The Economic Cost of Quarantine

As efforts to contain the COVID-19 epidemic continue, it is important to give consideration to the implications of the response for the economy and life expectancy.

Countries with higher per capita incomes have longer life expectancies, due to their ability and willingness to invest in healthcare, infrastructure, and environmental governance. A 100% increase in per capita income equates to an increase in life expectancy of 1-3 years. A 50% decrease in GDP would therefore see a 1.5 year decrease in life expectancy, meaning for each 1% reduction in GDP, life expectancy will decrease by approximately 10 days.

In economics, “value of life” refers to the amount that a society is willing to spend in order to increase average life expectancy. Whether in terms of work, business, or social management, a balance must be struck between reducing the risk of fatality and the cost of doing so.

Some jobs inherently entail higher than others, such as mining and construction. Instead of eliminating these jobs and letting society bear the cost of underdevelopment, a more rational approach would see the introduction of stronger labor protections for dangerous jobs, rewarded with higher salaries.

In designing a new road, governments can reduce the number of fatalities through the implementation of safety provisions, but if the cost is excessive, it is likely that the road will not be built, resulting in a lack of transportation infrastructure. Thus, a balance must be found between risk and cost.

Generally speaking, the value of life in developed nations is between 10-100 times the GDP per capita. Assuming that the value of life is calculated at 30 times the GDP per capita, the average life expectancy would be around 80 years, or approximately 30,000 days.

In the absence of large-scale compulsory quarantine measures, the infection rate for previous outbreaks of influenza does not exceed 10% of the population, and the fatality rate will be around 0.2%. Thus, the total number of fatalities relative to the entire population will be 2 in 10,000 (0.02%). Assuming that the life expectancy of those who die of influenza is around 60 years, and the average life expectancy is 80 years, each person who has died of influenza will have died prematurely by 20 years. On the basis of the fatality rate of 0.02%, the per capita reduction in life expectancy will be 20 multiplied by 0.02, or about 1.5 days.

If every person infected with influenza (10% of the population) and family members who have been in close contact with them (assuming 20% of the population) are quarantined for 14 days, the loss to GDP will be 30% * 14/365 = 1% of GDP. As mentioned above, a 1% GDP regression will cause a retrogression across society in medical care, infrastructure and environmental governance, amounting to a reduction in the average life expectancy of about 10 days.

A less optimistic estimation of the losses incurred could be 10% of GDP, leading to a reduction of the average life expectancy by 100 days, possibly amounting to a loss of life hundreds of times the impact of influenza itself.

As society strives to beat this epidemic “at all costs”, the above analysis can help society to keep various “costs” to a minimum. In responding to diseases that threaten lives, we must also give consideration to social and medical resources, and strike a balance that is conducive to protecting lives. Regularity and security in everyday life and work is an important and fundamental part of life for every person, and we should strive to minimize the impact to this.

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