This report is part of a series exploring the challenges and opportunities of technology for policymakers responding to Covid-19. Our companion report, Digital Policy for a Physical Lockdown, looks at how tech can help countries adapt to the radical change in operating environment for citizens, companies and governments.
The Covid-19 crisis appears to put policymakers in an impossible position. If they try to keep their economies open for business, then there will be significant loss of life as health systems are overwhelmed. Alternatively, if they impose strict lockdowns to suppress the spread of the virus, then the resulting economic damage – counted in both statistical lives and jobs and prosperity – may ultimately be worse than the disease itself.
Our recent papers on exit options and strategies for the UK explored the options available in the UK context and concluded that a combination of mass testing and contact tracing offered the best prospects for easing restrictions and restarting the economy.
The UK example is just one instance of a choice most countries face. Carefully applied, technology gives policymakers a possible way through the crisis that reduces otherwise very high costs in terms of lives lost and livelihoods destroyed. But this escape route comes with a price: dramatically increased technological surveillance.
Under the right conditions, this is a price worth paying.
The Covid-19 Trilemma
Even compared to the world’s relatively recent experience with other infectious diseases, the suite of tools made available by new technologies gives policymakers more sophisticated ways to respond.
There are no guarantees that any of these new approaches will be completely effective, and technology must always be understood as a tool, not a solution in itself. But compared to the alternatives, leaning in to the aggressive use of the technology to help stop the spread of Covid-19 – even if the precise efficacy is impossible to quantify ex ante – is a reasonable proposition.
Although this paper is framed in terms of the technology options available to policymakers, it is important to remember that these new opportunities also bring new policy challenges. These must be considered and managed properly; a crisis situation demands decisive action, but not that we abandon our values.
We have previously articulated three key principles for technology policy in relation to the response to Covid-19. When using technology to fight the virus, there are both opportunities and challenges for policymakers relating to each one.
Turn the networked public into an advantage
Widespread adoption of smartphones and other connected devices makes it possible to track what is happening in granular detail and in real time, as almost every action we take leaves a digital footprint. In turn this makes it possible to both get a better view of future macro scenarios and to fine-tune the current policy response down to the level of individual citizens.
Public policy in liberal democracies operates within a framework of protection for individual rights, consent and non-discrimination. Leveraging new capabilities based on the networked public requires a new settlement between the individual and society/the state.
Lean in to innovation and experimentation
Significant advances in both scientific understanding and practical applications – on everything from artificial intelligence to biotech and 3D printing – give us new avenues to explore in terms of detecting and treating Covid-19. Tech companies and the platforms they have built also provide new capabilities to organise and operate effectively at scale.
The pressing need to take calculated risks in pursuit of solutions comes at a point when there is already a huge amount at stake. Many new ideas will fail or have unintended consequences that bring their own problems. Some accepted best-practice procedures, such as randomised controlled trials, will not always be feasible against the clock.
Be more transparent with the public than ever
The internet has dramatically reduced the distance between leaders and citizens, which makes it possible to speak more directly to the public than ever before and build trust through accountability. Beyond this, open access to tools and platforms gives policymakers new opportunities to share the data and evidence that underpins their decisions, and to bring a wide range of expertise to bear to improve it.
The same technologies that democratise access to tools and information also open government up to unrelenting scrutiny, and if not approached properly, this can result in paralysis. It may also be difficult to reconcile radical transparency with traditional tendencies to hold information close and resist giving up new powers once acquired.
To limit the spread of Covid-19, and ultimately save lives, countries need to be able to control the transmission of infection. This is true whether the goal is to suppress the virus in its entirety or simply to mitigate it sufficiently to allow health-care systems to cope. Technology has a role to play at four distinct stages:
Detecting suspected cases
Testing suspected cases
Tracing people at risk
Enforcing social distancing
Detecting the Virus
Technology can help proactively identify likely cases of Covid-19, both at the individual level and when looking at particular groups or locations to prioritise for further investigation. Detection will never be a complete solution as many carriers are believed to be asymptomatic; nevertheless it is the first step for getting a grip on transmission.
