[TOTM: The following is part of a blog series by TOTM guests and authors on the law, economics, and policy of the ongoing COVID-19 pandemic. The entire series of posts is available here.
This post is authored by Julian Morris, (Director of Innovation Policy, ICLE).]
Governments are beginning to lift the lockdowns they imposed to slow the spread of COVID-19. That is a good thing. But simply lifting the restrictions won’t immediately take us back to normality. For that to happen requires a massive investment in mechanisms that will rebuild trust.
Prior to COVID-19, people implicitly trusted that travelling on public transit, working in an office, attending a ball game, or going to a shopping mall would not subject them to the risk of infection by a potentially deadly virus (or any other terrible eventuality). In the wake of the pandemic, this implicit trust is gone. Many people are afraid of COVID-19 and will require reassurance. While governments likely contributed significantly to the loss of trust, they are likely not in the best position to rebuild that trust. The onus is thus on businesses and civic organizations to provide reassurance and rebuild trust. This post outlines two ways businesses can contribute to this effort.
Lockdowns and the Trust Deficit
As the incidence of COVID-19 began to rise dramatically in March, governments across the world imposed “lockdowns.” These curfew-like arrangements have gone well beyond the limits on public gatherings and other “social distancing” strategies deployed during previous major pandemics such as the Spanish ‘flu of 1918-19. Indeed, they are among the most far-reaching restrictions ever imposed on human activity during peacetime. Hundreds of millions of people have been cooped up at home for nearly two months, allowed out only briefly each day for exercise or to buy groceries. Millions of those now at home have also lost their main source of income.
Governments are now finally beginning to remove some of the most severe of these restrictions, allowing more businesses to operate. As they do so, businesses are trying to figure out what the post-lockdown economy is going to look like: Will employees come back to work in offices? Will customers shop in stores, eat at restaurants, visit movie theatres, and use rideshares, taxis, planes, and public transit?
Many people are fearful about the consequences of going back to work. A recent IPSOS-MORI poll for the Washington Post found that 74 percent of American adults want policymakers to, “keep trying to slow the spread of the coronavirus, even if that means keeping many businesses closed,” while just 25 percent prefer to, “open up businesses and get the economy going again, even if that means more people would get the coronavirus.” Meanwhile, in a recent survey in the UK, the TUC union found that 40% of workers were worried about the prospects of returning to crowded workplaces.
The loss of trust is likely in part be due to conditioning: for the past two months we have been told by all and sundry to avoid other people (except over Zoom). Governments likely contributed to this through their promotion of scary predictions that millions could die if people didn’t “stay home, stay safe.” Partly, however, it is a natural reaction to the perceived threat posed by COVID-19.
For the elderly and those with underlying conditions more likely to be adversely affected by COVID-19, such anxiety is understandable. But even many people less likely to become seriously ill or die from COVID-19 are worried. This is also not surprising: They may have heard horror stories of young, otherwise healthy people who ended up on a ventilator and either died or suffered permanent lung damage. Or perhaps they read about the mysterious effects COVID-19 can have on other organs, ranging from the intestines to the brain. Or they may have a more vulnerable person in our household and are worried about the possibility that we might infect them. Or, as I am sure is the case with many, they just don’t know—and this is their reaction to uncertainty (fueled, in part by the now-discredited predictions of doom).
Regardless of why a person fears COVID-19, the fact is that many do. And one thing common to all of them is a trust deficit. Given widespread uncertainty regarding who has the virus, how can one trust that the business one works, shops, or dines at provides a safe environment free of COVID-19? This even extends to friends and colleagues: how can one individual trust another individual they might encounter while at work or at play? And it applies also to the use of taxis and rideshares; how can riders and drivers trust one another?
It might be argued that since governments were in no small part responsible for generating the trust deficit, through their well-intentioned but probably misguided efforts to lock down the economy and constant exhortations to avoid all human contact, they should now be trying to do what they can to rebuild trust. Unfortunately, however, they may not be in a very good position to do that. While governments are quite good at scaring people (“I’m from the government and I’m here to help”), they are less good at providing reassurance (“I’m from the government and I’m here to help”), or even data. In other words, governments aren’t much good at engaging in the kinds of “costly signalling” necessary to build trust between individuals and businesses. As a result, much of the responsibility for rebuilding trust will fall on businesses and civic organizations.
