Benford’s Law and COVID-19 Reporting

Trust in the reported data of contagious diseases in real-time is important for policy makers. Media and politicians have cast doubt on Chinese reported data on COVID-19 cases. We find Chinese confirmed infections match the distribution expected in Benford’s Law and are similar to that seen in the U.S. and Italy. We identify a more likely candidate for problems in the policy-making process: Poor multilateral data sharing on testing and sampling.

Contrary to popular speculation, we find no evidence that the Chinese massaged their COVID-19 statistics. We use a statistical fraud detection technique, Benford’s (1938) Law, to assess the veracity of the statistics. This empirical finding is important because China was affected first. Policies to combat the global pandemic are informed by its response. Skepticism about the Chinese data may result – and may indeed already have resulted – in poor policy choices.