Gleaning the best of out of bad data - Predictions for the epidemiological control of COVID-19

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02.04.2020 12:38

Gleaning the best of out of bad data - Predictions for the epidemiological control of COVID-19

Jana Gregor Presse- und Öffentlichkeitsarbeit
Max-Planck-Institut für Mathematik in den Naturwissenschaften (MPIMIS)

    Scientists from the Max Planck Institute for Mathematics in the Sciences in Leipzig provide a regularly updated statistical analysis of the growth trends of the corona pandemic. Through a better understanding of its spread, they aim to support decision-making with regard to existing and future measures.

    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. The goal of the mathematicians from Leipzig is to statistically analyze the huge and very inhomogeneous amount of data resulting from the published case numbers and to determine the growth rates and trends underlying this epidemic.

    The quality and consistency of the data daily published worldwide is essential to provide reliable forecasts of the spread of the virus. However, the data sets of the different countries are largely difficult to compare, partly internally inconsistent and in some cases likely manipulated. Prof. Jürgen Jost, director of the Max Planck Institute and head of the dynamical systems group, and his colleague Dr. Hoang Duc Luu used simplifying assumptions to developed a robust mathematical method that uses general statistical regularities to compensate for these data fluctuations.

    Instead of simply extrapolating current growth rates, the scientists seek to identify general trends in the dynamics of growth rates. They hope to better estimate when different countries may transition from alarming growth to a saturated phase. “We distinguish different periods of pandemic development based on the respective growth rates according to the number of infected. We believe that we can establish general statistical regularities in the dynamics of the growth rate, which are captured by a simple linear regression.” the scientists explain. In the beginning, the growth rate is typically extremely high but then weakens. In the final saturation phase, the growth rate reaches a regime where the development of the epidemic is essentially under control. In countries in which the growth rate is still very high, as is currently the case in Germany, it must be expected that a saturation phase will only occur after much higher case numbers. The goal is to determine in which time frame this will be the case and how high the total number of infected will be by then. The goal of the scientists is to determine the time frame when this saturation phase will be reached and to estimate the total number of infections by then.

    For data material and images as well as further information, please contact:

    Wissenschaftliche Ansprechpartner:

    Prof. Dr. Jürgen Jost
    Dr. Hoang Duc Luu

    Weitere Informationen: - COVID-19 Data Analysis Update / Institute’s Blog

    Merkmale dieser Pressemitteilung:
    Journalisten, Wirtschaftsvertreter, Wissenschaftler
    Gesellschaft, Mathematik, Medizin, Politik
    Forschungs- / Wissenstransfer

    COVID-19 Data Anlysis Update

    Zum Download


    Logarithmic growth trend using the example of the USA, based on the data on infected cases from March 30th

    Zum Download



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