Handheld, non-contact thermometer guns equipped with an infrared sensor can quickly measure surface temperature without touching a person’s skin. Some medical professionals and experts have questioned the reliability and accuracy of these sorts of devices. Nevertheless, a number of countries have deployed them in large numbers at train stations, hotels, supermarkets and other public places.
An AI-powered temperature-screening solution is being trialled in Singapore. It uses a smartphone fitted with thermal 3D and laser cameras to take images, which it then analyses using artificial intelligence. The device can recognise human facial features from thermal images to measure forehead temperature.
Kinsa Health in the United States has sold or given away more than 1 million smart thermometers. It uses data from its thermometer readings to estimate the number of people who are ill in different geographies. Pooling data in this way helps to generate a real-time, aggregate picture but is subject to selection bias and involves sharing personal health data.
Researchers at Stanford are investigating the capability of wearables to detect early signs of Covid-19, using data from Fitbit, Apple Watch and other consumer wearable brands.
Beyond direct temperature readings, there are other sources of health data that can also be pooled and analysed to identify infection hotspots. Evergreen Life, in collaboration with data and health scientists, has created an app in which users report their symptoms to generate a heatmap showing how the virus is spreading. And as part of its “data for good” programme, Facebook has stated it plans to ask users whether they have been infected to analyse the spread of the virus.
Health data can also be combined with other sources of insight. For example, by combining data on confirmed cases with other data on population patterns and movements, it is possible to generate predictions about where future hotspots are likely to develop. One of the important barriers to overcome here is bringing the right data together from a range of different sources and owners.
Testing for the Virus
Technology has a critical role to play in mass testing, both in terms of improving the underlying tests and ensuring they are distributed and processed efficiently.
A fast and reliable (high sensitivity, high specificity) antibody test is essential for establishing the prevalence of infection in the population and certifying safe return to work, especially for health-care professionals and other essential workers. Since these tests are not yet available at scale, there is a strong case for supporting scientists and biotech companies with innovative approaches.
One such example is the CRISPR-based diagnostics being worked on by Mammoth Biosciences. Their recent Nature Biotech paper showed clinical validation in real patient samples, with their DETECTR technology uniting two previously separate worlds: rapid testing and molecular testing. If successfully deployed, it would mean testing can be conducted at home, quickly and accurately, at a very low cost (and not necessarily limited to just Covid-19).
Hospitals are already stretched treating people with Covid-19 and cannot afford to be overwhelmed performing tests on new cases. Digital tools have a role to play in coordinating community testing on a large scale, by making it easier to manage when and where tests are conducted, and recording the results. South Korea uses data on symptoms gathered through a smartphone app to inform medics, who pitch tents on roadsides and provide free drive-through testing to residents.
With digital systems for coordination in place, it becomes possible to use the same infrastructure to help prioritise testing for high-priority groups. Going down this route necessarily involves creating new registers of people – whether they are grouped by demographics, vulnerability or key-worker status – and this data must therefore be properly secured and protected from abuse.
Given the scale of testing that is likely to be required, it may be desirable to co-opt volunteers or have citizens self-serve, in which case any app or web interface must be properly designed to meet user needs so that it is actually used at scale.
Ramping up to the scale of testing required may not be possible by relying solely on tests that are administered and processed at medical facilities or labs. But for home testing to be a viable part of the solution there will have to be efficient ways of distributing tests – the traditional approach of collecting them from pharmacies will not be feasible. Rather than building new logistics capabilities it may make more sense to leverage existing online shopping and delivery infrastructure to stockpile test kits and distribute them dynamically.
Contact tracing is a monitoring process that is a central public-health response to infectious-disease outbreaks. Once a case has been identified, it involves listing all those who have come into contact with the infected person, then monitoring and following up with those people.
Contact tracing has always been integral to fighting outbreaks, but digital solutions are largely being explored for the first time. As with traditional measures, how these digital tools are deployed and the speed at which they are delivered is key to their efficacy.
South Korea is using a deep set of tracing measures, including GPS and location tracking. The government has explicitly acknowledged the intrusive nature of the tools being used, but legal changes made in the aftermath of MERS have allowed their use. These changes include amendments to the country’s Infectious Disease Control and Prevention Act, which gave the Minister of Health the “legal authority to collect private data, without a warrant, from both already confirmed and potential patients.”
