Amid this pandemic, the most common numbers being thrown around are case numbers and deaths. Every morning I get up and look at theNew York Times US statistics on the spread of the COVID-19, and a few days ago I found myself wondering, “what do these numbers really mean?” Because of the vast heterogeneity in how tragic each death is, it’s tough to know.
In one extreme scenario, almost everyone who died was going to die anyways in, say, less than a year. This would be those with serious conditions and of advanced age (often both). Alternatively, there may be a surprising number of deaths where the expected number of years that the now deceased individuals would have lived is over 10 years, or perhaps over 20 or 30. I don’t think anyone would argue with the claim that deaths of the latter type are, in a sense, less tragic.
Thus, I propose a new measure to calculate the damage. Total number of expected life-years lost as a result of the virus. This could also be transformed into average number of expected life-years lost per death. To create this measure, ideally one would use individual-level data on demographics, family background, and medical history for each person who dies to predict how long this person would have lived in normal circumstances. The magnitude of the difference between age the person was when they died and the predicted age of death. This could then be summed up over all the people who died. Then median value, modal value, and average value of the measure could be calculated as well.
I am unaware of data that would make such a calculation doable, but if someone happens to see this who has such data, it would be great to see these numbers.