Covid-19 and the Cost-Benefit Analysis

The novel coronavirus "Covid-19," first found in December 2019 in the Chinese city of Wuhan, has as of the morning of March 18, 2020 spread to 157 countries/regions with 207,615 confirmed cases and 8,249 deaths.  The corresponding numbers for the U.S. are 7,324 confirmed cases and 115 deaths, respectively.1 March 11 the World Health Organization (WHO) finally declared what had been obvious for many public health experts for weeks: Covid-19 is a global pandemic.

During the past week, as the number of confirmed cases have grown exponentially, the U.S. has considerably beefed up its response. At the federal level, the White House imposed travel restrictions on flights to the U.S. from 28 European countries (the so-called Schengen area, plus the U.K. and Ireland).  This is in addition to the earlier travel restrictions on China. President Trump also declared the outbreak a national emergency to mobilize federal resources. Various federal aid packages were rushed through Congress, which will make testing of Covid-19 free and provide relief for hourly-wage workers and small and medium-sized businesses for lost work hours from the sick and family leaves due to the outbreak.

In many aspects, Covid-19 is like the flu: it is an acute respiratory viral infection that is very contagious; patients with a mild infection can often recover on their own without any treatment, but patients with a severe infection may develop complications, including pneumonia that may lead to death.  Older people and those with underlying health conditions are especially vulnerable.

However, despite these surface similarities, the Covid-19 outbreak is not like the flu.  We have partial immunity to the flu from repeated exposures, and we often are vaccinated against certain strains of the flu.  In contrast, Covid-19 is a new virus to which no one has built up an immunity, and against which there are no vaccines.  Indeed, Dr. Anthony Fauci of the CDC suggests that a vaccine is at least a year away.  Thus Covid-19 is both more contagious and more deadly than the flu.  As the experiences of Wuhan and Milan demonstrate, a Covid-19 outbreak tends to cause a surge in cases of severe infection in a very short period of time, a surge which threatens to overrun the resources available in intensive care facilities (including ventilators).  Italy is a prime example, with patients needing ventilators being subject to triage.  Such incidents increase the death rate of Covid-19 and also threaten patients needing intensive care for other emergencies as well.  It is in order to “flatten the curve,” to slow the rate of infection and to spread this surge over time, that certain containment measures are recommended and invoked. 

What is the optimal level of containment effort for Covid-19?  Cost-benefit analysis can shed some light on this question.  Cost-benefit analysis, as the name implies, compares the costs and benefits of a proposed action.  It is widely used in the evaluation of government projects and regulations.  For instance, the Department of Transportation and the Environmental Protection Agency use cost-benefit analysis when deciding on fuel economy standards.  In this situation,the costs are typically the cost of modifying the car design to achieve a particular miles-per-gallon standard.  The benefits are the reduction in fuel costs and the value of the reduction in greenhouse gas emissions. After calculating these costs and benefits for a range of different miles-per-gallon standards, the ‘optimal’ standard can be identified as the miles-per-gallon standard where the benefits exceed the costs by the largest amount.

Appropriately applied, cost-benefit analysis can be very useful in evaluating decisions related to public health interventions and the appropriate actions to take to mitigate the spread of the Covid-19. However, our lack of accurate knowledge of various aspects of the virus and its impact on health and the economy renders a cost-benefit analysis inaccurate as well.  Further, policymakers are being forced by circumstances to make decisions in real time, at a speed that precludes a thorough cost-benefit analysis and precludes waiting for more certainty. Nevertheless, the cost-benefit framework is useful to help understand some general implications of the cost-benefit analysis for Covid-19 containment effort.

For cost-benefit analysis of actions that impact human lives, such as Covid-19 containment, it is necessary to establish the value of the benefit, which is in large part the value of saving lives.  In this regard analysts use the concept of ‘the value of a statistical life’ or VSL.  The VSL is a society’s collective willingness to pay for saving a statistical life.  This is the value of saving the life of an unknown or unidentified randomly chosen person, hence the phrase ‘statistical life’.  Economists have estimated the VSL for various countries based on consumers’ purchase decisions on life-saving safety devices (e.g., optional side airbags) or on workers’ occupational choices among jobs with different mortality risks and corresponding compensating wages. In both cases, VSL is estimated by the additional dollars someone is demonstrably willing to pay to reduce risk, or the additional wages someone forgoes in order to reduce risk.  The VSL numbers used by U.S. federal agencies range from $7.9 million to $9.2 million per life.2

Putting a dollar value on a human life, even a statistical life, seems callous, but the VSL is used to reflect the idea that buying safety has a cost, and that there exists a tradeoff between safety and cost.  Given that all human action is subject at some level to budget constraints, taking an action that is expected to save one statistical life at a cost greater than the VSL should be avoided if an alternative action can save one statistical life at a cost that is less than the VSL.

Containing Covid-19, like pretty much everything else, involves both benefits and costs.  The optimal level of containment efforts is determined by balancing the benefits against the costs.

The existence of a tradeoff between benefits and costs implies that a “spare no expense” approach to Covid-19 containment is very unlikely to be optimal.  While it is impossible to implement a literal “spare no expense” approach, China’s containment strategy in Wuhan was quite stringent and perhaps the closest we can imagine coming to this extreme. In Wuhan, and in many other Chinese cities, people were confined to homes except for grocery and medicine shopping once every couple of days; private motor vehicles were not allowed on roads; many hospitals were converted to specialized Covid-19 ICU facilities.  This caused such consequences as children being left home unattended because their parents were hospitalized; older people with mobility issues were left on their own because their caretakers could not reach them; patients needing periodic kidney dialysis or other forms of life support were effectively left to die. Such extreme stories of human tragedies – including starvation and suicides – abounded on the internet, economic activities came to a standstill, and civil liberties were almost non-existent.

In terms of the economic costs alone, China’s approach was shockingly expensive. According to Bloomberg, “[China’s] Industrial output plunged 13.5% in January and February from a year earlier, retail sales fell 20.5%, and fixed-asset investment dropped 24.5%.3  The long term consequences, and the speed with which China can return to some semblance of normality in the economy, are as yet unknown.  If the return to normality is fairly quick, if China can maintain its low rate of infection that followed its draconian policies, then its approach will likely be regarded as a success, with the benefit in terms of saved lives well worth the cost to the economy.  The passage of time will provide a more information to allow a more accurate assessment of the costs, the benefits, and the wisdom of China’s approach, and will provide for judgement informed by the clearer lens of history.
1 Johns Hopkins University’s CSSE has updated information about Coronavirus Covid-19 Global Cases.
2 Three often-cited VSL numbers in the U.S. are $7.9 million (the Food and Drug Administration, 2010), $9.1 million (the Environmental Protection Agency, 2010), and $9.2 million (the Department of Transportation, 2014).

Posted: March 19, 2020 by Dennis Jansen, Liqun Liu