Economic information theory can help policymakers prioritise testing and understand the costs of taking the wrong action during the COVID-19 pandemic

How are countries going to establish testing regimes that minimise the spread of COVID-19 and allows economic activity to return? Elias Papaioannou, Professor of Economics at London Business School and Academic Director of the Wheeler Institute for Business and Development was joined in conversation with Andrea Galeotti, Professor of Economics at London Business School, and co-author, with Paolo Surico, of “The economics of a pandemic: the case of COVID-19”, to discuss the optimal testing strategy for countries across the world.

  • The two approaches taken by countries across the world, testing based on symptoms and testing based on non-symptoms, is broadly in line with the capacity and availability of tests in each nation; 
  • Testing regimes that include asymptomatic individuals show different characteristics than where only symptomatic hospitalised patients are tested, leading to a very different understanding about the carriers of the disease, influencing any strategy to fight the virus; 
  • There needs to be an economic assessment of the cost for society if the government does or does not test certain individuals, based on the impact of knowing whether an individual is infectious; 
  • Policymakers need to categorise individuals in groups, based on their probability of infection and the cost of taking the wrong action given their state, as well as the opportunity cost of not giving the test to somebody else; 
  • The economic theory of information can help develop a tool which enables policymakers to prioritise testing for individuals and groups, as well as determine the information required in order to ease lockdown measures.  

While there is variability across countries on the number of tests taking place, the quality of testing is more important

As explained by Professor Galeotti in his article, ‘How a COVID-19 Testing Model No One Is Talking About Could Save Thousands of Lives’, there are a number of different considerations policymakers need to evaluate when putting a testing regime in place.  Clearly, every country in the world would like to test as much as possible, but there is a limitation on capacity and availability. Countries with limited availability have prioritised testing for very symptomatic individuals, for example, the UK and Italy, where people who are ill in hospital are tested. Countries with more capacity, such as Germany, were able to also test individuals who are mildly symptomatic or even asymptomatic, because of the capacity they have in their laboratory system. This has meant they are able to test all healthcare workers because they are in an important category to prevent the spread of the virus. While there is variability in the number of tests taking place, a more important factor to consider is what Galiotti calls the ‘quality’ of testing.  

Countries like Iceland and South Korea that tested asymptomatic individuals found that infected people are generally young individuals and not necessarily older people, unlike countries such as the Netherlands and Italy where only symptomatic individuals were tested. This very different information about the carriers of the disease is clearly very important to formulate any strategy to fight the virus. 

Policymakers need to determine the costs and benefits of giving each individual a test in order to prioritise where their resources are allocated

Galeotti has researched the allocation of testing resources through an economic lens that enables policymakers to evaluate their testing strategy with a framework that considers the value of testing. He considers how public health authorities can choose how to allocate tests that will inform the government on how to design social distancing measures. The categorisation of individuals needs to consider two key dimensions: the probability that an individual is infected and the loss the government will face to society if they make the wrong judgement about whether that individual is infected or not.  

Galeotti stresses the importance of a multitude of factors that policymakers need to consider, such as if the individual needs to commute to get to work, how densely populated his or her neighbourhood is to gain an understanding of how he or she might spread the disease further if they were to return to normal activity. This information is important to determine the cost and benefit of giving this person a test. Galeotti cites the example of an asymptomatic healthcare worker, who by the nature of their job is a greater cost if they have to isolate unnecessarily because we need their support on the frontline during the pandemic, but also if they are infected, they will cause a great cost because they work in a densely populated workplace which means they might spread the disease to many vulnerable people. This pre-test information should allow policymakers to categorise individuals in groups, based on their probability of infection and the cost of taking the wrong action given their state. This test allocation will also enable policymakers to redefine the probability of infection, as we will learn about this individual and then be able to choose whether to isolate them or not to minimize the losses that we will incur by taking the wrong action. To this extent, there is less value testing people who are already displaying symptoms, as it is likely that, as there is no treatment in place for the coronavirus, the government will simply ask them to maintain isolation, rather than changing their approach as a result of the test.  

According to economic theory, the test is only valuable is the action of the decision-maker changes as a result of having this information. For example, a PCR test showing whether an individual is infected at that point in time or not can give false positive or false negative errors, based on the sensitivity and specificity of the tests. The amount of variability across different tests means that an individual test in and of itself might not be valuable, especially if the action you take upon learning the result of the test is the same. The test needs to inform the decision-maker to formulate better strategies if it is going to be valuable. This is because there is also an opportunity cost of testing one individual when tests are scarce. Based on an individual’s characteristics, where is a greater value to the policymakers of testing certain groups than others, with the government being indifferent to whether some people have to isolate or not depending on their economic productivity when under lockdown? 

Policymakers need to consider the individual and collective value of testing. For example, an individual may present themselves to a hospital with symptoms, the value of testing them depends on the course of action taken once certain the individual has COVID-19. It is unlike testing for cancer, as we have specific cures for individuals based on the outcome of the test that will impact the efficacy of their treatment. With coronavirus, there is limited value because there is no specific way to cure the patient. As medical science is developing, it may be the case that if you are able to identify COVID-19 early on you can reduce the length of stay at the hospital for patients, which is a large issue because hospital capacity is constrained. If this becomes the case, testing for COVID-19 early on will have large individual and collective value. These are the sorts of dimensions that need to be quantified, according to Galeotti, in order to make more effective decisions.  

Having detailed pre-test information will help categorise individuals and target testing to prevent further outbreaks. This includes demographic information, as well as medical records. Serological tests can also help by using a representative sample of the population to provide information to inform any lockdown exit strategy. This representative sample can lead to a standard statistical model applied across the entire population, as we have seen already used by the Office of National Statistics in the UK. This will help allocate tests in a targeted way to the right people. Contact testing will also help understand more about different individuals and how they interact with others.  

Elias Papaioannou’s conversation with Andrea Galeotti is part of the Wheeler Institute’s COVID-19 series – bringing together the expertise and experience of our extended community to understand, illuminate and offer solutions to the challenges created by COVID-19. Our differentiating factor is the role of business in addressing these challenges, with a focus on the implications and actions for those in developing countries. 

If you’re interested in following the Wheeler Institute COVID-19 series, check out our previous episode, ‘Quantity of tests rather than quality could be the answer to COVID-19,’ with Professor Kamalini Ramdas.

Andrea Galeotti is a professor of economics at London Business School. He is an expert in microeconomics, industrial organisation and game theory. His research focuses on the economics of networks, with a particular interest in business strategies in network industries. 

Elias Papaioannou is academic director of the Wheeler Institute for Business and Development and professor of economics at London Business School, focusing on international finance, political economy, applied econometrics and growth and development. 

More from Andrea Galeotti, Professor of Economics at London Business School:

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