Introducing our regular COVID-19 Data Analysis Update
The growing number of people infected with the SARS-CoV-2 virus and the enormous scale of the pandemic pose immense challenges for society and science worldwide. As an international mathematical research institute, we wish to contribute to the discussion by providing a statistical analysis of the growth rates underlying this pandemic.
This regularly updated report is a cautionary analysis of statistical trends from reported case numbers. Instead of simply extrapolating current growth trends, we seek to identify general trends in the dynamics of the growth rate, in order to estimate when countries may hopefully make a transition from alarming growth to a saturated phase. This can support researchers and policy makers in judging the effectiveness of various social distancing measures undertaken in different countries.
The data evaluation is performed by
Hoang Duc Luu and
Jürgen Jost from our
dynamical systems group.
Based on the respective growth rates according to the number of infected we differentiate between various periods of pandemic development. We believe that we can establish general statistical regularities in the dynamics of the growth rate, which are captured by a simple linear regression. A linear extrapolation of this regression allows us to make a robust prediction on the final number of infected cases, once the growth rate has stabilized at a low enough level (r<0.1). The results of this evaluation of growth rate trends for countries with more than 1000 confirmed COVID-19 cases are represented in the forecast table.