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COVID-19 threw the world into a situation where data were unreliable for several reasons: disorganization and delays in data collection, data that might not measure what they were intended to measure, widespread disagreement over the accuracy of critical measurements, multiple collectors of data, and government attempts to deceive their citizens. In these circumstances even honestly accumulated data sets may be unreliable. What is a scrupulous researcher to do? For COVID-19, it was imperative for public health that we build policy based on reliable data. Yet even as we conducted our research, we were acutely conscious of serious limitations in data reliability for many reasons. Further, as we show here, initial analysis of COVID’s impact produced results so complex and nuanced that they could easily–and deliberately–be misinterpreted by politicians, the public, and the media, all to the detriment of public …