Lies, damned lies, and statistics: The uncertainty over COVID-19 numbers in India

This paper intends to ascertain the veracity of reported data on deaths and testing pertaining to the novel coronavirus in India. We use a widely used forensic audit technique called Benford's law to analyze the data, and our findings suggest anomalies in the reported numbers and the reported data for most of the states do not adhere to the Benford distribution. The implications of these findings are manifold, especially on the trajectory of policy-making, vaccination strategy, and preparedness for future waves and new variants. We strongly argue for the need for a robust data collection and reporting mechanism, creating a central data repository, and instituting a data-driven policy framework as key steps in the process management bulwark for managing such future pandemics and other events concerning public health.