By now I’m sure you know that the phrase of the week is “social distancing”—the act of maintaining distance from others in order to slow spread of disease. Social distancing can mean anything from cancelling of public events to workplace interventions to self-quarantine measures, all with the goal of reducing contact between people to reduce the number of new infections.
Social distancing measures have benefits. The benefit getting the most attention recently is the reduction of strain on the health care system. An epidemic can put strain on capacity of hospitals and clinics, making it harder for the system to prioritize harsher cases and potentially increasing the fatality rate of a disease. The goal of social distancing on this front is to “flatten the curve” of disease outbreak by slowing the spread of disease and spreading new cases out over a longer period of time so the health care system can better manage new cases.
Social distancing can also strategically protect more vulnerable populations and can potentially buy more time for development of treatments and prevention methods.
At the same time, social distancing has costs. Cancelled events means lost experience for attendees and revenues for hosts. Closed workplaces can mean less work for employees and less value for employers. Closed schools and conferences mean reduction in human capital development and exchange of ideas.
In a way, social distancing is different from a lot of interventions analysts study because the benefits are easier to measure than the costs: less people die when social distancing is implemented. That being said, every good analyst needs to ask the question of how much life is preserved through measures as opposed to how much life experience is destroyed through social distancing. After all, social interaction is a cornerstone of much of the theoretical and empirical evidence we have around well-being.
One way to estimate the tradeoffs individuals face when deciding whether to engage in social distancing is to see how individuals mitigate risks to life in other areas. In formal cost-benefit analysis, this is referred to as the “value of a statistical life”, or how willing people are to trade off fatality risks for monetary compensation. The current best practice for determining what people are willing to trade for fatality risk is by comparing compensation of more- and less-risky jobs and how willing people are to take on higher wages for accompanying higher fatality risk in the workplace. Using this technique, the current estimate of how much people value their lives in the workplace is $11 million.
Using this number, we can conduct some conservative individual-level cost-benefit analysis to estimate how people trade off coronavirus infection risk with the costs of social distancing techniques. For instance, if the median household income in Ohio is roughly $55,000, this means two weeks off work unpaid costs the average family about $2,100. Under the most conservative of scenarios using the low fatality rate in South Korea of 0.8%, that means an averted case of coronavirus would be worth about $92,000 to the average household using the standard value of a statistical life. This includes only fatality risk and not other medical costs that are more common with coronavirus, so this should be considered a low-end estimate of the cost to a household associated with coronavirus infection. With fatality rates ranging from 0.8% in South Korea to 6.6% in Italy, the fatality risk reduction value of avoiding a coronavirus infection at the household level could be as high as over $700,000.
Fatality rates as of 6:00am Thursday morning.
Under the conservative relatively low-risk 0.8% fatality rate scenario, if a family thinks taking two weeks off of work unpaid would allow a family member to avoid a 2.3% chance of contracting coronavirus, it makes economic sense for the household to do so on avoidance of fatality risk alone. With as much as one percent of the Ohio population assumed to be infected and coronavirus’s high infection rate, this does not seem to be a ridiculous assumption to make. In the opposite extreme case of an Italian-level 6.6% fatality rate, even avoiding a 0.3% chance of infection is worth the cost of two weeks’ wages.
It also should be noted that a two-week unpaid quarantine is an extreme measure. There may be lower-cost interventions for families such as telecommuting, avoiding mass gathering, and simple sanitary activities that could yield huge savings for households in reduced fatality and medical risks.
That being said, this analysis applies to the average household. Lower-income households might have less ability to mitigate risks and less flexibility in the workplace. Nonetheless, actors like state and local departments of health and broader state and local government want to encourage social distancing in these populations as well. This is where interventions like sick leave funds and even cash transfers could encourage workers to stay home and mitigate the spread of this disease.
Ultimately, social distancing will pay off for households, but public sector actors have tools to create stronger encouragement by reducing the cost of social distancing. Paying attention to both sides of the ledger for households will make interventions to promote social distancing more effective than they would be otherwise.