Scott Tibbs

Please have charity in analyzing COVID-19 predictions

By Scott Tibbs, May 11, 2020

Things have been rapidly changing over the last three months regarding the novel coronavirus, and we have to have some charity and not assume the worst regarding the predictions and the models.

I heard a commentary recently that predictions that COVID-19 would overwhelm the hospital system and would not overwhelm the hospital system could not both be true, and connected that to a wider point about the idea that objective truth does not exist. That is unfair. Some models are just bad, but that does not mean that anyone is rejecting the idea of objective truth.

Because, actually… both can be true. We have a large country, with different populations, infrastructure and public policy in different areas. One city might not be at risk of seeing hospitals overwhelmed because of population density and public policy, while another might be at a higher risk. Even the same city could be at risk with looser restrictions while aggressive social distancing would make the risk less.

Obviously, there are empirical facts about the virus. The lethality of the virus among different age groups and different risk factors is a set of empirical facts. (Recognizing that there are obviously statistical outliers.) The effectiveness of treatments is another set of empirical facts. Other things are also empirical facts.

However, certain contradictory predictions, such as the impact of the virus on the hospital system, can both be true at the same time depending on a large number of factors. Predictions are always changing based on facts on the ground changing, and a prediction that is accurate for one city or state might not be accurate for another city or state. We need to be careful in how we approach these things and not unfairly judge the competence and especially the character of those making the predictions.

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