Businesses can do several things that would likely reduce this trust deficit and allay the fears of employees and customers. First, they can establish, communicate, and implement clear standards for employees and customers regarding the practices to be adopted to reduce infection risk. Second, and relatedly, where employees are likely to be working in close quarters with one another or with customers or suppliers, they can adopt mechanisms to establish the COVID-19 status of those employees, suppliers and customers (somewhat along the lines of the system implemented by Taiwan in February and subsequently elaborated by Hal Singer in his post in this series here).
The following sections briefly consider how such systems might work.
Companies that have not been locked down are already implementing processes to limit the exposure of employees to potentially infected customers, suppliers, and other employees. For example, many supermarkets require staff to use masks and/or protective screens and gloves. Some stores also require customers to wear masks, limit how many people can be in the store, and impose distancing rules. Some have even built seemingly permanent screens in front of check-out clerks and imposed seemingly permanent rules for in-store movement. Other stores and restaurants are currently limiting service to take-out and delivery.
At present, the approaches taken by businesses vary considerably. There is nothing inherently wrong with this; indeed, it is a healthy part of a market process in which companies develop different solutions to the same problem and allow consumers to pick and choose the ones that work best for them. Consumers can be aided in this process by reading reviews and ratings provided by other consumers; that model has worked well for goods and services purchased online. As Paul Seabright has noted, these systems are designed to enable users to build trusting relationships with suppliers. Survey data suggest that consumers find such systems more trustworthy than government regulations.
But when consumers are not well placed to evaluate the most effective solution, for example because it is difficult to observe the effectiveness of the solution directly, it can be helpful for third parties to evaluate the various solutions and either rank them or set out voluntary pass-fail standards. COVID-19 is just such a case: individual consumers and employees are unlikely to be in a good position to evaluate the relative effectiveness of different processes and technologies designed to limit the transmission of SARS-CoV-2. As such, pass-fail standards developed and/or validated by credible, independent third parties are likely to be the most effective way to help rebuild trust.
Standards will vary depending on the type of establishment and activity. For some businesses, such as theatres, gyms, and mass transit systems, the standards will likely be more onerous than others. Plausibly, such establishments could reduce transmission through such things as: mandatory masks, mandatory use of antiviral hand sanitizer on entry, regular cleaning, the use of HEPA filters (which remove the droplets on which the virus is spread), and other technologies. But given the very close proximity of people in such systems, often for extended periods (half an hour or more), the risk of significant viral load being transferred from one person to another, even if wearing basic masks, remains.
For standards to be effective as a means of regaining the trust of employees, suppliers, and consumers, it is important that they are communicated effectively through marketing campaigns, likely including advertising and signage. Standards will also likely change over time as understanding of the way the virus is transmitted, technologies that can prevent transmission, and hence best practices improve. The need for such standards will also likely change over time and once the virus is no longer a major threat there should be no need for such standards. For these reasons, standards should be both voluntary and developed privately. However, governments can play a role in encouraging the adoption of such standards by legislating that organizations that are compliant with a recognized standard will not be liable if an infection occurs on their property or through the actions of their employees.
In addition to other practices designed to reduce transmission of the SARS-CoV-2 virus, some businesses have begun testing employees for the virus, to determine who is and who is not currently infected, so that infected individuals can be isolated until they are no longer infectious (employees who are required to isolate continue to receive their salary). Some businesses are also considering testing for antibodies to the virus, to determine who has had the virus and likely has some immunity. By doing such testing, businesses are probably reducing transmission both among employees and between employees and customers to a greater extent than by merely implementing technologies, hygiene and distancing rules. But the tests are not perfect and given the potential for infection outside work, it is possible that an employee who tests negative on one day could then become infected and be infective a few days later. While daily testing might be an option for some firms, it is unrealistic for most—and will not solve the trust problem for most individuals.
CV19 Status Verification
This brings us to the second major thing that business can do to reduce the trust gap: status verification. The idea here is to enable parties to ascertain one another’s current COVID-19 status without the need to resort to constant testing. One possible approach is to use a smartphone-based app that combines various pieces of information (time stamped virus tests and antibody tests, anonymized information about contacts with people who subsequently tested positive, and self-reported health-relevant data) to offer the most accurate and up-to-date status of an individual.