The highly invasive nature of location tracking has prompted the development of alternative implementations that try to increase privacy protections. Prominent among these is an MIT-developed app, Private Kit: Safe Paths, which stores up to 28 days of users’ GPS location data (harder to anonymise, but researchers are exploring new cryptographic approaches) and allows them to share that information with health officials if they test positive for the virus.
Alternative approaches focus on proximity rather than location, typically taking advantage of the short-range Bluetooth functionality of most smartphones. This has the advantage of eliminating the need to collect personal location data. Instead, phones anonymously track other devices they have been near, and when a new case is detected, the person’s smartphone data can be recovered and used to notify people who may have been at risk.
Bluetooth-based apps do still pose security and privacy risks, particularly if the data is processed in ways that make it possible for the authorities to bulk collect and/or de-anonymise individual records. The potential for this is heightened during the crisis as countries implement emergency powers enabling the collection and processing of confidential medical data to assist national planning.
However, proximity-based tracing does not require users to surrender their privacy; a number of security researchers have developed various decentralised implementations such as DP-3T that are privacy preserving and eliminate the need for a central database. Covid Watch, which is backed by Stanford University, has been working on similar technology, releasing an open-source protocol for privacy-preserving, decentralised Bluetooth contact tracing. This has since become a broader TCN Protocol, with partners from around the world including CoEpi, Openmined in the UK and Cotect in Germany forming a coalition to increase efforts for a shared, privacy-first protocol.
Singapore’s TraceTogether app operates a hybrid model, with an opt-in approach and clear and time-limited conditions on how matched data is centralised. However, the government has said that only around one in six people downloaded the app in its first two weeks; this is enough to help but is well below the 60 per cent figure believed to be needed for an automated system to be fully effective. One important constraint is that iPhone users must keep the app open and their screen unlocked for it to work; this is a security measure imposed by iOS and hugely impacts convenience.
Apple and Google have now announced a collaboration on a privacy-protecting approach to contact tracing that is interoperable between Android and iOS. The first stage will be a set of common APIs, followed by direct integration of Bluetooth contact tracing into the underlying platforms. At this point high take-up looks viable, as official apps can be promoted easily to users and, once installed, run in the background without affecting normal phone use or battery life. The constraint that will ultimately matter is how many people have access to a compatible device; assuming 80 per cent smartphone penetration and 80 per cent of these handsets being compatible, good take-up should be well within reach and a best case of 65 per cent of the population seems reasonable.
Importantly the tech companies are prioritising a privacy-preserving approach, with anonymous identifiers and encryption keys that change frequently and are difficult to link. Although some theoretical risks will always remain around tracking and deanonymisation, and there will always be a balance to be struck between simplicity, scalability and reasonable security.
Understanding and balancing these issues is important because they are likely to have a material effect on the take-up, and therefore ultimate utility, of contact-tracing apps. Health-care institutions often have high trust from the public; in a country like the UK, where the NHS is one of the most trusted brands, this is a real opportunity. But trust can easily be compromised by poor technology choices – which in turn alienate people who have concerns about privacy, are sceptical of government motives, or simply put a premium on convenience.
Getting most people who have a smartphone to use an app will be much more viable if it is easy to use and if people understand what data is being used and how it will be protected. Far better to be able to get people to buy in to a positive, collective effort to save lives that is easy to trust and participate in than to provoke resistance from the outset.
The tech companies are requiring apps that use their platform to operate on an opt-in basis only, in order to protect users from coercion and to safeguard against any future attempt by governments to use contact-tracing apps for wider population surveillance. They have also said that users will have to use apps provided by public-health authorities to enter positive test results, in order to help limit the risk of disruption from unverified user-generated reports of infection.
Proximity apps and other digital solutions are not a replacement for traditional contact tracing measures. There are important contextual points that will not always be picked up (being near to someone in a closed room may be a different risk to being near them outside). So success will depend not only on effective apps with high take-up, but also having sufficient numbers of people able to do coordinated contact tracing, augmented by tech and insights from apps, at scale. Technology can help to organise this number of people, including getting them trained en masse and providing them with the software infrastructure necessary to track tasks and record actions taken.
