Strong impact of closing schools, closing bars and wearing masks during the COVID-19 pandemic: results from a simple and revealing analysis

Many complex mathematical and epidemiological methods have been used to model the Covid-19 pandemic. We took a different approach. Making no assumptions, we simply plotted cases, hospitalizations and deaths, on a log 2 Y axis and a linear date-based X axis, and analyzed them using segmented regression. The data fit straight lines with correlation coefficients ranging from 92% - 99%, and these lines broke at interesting intervals, revealing that school closings dropped infection rates in half, lockdowns dropped the rates 3 to 4 fold, and other actions (such as closing bars and mandating masks) brought the rates even further down. Hospitalizations and deaths lagged, but paralleled cases. The graphs, which are easy to read, have several implications for modeling and policy development during this and future pandemics. Overall three interventions had the most impact: closing schools, closing bars and wearing masks: a message easily understood by the public. One Sentence Summary Regression analysis showed that closing schools, closing bars, and wearing masks had major effects on infections, hospitalizations and death rates in the US during the Covid-19 pandemic.