In principle, such a status app could be used by employers to minimize the likelihood that their staff have COVID (and to require those that may be infected to self-isolate and obtain a test). But their potential application is far wider:
· Universities, churches, theatres, restaurants, bars, and events might utilize the status app not only for employees but also to determine who may participate and/or what forms of PPE they should utilize and/or where participants may congregate.
· Airlines might utilize status apps to determine who might fly and where passengers should be seated.
· Jurisdictions might utilize status apps as a means of facilitating more rapid immigration – and to enable those who most likely do not have COVID-19 to avoid most quarantine requirements.
· Public transit systems might utilize status apps to determine who can use the system.
· Taxis and ridesharing services, such as Uber and Lyft, might utilize data from the status app to help match riders and drivers.
· Personal services facilitators such as Thumbtack might utilize the app to help match service providers and customers.
· Hotels, AirBnB and vacation rental facilitators such as vrbo might use status apps for both hosts (and their employees and contractors) and guests in order to minimize infection risk during a visit.
· Online dating and matchmaking services such as Match and Tinder might utilize status apps to help facilitate virus-compatible matches. (While SARS-CoV-2/COVID-19 is not really comparable to HIV/AIDS, it is noteworthy that sites already exist that seek to match people who are HIV positive.)
How a CV19 Status App might Work
A basic schema for a CV19 status app would be:
· Red = Has COVID-19 (e.g. recently tested positive for virus)
· Red-Amber = May have COVID-19 (e.g. recently tested negative for virus but either has COVID-19 related symptoms or has been in contact with someone who tested positive).
· Amber = Is susceptible: Has not had COVID-19 and likely does not have COVID-19 (e.g. recently tested negative for COVID-19, has no COVID-19 symptoms, and has had no recent known contact with someone who tested positive).
· Green = Has had COVID-19 and is now presumed to be immune (either tested positive for CV19 and then tested negative for CV19, or tested negative for CV19 and also tested positive for Antibodies) (See below regarding immunity concerns.)
This schema is shown in the decision tree below
There are numerous technical issues relating to the operation of an app designed to establish a person’s CV19 status that must be addressed for it to function effectively. First, it will be necessary to ensure that the person using the app is the person whose status is being asserted. It should be possible to address this by storing the information from tests, contacts with infected people, and self-reported symptoms on an immutable digital ledger and use biometric identification both to record and to share status information. (Storing the status information on a person’s phone in this way also avoids the risk of hacking that plagues centralized databases.)
Next there is the question of authenticating test data recorded by the app. Ideally, this would be done by having a trusted third party—such as a doctor, nurse, or pharmacist—verify the data. If that is not feasible—for example because the test was carried out at home—then some other mechanism will be required to ensure the data is input correctly, such as rewards for accurate self-reports and/or penalties for inaccurate self-reports. (Self-reported data could also be treated within the system as less reliable, or simply as tentative—requiring verified test data to be added within a specified period.)
Beyond these verification issues, there remain problems with the specificity and sensitivity of tests—implying a likelihood of both false positive and false negatives. Although there are now both PCR and antibody tests that achieve very high levels of accuracy, even small numbers of false negative PCR tests and false positive antibody tests would clearly create problems for the effective functioning of the status app system. To address these problems, it may be necessary to undertake secondary testing for some portion of the tests.
The more challenging problem is that of infection after tests are conducted. As noted above, this can in principle be mitigated—but not eliminated—by incorporating contact tracing and/or self-reporting of symptoms. Related to this is the possibility that having COVID-19 confers only limited immunity (as has been suggested in relation to some people who have seemingly become reinfected). This obviously poses problems for the notion of a “Green” status; if reinfection is possible, then Green clearly would not be a permanent designation and would require regular testing. The evidence remains ambiguous, with news of five US sailors who had COVID then tested negative twice subsequently having new symptoms and testing positive again; on the other hand, a recent study suggests that people who test positive after recovery do not have a live (infectious) version of the virus.
