Published 24 July 2020
Current evidence shows that prevalence of certain comorbidities in a given population could make it more vulnerable to serious outcomes of COVID-19, including fatality. A new mixture of polynomial time series (MoPTS) model was developed to simultaneously identify (a) clusters of U.S. cities in terms of their COVID-19 death rates, and (b) the different associations of those rates with some key comorbidities among the populations represented in the clusters. The study, A Mixture of Regressions Model of COVID-19 Death Rates and Population Comorbidities (PDF), was conducted by Saumyadipta Pyne and collaborators (M. Maleki, R. Gurewitsch, M. Aruru, and G.J. McLachlan, University of Queensland).