency context.
Effectively leveraging research data for public health will additionally rely on the capture of high-quality metadata and the application of technical and legislative solutions that enable sensitive datasets to be used for research and public health purposes at scale.
Overall, any efforts in this direction will require significant collaboration from actors across sectors. Funders, publishers and policymakers have a role to play in setting expectations for open and rapid sharing of research results, data and information in emergency circumstances. Open infrastructure providers must be able to identify and respond rapidly to emerging requirements, while new approaches should make provision for sensitive datasets to be used for research purposes in emergency scenarios.
“We are in this bubble of open science and …. [clinical labs] are in their own bubble. Breaking those silos within science is a tremendous amount of work, and a much bigger issue than I ever anticipated.”
Infrastructure provider (Interviewee)
Move beyond current sharing paradigms
When it comes to viral genomic data sharing, COVID-19 exposed a fragmented landscape populated by actors with divergent perspectives and motivations. For example, between the research and public health communities, different perspectives came to light on the merits of open and controlled models of access to genomic viral data. And, across, high-, middle- and low-income countries, we’ve seen that there are also differing capabilities and priorities in relation to generating, analysing and sharing scientific data.
While fully open-access infrastructures for data sharing offer demonstrably greater benefits than controlled access repositories in terms of data re-use and integration at scale, we find that these benefits cannot be realised in practice unless these infrastructures are accompanied by a transparent and globalised approach to funding, governance and benefits sharing.
The most effective approaches for balancing competing interests in emergency contexts will therefore be those that take the diverse and evolving perspectives across sectors into account, giving all actors a seat at the table in such discussions.
“I think the largest lesson that I’ve learnt from this situation is that you need to pull in a diverse set of voices… We have to think about how the least among us are going to benefit from [sequencing] and why they might care about it. And if we fail at that task, then we will fail to get representative data every time.”
Academic expert (Interviewee)
Towards intelligent open science
So, what do all of these lessons learnt mean for future pandemics?
For open science policymakers, the most important takeaway is the need to consider diverse perspectives and the risk of unintended consequences when formulating policy interventions. This should come with an awareness that different and flexible approaches may be needed to address the competing interests of data generators and data users, and that the most appropriate solutions are highly context dependent.
Across the rest of the scientific community, a renewed focus on prosocial approaches will be needed, and incentive structures and community norms should continue to evolve. In particular, incentives that recognise and reward the sharing and re-use of data at the level of individuals, institutions and nations should be established.
Building on the momentum from the COVID-19 pandemic, now is the time to move beyond existing data-sharing paradigms and towards intelligent applications of open science to be better prepared for future emergencies.
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Image Credit: CDC via Unsplash.