Before revision:  We apply this method to analyse the evolution of COVID-19 cases and deaths, partitioning data points into an appropriate number of clusters on each day to track both the  total number of clusters and their changing constituency over time .
After revision:  We apply this method to analyse the evolution of COVID-19 cases and deaths, partitioning data points into an appropriate number of clusters on each day to track both the total number of clusters and individual countries' cluster memberships are algorithmically determined. We study the change in both quantities over time, demonstrating a close similarity in the evolution of cases and deaths. The changing number of clusters of the case counts precedes that of the death counts by 32 days. On the other hand, there is an optimal offset of 16 days with respect to the greatest consistency between cluster groupings, determined by a new method of comparing affinity matrices .