Covid-19 Predictions Using a Gauss Model, Based on Data from April 2
| Autor: | Martin Kröger, Reinhard Schlickeiser, Frank Schlickeiser, Janik Schüttler |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Coronavirus disease 2019 (COVID-19)
Logarithm forecast statistical methods in physics extrapolation Extrapolation virus 01 natural sciences 03 medical and health sciences symbols.namesake 0302 clinical medicine 0103 physical sciences Statistics Gaussian function Quantitative Biology::Populations and Evolution time evolution pandemic spreading 030212 general & internal medicine 010306 general physics health science Mathematics Statistical methods in physics Health science Parameter estimation Pandemic spreading Virus Forecast Time evolution Dynamics Estimation theory Gauss other dynamics Sigmoid function Quadratic function lcsh:QC1-999 Exponential function Predictive power symbols parameter estimation lcsh:Physics |
| Zdroj: | Physics, Vol 2, Iss 13, Pp 197-212 (2020) Physics Volume 2 Issue 2 Pages 13-212 Physics, 2 (2) |
| ISSN: | 2624-8174 |
| DOI: | 10.20944/preprints202004.0175.v1 |
| Popis: | We study a Gauss model (GM), a map from time to the bell-shaped Gaussian function to model the deaths per day and country, as a simple, analytically tractable model to make predictions on the coronavirus epidemic. Justified by the sigmoidal nature of a pandemic, i.e., initial exponential spread to eventual saturation, and an agent-based model, we apply the GM to existing data, as of 2 April 2020, from 25 countries during first corona pandemic wave and study the model’s predictions. We find that logarithmic daily fatalities caused by the coronavirus disease 2019 (Covid-19) are well described by a quadratic function in time. By fitting the data to second order polynomials from a statistical χ2 -fit with 95% confidence, we are able to obtain the characteristic parameters of the GM, i.e., a width, peak height, and time of peak, for each country separately, with which we extrapolate to future times to make predictions. We provide evidence that this supposedly oversimplifying model might still have predictive power and use it to forecast the further course of the fatalities caused by Covid-19 per country, including peak number of deaths per day, date of peak, and duration within most deaths occur. While our main goal is to present the general idea of the simple modeling process using GMs, we also describe possible estimates for the number of required respiratory machines and the duration left until the number of infected will be significantly reduced Physics, 2 (2) ISSN:2624-8174 |
| Databáze: | OpenAIRE |
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