Enforcing Social Distancing
Contact tracing is only a means to an end. If individuals who are identified as likely to become new vectors of infection are not isolated, then there will be no reduction in transmission. As countries introduce social-distancing rules, technology can help people to understand what the rules mean and manage their compliance with them. These options are equally applicable to countries that have imposed blanket measures and want to ensure they are followed.
Taiwan, which has a tech-enabled civic culture, has been effective in its response to Covid-19 and has recently announced a mobile phone-based tracking system – referred to as an “electronic fence” – that uses location-tracking to ensure that those who are quarantined stay at home.
If countries want to exempt some individuals or groups from social-distancing rules, then it may be helpful to have a reliable way for people to assert their eligibility. At present this is often ad-hoc, for example presenting an official ID for health-care workers. Looking ahead, countries may wish to consider options like relaxing the rules for people who are known to have had the virus and are now presumed immune, or for certain demographics who are believed to be at significantly lower risk. This approach could also be used to record people with confirmed immunity, in order to exempt them from further testing.
In such cases, a digital credential – perhaps biometrically secured and stored on a person’s smartphone – may be the best way for people to be able to carry secure, verifiable proof of their status without leaking other personal information. The flipside of this is the prospect of citizens who are accustomed to personal freedom now being subject to requests to verify their right to mobility or exemption from certain conditions, along with a requirement to impose credible sanctions on those who fail to comply.
As with the other digital measures discussed in this paper, policymakers must remain mindful of distributional issues around access to devices and readiness to participate.
Increasing Health-System Capacity
Despite measures to prevent the spread of the virus, many people will still become infected. Experts warn that a Covid-19 vaccine is unlikely to be available in the next 12 months, so urgent action needs to be taken to ensure health systems are well prepared to treat patients. Technology can help increase health-system capacity in two main ways. First, by being applied to accelerate the production of equipment and to get it into the system where it is most needed. And second, by helping organisations to quickly learn and adapt their treatment protocols as our understanding of the virus evolves.
The surge in demand caused by Covid-19 cases is already putting a significant strain on health-care systems around the world. Countries need access to enough equipment and treatments to meet likely needs over the months ahead. New or improved options that prevent deterioration or accelerate recovery times will be particularly important.
There is an urgent need for essential equipment such as PPE and ventilators. Traditional manufacturers are critical here, but policymakers must also be willing to think unconventionally and explore and support a range of innovative equipment solutions such as 3D printing and robotics for medical use, delivery and cleaning.
3D printing can be done much more quickly than traditional production, and can deliver full products, partial products or components that enable other products to be adapted for new uses (for example adapting diving masks for medical use). Because 3D printing capacity is spread around different organisations, there is often a need to coordinate efforts. Initiatives including EndCoronavirus.org and 3DCrowd are attempts to do this for ventilators and face masks respectively.
3D printing to help produce ventilators has been accompanied by an explosion in open source efforts, including groups at University College Dublin and MIT who have adapted “ambu-bags” (self-inflating bag resuscitators) and an engineer in Colombia building a low-cost design with a Raspberry Pi.
Varying degrees of success have also been apparent in the UK, after the government put out a call for industry to help build ventilators. A collaboration between University College London and the Mercedes F1 team has resulted in the production of 10,000 approved CPAP breathing aids, but a lack of clarity at the outset has meant many products are unlikely to meet clinical requirements. The Medicines and Healthcare products Regulatory Agency (MHRA) have updated guidance to rectify this, but it has meant that government is behind on its stated ambition of having 18,000 built by now.
Engineers in China have developed a remote-controlled robot that health-care workers can use to treat Covid-19 patients while keeping at a safe distance. Robotics can also be used to help disinfect hospitals and ambulances. For example, the Danish company UVD robots has provided disinfection robots to China, Europe and the US.
The UK has announced that the NHS is working with the tech companies including Amazon, Microsoft and Palantir to use data to help predict where ventilators, hospital beds, and medical staff will be most in need. More technological solutions of this kind are likely to be necessary as governments step up their response.
