Most people think they have pretty good BS detectors, at least when it comes to advertising hyperbole, weasel words, and politicians’ promises. Quantitative claims are harder: Numbers have the sense of objectivity and precision, and people feel less confident in challenging them. This has been a huge problem during the past year 20 months. From epidemiological models to case rates and vaccine efficacy estimates, the COVID-19 outbreak has put quantitative information front and and center in all of our lives. Worse yet, the pandemic response has been aggressively politicized, giving ample incentive for many sorts of actors to spread misinformation and disinformation. Shortly before the pandemic broke out, I finished a book on how to spot and refute quantitative misinformation. Every lesson in the book has proven useful during the current pandemic. In this talk, I will present a tour of how misleading numbers, statistics, mathematics, and data graphics have muddied the social and traditional media streams that we all rely upon during COVID. I will give examples of deliberate disinformation, and examples of unintended misinformation around the pandemic. And I will explore how as scientists, citizens, and as educators we all can promote data reasoning and quantitative literacy around the pandemic and more broadly.