# Why sacrificing Grandma by opening up again might not save the economy **URL:** \ **Category:** Great Debates\ **Created:** [April 3, 2020, 11:45pm UTC](https://boards.straightdope.com/t/why-sacrificing-grandma-by-opening-up-again-might-not-save-the-economy/851011 "2020-04-03T23:45:01Z")\ **Posts on this page:** 1\ **Showing post:** 3
**Author:** ![Sage\_Rat](https://sea3.discourse-cdn.com/straightdope/user_avatar/boards.straightdope.com/sage_rat/32/399_2.png) [@Sage\_Rat](https://boards.straightdope.com/u/Sage_Rat)\ **Post date:** [April 4, 2020, 12:57am UTC](https://boards.straightdope.com/t/why-sacrificing-grandma-by-opening-up-again-might-not-save-the-economy/851011/3 "2020-04-04T00:57:37Z")
Let’s assume the following: 1. The average person can generate about $2500 worth of value per month, if employed. 2. There is a linear scale of social distancing (e.g., cutting off airplanes, cutting off events, shelter-at-home, forced complete quarantine for all, etc.) which causes 5% unemployment if we do nothing (0) and 15% employment at the top end (10). 3. The fatality rate for people under 55 is 0.15% and 5% for those 55 and older. This is, assuming that hospitals are able to adequately care for them. 4. If hospitals have become overrun, then the fatality rate is tripled in direct correlation to the percentage of overrun hospitals. 5. 80% of the labor force is under the age of 55. 6. The percentage of hospitals which are overrun is linearly correlated to the scale of social distancing. At 0, 50% will be overrun. At 10, 0% will be overrun. 7. The duration of the epidemic is linearly correlated to the scale of social distancing. At 0, the epidemic will factor on employment rates for a 3 month period. At 10, it will be stretched over a 6 month period. 8. The percentage of infected is linearly correlated to the scale of social distancing. At 0, 60% of individuals will become infected. At 10, 30% will. 9. The average age of a worker is 42. The average retirement age of a worker is 62. Any deaths (for simplicity’s sake) will be viewed as a loss of 20 years worth of economic activity. While these numbers are somewhat ballpark, they are generally based on these cites: > **[South Korea: coronavirus mortality rate by age 2023 | Statista](https://www.statista.com/statistics/1105088/south-korea-coronavirus-mortality-rate-by-age/)** > > As of February 1, 2023, the fatality rate of novel coronavirus (COVID-19) in South Korea lay at around two percent among people aged 80 year and older. > **[Italy COVID - Coronavirus Statistics - Worldometer](https://www.worldometers.info/coronavirus/country/italy/)** > > Italy Coronavirus update with statistics and graphs: total and new cases, deaths per day, mortality and recovery rates, current active cases, recoveries, trends and timeline. > **[Older workers: Labor force trends and career options : Career Outlook: U.S....](https://www.bls.gov/careeroutlook/2017/article/older-workers.htm)** > > BLS data have a lot to say about older workers. What those data show may surprise you. **If we perform a social isolation level of 8 across the entire worker population, we expect a fatality rate (among workers) of:** workerCount = 150m workersInfected = (workerCount \* ((1.0 - 0.8) \* (0.6 - 0.3) + 0.3)) = 54m youngWorkerFatalitiesPreHospital = (workersInfected \* 0.8) \* 0.0015 = 64,800 olderWorkerFatalitiesPreHospital = (workersInfected \* 0.2) \* 0.05 = 540,000 youngWorkerFatalities = youngWorkerFatalitiesPreHospital \* ((1 - 0.8) \* 0.5 \* 2 + 1) = 77,760 olderWorkerFatalities = olderWorkerFatalitiesPreHospital \* ((1 - 0.8) \* 0.5 \* 2 + 1) = 648,000 totalFatalities = youngWorkerFatalities + olderWorkerFatalities = 725,760 And we expect an economic loss of: lossesToDeath = totalFatalities \* $2500 \* 12 \* 20 = $435.5b totalUnemployed = (0.8 \* (0.15 - 0.5) + 0.5) \* workerCount = 87m totalMonthsUnemployed = (0.8 \* (6 - 3) + 3) = 5.4 totalLossesToUnemployment = totalMonthsUnemployed \* totalUnemployed \* $2500 = $1.2t totalLoss = lossesToDeath + totalLossesToUnemployment = $1.6t **Versus a 2:** workerCount = 150m workersInfected = (workerCount \* ((1.0 - 0.2) \* (0.6 - 0.3) + 0.3)) = 81m youngWorkerFatalitiesPreHospital = (workersInfected \* 0.8) \* 0.0015 = 97,200 olderWorkerFatalitiesPreHospital = (workersInfected \* 0.2) \* 0.05 = 810,000 youngWorkerFatalities = youngWorkerFatalitiesPreHospital \* ((1 - 0.2) \* 0.5 \* 2 + 1) = 174,960 olderWorkerFatalities = olderWorkerFatalitiesPreHospital \* ((1 - 0.2) \* 0.5 \* 2 + 1) = 1,458,000 totalFatalities = youngWorkerFatalities + olderWorkerFatalities = 1,632,960 lossesToDeath = totalFatalities \* $2500 \* 12 \* 20 = $979.8b totalUnemployed = (0.2 \* (0.15 - 0.5) + 0.5) \* workerCount = 78m totalMonthsUnemployed = (0.2 \* (6 - 3) + 3) = 3.6 totalLossesToUnemployment = totalMonthsUnemployed \* totalUnemployed \* $2500 = $702b totalLoss = lossesToDeath + totalLossesToUnemployment = $1.7t Not a particularly rigorous analysis but the biggest difference seems to be life rather than economics. --- _[View the full topic](https://boards.straightdope.com/t/why-sacrificing-grandma-by-opening-up-again-might-not-save-the-economy/851011)._