Contact tracing apps have been used successfully in several locations as part of a strategy for containing COVID-19. However, the only really successful implementations so far have been those in China, South Korea and Hong Kong, which had a mandatory component and were highly centralized. By contrast, apps that required voluntary uptake have generally been less successful.
One reason for the lack of success of voluntary contact tracing apps is heightened concern regarding privacy (for example, the app used in Hong Kong enables anyone to find the gender, age, and precise locations of every person in the city who currently has COVID-19). Of course it is worth repeating Jane Bambauer’s observation in an earlier post that “Objections to surveillance lose their moral and logical bearings when the alternatives are out-of-control disease or mass lockdowns. Compared to those, mass surveillance is the most liberty-preserving option.” But assuming imprisonment is not the only alternative, concerns over privacy are not necessarily unmoored from logic or ethics (pace Christine Wilson’s earlier post). And to address these concerns, several groups have developed privacy-protecting systems. For example, the TCN coalition developed a system that shares anonymized tokens with other nearby phones over Bluetooth Low Energy. That system has now been adopted by Google and Apple in an API that is being made available to government health authorities (but not to other private app developers).
Another reason voluntary contact tracing apps have not been successful is the lack of incentives to adopt them. The main benefit of a contact tracing app is that it notifies the user when they have been in close contact with someone who subsequently tested positive. Logically, the people most likely voluntarily to adopt a contact tracing app are those who are most risk averse. But those people would also presumably be taking strong measures to avoid contracting COVID-19, so they would be less likely to become infected. By contrast, the people most likely to become infected are those who are least risk averse. But those people are least likely to be motivated to use the contact tracing app. In other words, even if there is relatively wide uptake of the app (say, 40% of the population, as in Iceland), it is likely to miss many of the people most likely to be spreading COVID-19 and so would not actually be very useful as a means of identifying and containing clusters.
Tying the contact tracing app to a CV19 Status App potentially overcomes this incentive compatibility problem, since anyone who wants to engage in an activity that requires use of the app would automatically participate in the contact tracing system. It could thus be quite effective at identifying instances of transmission that occur during activities that require the app to be used, which would also presumably be activities that put users at higher risk.
Nonetheless, for the app to be useful as a means of identifying clusters of COVID-19, either a significant proportion of common activities would have to require use of the app (e.g. public transit, rideshares, gyms, and shopping malls) or it would have to be used by at least some proportion of those not required to use it for access to activities.
Adding a symptom monitoring component can help in two ways. First, by offering users a way to self-assess for early symptoms of COVID-19, it encourages more people to download and use the app. More important, symptom monitoring can help identify additional potential COVID-19 infections, both among the individuals reporting symptoms and among their contacts. Thus, the combination of test data, symptom data and contact tracing become the information determining a person’s current status in a manner that is more reliable than relying on any one datum.
It should be noted that even combining these data will not make the status app 100% accurate. Some people with COVID-19 will likely slip through as Green or Orange and others will likely inadvertently be infected as a result. But the number of such instances is likely to be small and certainly much lower than would be the case without the use of the app. Moreover, widespread use of the app should dramatically reduce the infection rate throughout the population, with benefits to all.
Both CV19 standards and CV19 status verification offer potential means by which to address the trust deficit that has emerged in the context of the continuing COVID-19 pandemic. A company that adopts both solutions would likely dramatically reduce the chances of their employees, suppliers and customers contracting the virus on their premises. That would also likely reduce the company’s liability, which could be rewarded by insurance providers offering discounts. Indeed, one could envisage a greater role for insurance companies in designing or certifying the standards and the status app.
However, the real benefits of these systems come not from one or a few companies adopting them but from widespread adoption, which has the potential dramatically to reduce the transmission of the virus both now and in the future (should there be a second wave). This leads to something of a paradox: Governments could mandate adoption, but such an approach may be counterproductive for two reasons. First, much knowledge is dispersed and tacit, so it is generally better to allow private actors to determine which standards to adopt (lest an inferior standard be the subject of a mandate). Second, if companies are genuinely concerned to address the trust deficit, then they will be willing to invest in standards and to limit access though status apps — both of which entail costs. By contrast, if governments mandate the use of standards and apps, they would effectively prevent firms from engaging in such costly signalling, so would undermine at least part of the effectiveness of such tools as trust-generative.