The time-critical nature of equipment needs means there is an argument for streamlining regulation if it is proving a bottleneck to production and distribution. The US Food and Drug Administration recently introduced an Emergency Use Authorisation for ventilators and associated parts, which is already encouraging innovation in the production of medical equipment. It has also openly collaborated with a group of researchers at institutions such as Harvard and Stanford to produce guidelines for producing 3D-printed test swabs.
Panic buying has been witnessed in various forms during the crisis, and governments need to take measures to stop hoarding. Taiwan’s government has developed a system in which national health insurance cards are digitally scanned when a person buys a mask. It has also released its data to the public, enabling the creation of maps with real-time mask availability information. This requires a digitally mature system, but other governments may need to consider similar measures.
In some countries there has been a grassroots effort to donate PPE to health-care workers, but this will need to be effectively coordinated. Again technology can play an important role in aggregating donations and matching them to local needs.
Treatments for Covid-19 must be safe in humans, able to be quickly manufactured and deliverable in low-resource environments. Despite anecdotal evidence of some treatments being effective for Covid-19, no treatments are clinically proven. Technology can help to accelerate the search for treatments in both simulation and in clinical settings.
DeepMind has used AI software to study how proteins fold and released a detailed portrait of the virus on its website under an open license.
Researchers at London-based BenevolentAI have been exploring the use of existing drugs to treat the virus by using AI to crunch huge amounts of public data. OneThree biotech is also hoping to speed up the timeline for drug developers by building an AI platform that aims to identify targets as well as potential risks and side effects at an early stage.
Oracle’s cloud-based Therapeutic Learning System, which has been donated to the US government, gathers real-world patient data from health-care professionals with the aim of discovering effective treatments.
The White House has launched a COVID-19 data hub to bring together an open set of scientific literature and machine-readable data on Covid-19.
The COVID-19 Therapeutics Accelerator – launched by the Gates Foundation, the Wellcome Trust and Mastercard – aims to deliver 100 million treatments by the end of 2020 and is seeking these funds from philanthropists and governments to rapidly develop and scale-up access to therapeutics.
All of these efforts hinge on the software and data infrastructure necessary for companies, non-profits, researchers and the public sector to innovate and respond quickly to the crisis. And because insights are informed by data, mechanisms for organisations around the world to work together and share data will be critical.
One of the biggest challenges in this field is reconciling data sharing and analysis with privacy and patient-confidentiality concerns. Governments may choose to collect and process confidential data for legitimate public-interest reasons, particularly during the crisis, and may do this under existing rules or by invoking emergency powers. The critical point for policymakers will be to ensure these steps are proportionate and properly explained.
Data and analytics-based insights into effective treatments are not a substitute for randomised controlled trials. But in a time of crisis, these insights have one key advantage: speed. Aggregating data and looking for hidden patterns formalises the experimentation and intuition that happens on the front line, surfacing new ideas faster and making it easier to prioritise candidates for future trials.
Improving Forecasting at Scale
There is still much we do not know about Covid-19 and its knock-on effects. One of the threads running throughout the discussion of how technology can help us fight the virus is around the use of data to allocate scarce resources and generate actionable insights. Of course data alone is not a panacea – those wielding data-driven conclusions must be able to situate them in a reasonable explanation of the underlying causality – but with the crisis evolving in real-time, access to live data and modelling is essential for policymakers and researchers to respond to Covid-19. One of the key lessons that has already come to light is the need for governments to work together to build new systems that can track, predict and prevent global disease outbreaks using digital data. The crisis has also highlighted the fragility of some of the world’s leading health systems and missed opportunities to share data to inform coordinated decision-making.
Openness of data has been key to the development of policy and the response to Covid-19 to date. For example, it has helped inform estimates of incubation periods and transmissibility, which in turn have helped drive policy choices such as lockdowns and social isolation.
However, missing data and gaps in our understanding have resulted in misinformation or lack of clarity. Despite a move towards open data and countries being able to lean on a variety of real-time data sources, countries including the US have not been reporting in real-time, which means global understanding of the situation trails behind reality.
Given the fast-moving nature of the crisis, access to reliable forecasts is a critical component in being able to adjust a country’s policy stance effectively. Many of the changes policymakers may want to make may have a lead time measured in days; consequently tools and technologies that help paint an informed view of likely near-future scenarios will be very important.
