{"id":8203,"date":"2020-06-16T23:01:00","date_gmt":"2020-06-16T22:01:00","guid":{"rendered":"http:\/\/www.economicsobservatory.com\/question\/how-should-we-allocate-limited-capacity-coronavirus-testing"},"modified":"2021-01-22T17:37:25","modified_gmt":"2021-01-22T17:37:25","slug":"how-should-we-allocate-limited-capacity-coronavirus-testing","status":"publish","type":"question","link":"https:\/\/www.economicsobservatory.com\/test\/how-should-we-allocate-limited-capacity-coronavirus-testing","title":{"rendered":"How should we allocate limited capacity for coronavirus testing?"},"content":{"rendered":"

Governments around the world are having to make difficult choices about the allocation of limited testing capacity. Some are testing mainly symptomatic individuals and, if it is possible, giving priority to tests for staff working in hospitals and care homes. Others are also testing non-symptomatic individuals to trace key spreaders of the virus. Figure 1 illustrates different testing strategies adopted across countries.<\/p>\n

Figure 1: Testing policies around the world<\/h4>\n

\"Map<\/p>\n

When one person is tested, this means that someone else cannot be tested. This is what economists call an 'opportunity cost'. These opportunity costs arise not only when we need to decide who <\/em>should be tested, but also how <\/em>and when<\/em>. The testing policy that saves the most lives takes account of all of these opportunity costs.<\/p>\n

What are the costs and benefits of testing?<\/h3>\n

A test allows policy-makers to become better informed about the health status of an individual. The benefit of a test is that it provides information that allows more appropriate actions to be taken. For example, if the test is accurate and the policy-maker observes that an asymptomatic individual is currently ill, then the individual could be quarantined with the benefit of avoiding further contagion.<\/p>\n

We can think about the cost of a test in different ways. One way is to think about the cost of buying and administering an additional test. Another way is in terms of the opportunity cost of the test: this is the benefit of allocating the test to another individual (today or in the future), who would not be tested otherwise.<\/p>\n

Understanding all the relevant costs and benefits is important for the government to understand the groups of people for whom testing should be a priority. The criteria for making testing a priority for a particular group should be based on the benefits and the costs of testing an additional individual in that group. We briefly explain what determines those costs and benefits.<\/p>\n

Who should be tested? Why group prevalence matters<\/h3>\n

Prevalence in a group is the chance that an individual from that group is infected. Prevalence is determined by the demographics of the individual (such as their age, sex and ethnicity), their symptoms, their medical records or information from track-and-tracing technologies.<\/p>\n

Prevalence is the key input to determine the benefit of testing an individual. Suppose Alice has all the symptoms of Covid-19: she is coughing, has a high temperature and blurred vision. The prevalence in Alice\u2019s group of people with similar symptoms and demographics is very high. By testing Alice, the policy-maker is likely to learn very little information because the test will, most likely, confirm the initial information.<\/p>\n

Since the policy-maker learns very little from the test, their action towards Alice (that is, quarantine) would be the same with or without the test. In other words, the test is wasted. The same logic applies if Alice is very likely to not be infected with Covid-19 (for example, because she has been isolating for several weeks).<\/p>\n

Finally, suppose that the policy-maker estimates that Alice has a 50% chance of having Covid-19. Then, testing her is very valuable: the policy-maker will learn a lot by finding out whether she is ill or not, and this information will guide the choice of the policy-maker (see Figure 2).<\/p>\n

Figure 2: Benefits of testing are highest for moderate prevalence levels<\/h4>\n

\"Simplified<\/p>\n

Lesson:<\/strong> Testing should be targeted at groups with a moderate level of Covid-19 prevalence.<\/p>\n

Who should be tested? Costs of errors<\/h3>\n

The allocation of tests depends on the objectives of the policy-maker. A government might care about social costs of the disease: that is, the total health cost, the cost of lost economic output, the cost of children being out of school and so on. A business, on the other hand, might care about its profitability, its employees and its customers. The objectives of governments and individual businesses may diverge in test allocation.<\/p>\n

To stop a new wave of Covid-19, governments need to find and isolate infected people. To re-open the economy and society, governments need to relax social distancing measures with the risk that infected people (maybe asymptomatic) restart the contagion.<\/p>\n

In other words, governments need to balance quarantining <\/em>an individual and releasing <\/em>an individual. If the policy-maker does not test an individual (or if the test is imperfect), they can incur two types of costs. One cost is the cost of false quarantine<\/em>, that is the cost of isolating individuals who are not, in fact, infected. The other cost is the cost of false release<\/em> of individuals who are, in fact, infected.<\/p>\n

The costs of false quarantine and false release differ a lot in the population. For example, they depend on the economic sector in which the individual is employed. For some sectors, social distancing is not feasible, so false release is very costly: infected people in those industries can contribute disproportionately to the likelihood of spread, for example, the entertainment and sports industries. Testing is valuable in such sectors unless the prevalence is already very high.<\/p>\n

On the other hand, in industries where working from home is a good substitute for traditional office-working, the cost of false quarantine is not particularly high. Testing these workers is less valuable. Of course, for some workers, such as those on the NHS frontline, the costs of both false quarantine and false release are very high, and testing is very valuable indeed (see Figure 3).<\/p>\n

Lesson:<\/strong> Tests should be targeted at individuals for whom a false quarantine or a false release is costly. If false release costs are low, do not test the individual if the prevalence is low (release them instead). If false quarantine costs are low, do not test the individual if the prevalence is high (quarantine them instead).<\/p>\n

Figure 3: Costs and benefits of testing<\/h4>\n

\"Simplified<\/p>\n

What tests are available?<\/h3>\n

There are two main types of Covid-19 tests: serological; and polymerase chain reaction (PCR). Serological tests detect antibodies and therefore they are useful to determine how many people have already had Covid-19. PCR tests (swabs) detect the presence of Covid-19, and therefore they are useful in estimating the current infection rate in the population.<\/p>\n

Serological tests help to estimate the prevalence in a group. Many governments, including in the UK, are now running serological testing programmes for representative samples of the population. The outcome of those programmes allows policy-makers to estimate the prevalence across different groups.<\/p>\n

PCR tests give the policy-maker actionable advice about whether they should quarantine or release an individual. Therefore, PCR testing should be based on the prevalence in a group. The policy-maker can estimate prevalence based on all the serological and PCR tests conducted in the group.<\/p>\n

As a result, PCR tests and serological tests are substitutes for learning about Covid-19 prevalence. But if the policy-maker believes that PCR testing is likely to be necessary in a particular group (because it has high costs of false quarantine and false release), then serological testing and PCR testing can be complementary for that group.<\/p>\n

Lesson:<\/strong> Serological tests should be used to learn the prevalence of different groups that the policy-maker wishes to monitor for the possibility of further Covid-19 outbreaks. The policy-maker can then use the more accurate prevalence information to target PCR tests to these groups more effectively.<\/p>\n

How should people be tested when testing is imperfect?<\/h3>\n

Even if tests are often imprecise, they are still very useful. The specificity and sensitivity of a test summarise the precision of a given test (Ely et al<\/a>, 2020):<\/p>\n