Abstract
AbstractWe develop a Bayesian method for estimating the dynamics of COVID‐19 deaths and discover four key findings that expose the limitations of current structural epidemiological models . (i) Death growth rates declined rapidly from high levels during the initial 30 days of the epidemic worldwide. (ii) After this initial period, these rates fluctuated substantially around 0%. (iii) The cross‐location standard deviation of death growth rates decreased rapidly in the first 10 days but remained high afterward. (iv) These insights apply to both effective reproduction numbers and their cross‐location variability through epidemiological models. Our method is applicable to studying other epidemics.
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