The UK’s announcement of an NHS platform that will consolidate metrics such as occupancy levels at hospitals, waiting times and lengths of stay for Covid-19 patients is an important step. Clear, real-time, actionable data will be critical for the response and will ensure that those managing it know how the system is coping, from levels of ICU utilisation to where hotspots are developing.
There also seems to be a pressing need for more open-source datasets and models for diagnostic purposes, such as the Covid Chest X-Ray Dataset. Achieving this will require the health community and governments to make data available as quickly as possible.
For genomic sequencing and drug discovery, the UK has made an important step with the Covid-19 Genomics Consortium, while initiatives such as the RCSB Protein Data Bank, the Global Health Drug Discovery Institute and Nextstrain are all crucial.
In the technology sector there is an increasing debate about the role of infodemiology, which centres on scanning the internet for user-generated health-related content with a view to informing the public-health debate. The Google Flu Trends project, which looked at search trends as a leading indicator for seasonal influenza, is an early example of this.
More broadly the democratisation of health information via the internet opens up new opportunities and challenges around public-health messaging and the role of traditional authorities. Technology companies were the first major sector of the economy to introduce additional precautions and then close their offices; the individuals leading them and making these decisions are also those closest to unmediated access to experts via the internet.
There are also questions to explore around how other sources of real-time data are leveraged in pursuit of public-health goals. The technology that underpins most of the modern economy also generates huge amounts of data, covering everything from how people are moving around (drawn from mobile-phone networks, transport systems and supply-chain managers) through to detailed records of people’s individual characteristics and behaviours (drawn from their financial data, online profiles, wearables and other sources).
The quest for insights will generate huge pressure to combine disparate datasets in the hope of finding new solutions; the test for policymakers will be approaching this in a way that earns public trust with properly defined goals and oversight.
Covid-19 is a hugely complex, systems-level problem, and technology alone cannot and will not be a silver bullet to solve it. Nevertheless it is clear there are hugely important applications in terms of controlling transmission, increasing health-system capacity and improving forecasting at scale.
All of these domains are critically important for policymakers. As we increase our ability to master these three dimensions of the problem, we increase our ability to escape from the choice between protecting lives and protecting the economy.
The price of this escape route is an unprecedented increase in digital surveillance. In normal times the degree of monitoring and state intervention we are talking about here would be out of the question in liberal democracies. But these are not normal times, and the alternatives are even more unpalatable.
This is quite different from the traditional debate about whether confronting security threats to our way of life merits sacrificing the values of freedom and privacy that define us. Covid-19 is not an ideology, and rebalancing the contract between citizens and the state to take advantage of the capabilities of new technologies is not capitulation.
Instead, in the face of the unprecedented crisis caused by Covid-19 we should be looking to maximise the ways in which technology can improve the world’s chances. And in doing so we should approach policymaking intelligently, so that the actions we take are proportionate and lawful, and so that we are able to chart a path to unwinding emergency measures as the crisis eventually recedes.
Rules of Engagement
Technology provides the tools for policymakers to use, but it is up to us to apply them to our most important problems in a focused way, to ensure that the decisions we make in relation to technology and the fight against Covid-19 are consistent with our values and principles. The analysis presented here of the tools on offer and the opportunities and risks around them takes us to some general rules for policymakers looking to bring technology to bear. These fall into two categories: gold standards that policymakers should aim for, and guardrails that provide essential protections against undesirable outcomes.
Make things open. Our networked world massively amplifies the impact of new ideas and expertise, but policymakers need to quickly get used to operating on a default model of feedback and collaboration. Open data, open-source software and open platforms all have a part to play in maximising our collective impact.
Prioritise privacy, earn trust. Technologies for monitoring and analysing the data generated by individuals necessarily involve a level of intrusion. But policymakers have choices, and these choices are key to public trust and acceptance. All else being equal, privacy-protecting architectures should be preferred over the alternatives.
Think global. Covid-19 is a global challenge, and technology and the internet know no borders. Many of the most successful technology companies and products have focused on tackling common problems and applying their solutions worldwide. Policymakers are already overstretched; far better to work together and avoid duplication where possible.
