Exaggerating COVID deaths: Calif. vs. Florida
In an Aug. 25 article in Yahoo news writer Andrew Romano states that Florida’s surging COVID-19 death rate, six times the rate in California, is due to either “bad luck” or to Gov. DeSantis’ disdain of masks. The author concludes, “Nearly every one of their deaths was preventable.”
The math, suppositions and conclusions in this article are endemic of the communication failures that have plagued COVID-19, transforming a pandemic into a political battleground bereft of science. Let’s look at four important areas where the author’s preconceptions drive his conclusions.
Florida has six times the death rate as California: When you use numbers like “six times the rate,” it exaggerates the difference. The absolute death rates are very low in Florida and California, a critically relevant and important fact. Imagine a football stadium with 88,000 seats, such as the one at the University of Florida. In Florida, COVID’s daily death rate is one seat in that stadium. In California, the death rate is a fifth of a seat, or an armchair. Yes, technically, California has fewer deaths, but both states have low death rates overall, a conclusion which should not be passed over.
It must be the masks: The author states that masks account for the difference in death. He cites studies in which communities told to wear masks have fewer deaths than communities that don’t. But that is observational data; it shows a correlation between masks and deaths, but not cause and effect. For instance, it could be shown that communities with more Prius drivers have lower COVID-19 deaths, but that does not imply that driving a Prius lowers your risk of COVID death. It’s a correlation. Acknowledging these facts is essential for objective conclusions.
As an example, let’s look at the same stadium in another situation. In Florida, 15 seats are occupied by people who die in auto accidents annually, while Californians who die in cars occupy only 10 seats. We can’t then assume that the Pacific Ocean protects Californians from car deaths, or that Floridians’ penchant for white cars cause more people to die there. That’s correlation; it doesn’t prove cause and effect.
We have no way of knowing if masks reduce deaths until we do a randomized controlled trial: Have 1,000 people wear masks and 1,000 not wear masks and see what happens. That trial was done in Denmark and found no benefit to masks. And while some Americans dispute its methodology, they have yet to run one on their own, and until they do, the most we can say about masks is that we don’t know. Thus, we certainly can’t ascribe the difference in COVID-19 deaths to mask mandates.
If not masks, then it’s bad luck? Not true. We do know of one factor that tremendously impacts COVID-19 deaths: demographics. If everyone in a 1,000-seat theater of long-term care residents gets COVID, 85 will die of it. It would take two 1,000seat theaters of community residents for one to die. In a 1,000-seat theater of people over 70, 54 die of COVID, while in the same theater of people under 50, 20 will die. Thus, older, more frail people are more likely to die.
And Florida has far more elderly people. In Florida, 21% of the population is over 65, compared to 16% in California. In Florida, 3.2 people out of 1,000 live in long-term care, compared to 2.5 in California. Given these demographic differences, and the impact of age and frailty on COVID-19 death, we don’t’ have to evoke masks or luck in showing the mortality differences. In fact, if demographics are factored in, Florida may be doing better than California.
Is there a downside of masks and quarantines? The author does not discuss the negative ramifications of masking or prolonged quarantines. Who’s to know if California has more non-COVID deaths than Florida due to its more draconian shutdown and mandates? This is crucial to determine the success or failure of any interventions. How can we know how effective both strategies are unless we understand the harm that the strategies incur? The author should certainly acknowledge this reality.
In summary, we must use accurate and transparent data that looks at all variables, that doesn’t rely on observational data, and that measures both the benefit and success of what we do. If we don’t know whether something works, then we should acknowledge that and conduct a randomized controlled trial. But by mangling data to what appears to be a political point, we are not using science to work together as a nation to solve the COVID-19 pandemic in a way that saves as many lives as possible while harming the fewest people possible.