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Piecewise quadratic growth during the 2019 novel coronavirus epidemic
Stockholm University, Nordic Institute for Theoretical Physics (Nordita).ORCID iD: 0000-0002-7304-021X
Number of Authors: 12020 (English)In: Infectious Disease Modelling, ISSN 2468-0427, Vol. 5, p. 681-690Article in journal (Refereed) Published
Abstract [en]

The temporal growth in the number of deaths in the COVID-19 epidemic is subexponential. Here we show that a piecewise quadratic law provides an excellent fit during the thirty days after the first three fatalities on January 20 and later since the end of March 2020. There is also a brief intermediate period of exponential growth. During the second quadratic growth phase, the characteristic time of the growth is about eight times shorter than in the beginning, which can be understood as the occurrence of separate hotspots. Quadratic behavior can be motivated by peripheral growth when further spreading occurs only on the outskirts of an infected region. We also study numerical solutions of a simple epidemic model, where the spatial extend of the system is taken into account. To model the delayed onset outside China together with the early one in China within a single model with minimal assumptions, we adopt an initial condition of several hotspots, of which one reaches saturation much earlier than the others. At each site, quadratic growth commences when the local number of infections has reached a certain saturation level. The total number of deaths does then indeed follow a piecewise quadratic behavior.

Place, publisher, year, edition, pages
2020. Vol. 5, p. 681-690
Keywords [en]
COVID-19, Coronavirus, Epidemic, SIR model, Reaction-diffusion equation
National Category
Public Health, Global Health and Social Medicine
Identifiers
URN: urn:nbn:se:su:diva-186286DOI: 10.1016/j.idm.2020.08.014ISI: 000572300900001PubMedID: 32954094OAI: oai:DiVA.org:su-186286DiVA, id: diva2:1484295
Available from: 2020-10-28 Created: 2020-10-28 Last updated: 2025-02-20Bibliographically approved

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Brandenburg, Axel

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