Form partnerships. Governments have political authority, but when it comes to practical delivery of new technologies and the management of complex data platforms, many private-sector partners will be best placed to step up. Policymakers should seek to leverage the capabilities of commercial partners and local players to roll solutions out quickly.
Experiment and iterate. In a fast-moving environment it will never be possible to get everything right the first time, or to precisely pre-empt future needs. But taking steps to increase optionality and generate feedback for learning and improvement will be hugely valuable. Although the stakes are high, this is actually the time for more calculated risks.
Keep humans in the loop. Technology matters ultimately because it serves the people on the front line and the public they are trying to protect. All of the tools we have been talking about should support decision-makers and practitioners, shouldering some of the load in the most difficult circumstances.
Be inclusive. Many of the tools outlined in this paper assume access to devices and/or the digital skills to use them confidently. When widespread participation is so important, policymakers will need to pay special attention to both usability and to protecting and catering for the people who are digitally excluded.
Establish independent oversight early. Taken together, the technologies described in this paper represent an unprecedented extension of the state’s surveillance activities. Introducing scope for abuse is unavoidable, even when governments have the best of intentions. The best way to protect against this is independent, credible oversight from the very beginning.
Enforce transparency. If making things open is the aspiration, then radical transparency is the backstop. So much of the technology debate takes us into new territory and the public will rightly expect to know what decisions are being made, what evidence informed them and how they can be challenged. There must be binding mechanisms to enable this.
Deploy sunset clauses. An unprecedented increase in digital surveillance is acceptable given the alternatives. But there are good reasons why liberal democracies have resisted these sorts of measures in normal times, and we should be wary of emergency measures becoming the new normal. All new measures should fall away unless actively renewed.
Actions for Policymakers
Technology has a critical role to play in the fight against Covid-19. Governments should:
Deploy official apps to augment significantly increased contact-tracing efforts. To increase trust and therefore participation, these apps should be made available on an opt-in basis, adopt privacy-protecting architectures and require case reports to be certified by an appropriate authority. Governments must also promote apps clearly to the public and develop a narrative emphasising participation as part of a positive, collective effort.
Establish a real-time, single source of truth showing the overall demand and capacity of the country’s health-care system. Where the required data is currently fragmented, governments should break down any regulatory or technical barriers immediately.
Require businesses to share relevant operational data with the authorities for the express purpose of assisting the response to the crisis. This should include telecoms operators, transport and logistics platforms and other commercial entities.
Require technology platforms to share aggregated user insights with the authorities for the express purpose of responding to the crisis. This should include search and social media trends, and telemetry from wearables and other connected devices.
Commission data-science efforts to search for hidden patterns in the data and actionable insights that arise from them. These should be properly interrogated and used as an input to holistic decision-making; models should be neither neglected nor overemphasised.
Join a global consortium to share patient data in order to accelerate the search for treatments and an eventual vaccine. The virus does not discriminate between nationalities; all countries should be prepared to pool their data for the greater good.
Set up regulatory sandboxes and IP exemptions for new equipment, link these to government-backed accelerators and place advance purchase orders to pull new equipment and manufacturing approaches through from ideation to delivery.
Develop a digital platform to manage and direct community participation. The right coordination can make the public a force multiplier for public policy, for example supporting contact tracing efforts, delivering mass community testing or cascading authoritative public-health advice.
Develop a digital credential to assist the selective lifting of restrictions. A secure digital credential is harder to forge and faster to distribute than paper certificates. There must be a practical alternative and no discrimination for people who do not have a smartphone.
Prohibit the linking of apps and services in ways that are de facto coercive, for example linking the issuance of digital credentials to participation in a tracing programme. If it is necessary to deem participation in a scheme mandatory, this should be legislated for.
Introduce specific rules to ensure that personal and/or confidential data collected and processed as part of the response to Covid-19 is deleted at the earliest reasonable opportunity, ranging from 14 days (proximity data) to six months (commercial data).
Immediately establish independent oversight mechanisms for the use of confidential patient data and other data collection and processing related to Covid-19. The Investigatory Powers Commissioner’s Office in the UK may be a good model for this.