A new modelling of the COVID 19 pandemic
| Autor: | Anton Kovalev, Vladislav Soukhovolsky, Boris Kessel, Anne Pitt |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Distributed lag
Coronavirus disease 2019 (COVID-19) Process (engineering) Computer science mathematics model General Mathematics Physical system General Physics and Astronomy 01 natural sciences Article epidemics 010305 fluids & plasmas modelling 0103 physical sciences Health care Pandemic Econometrics 010301 acoustics business.industry Applied Mathematics COVID-19 Statistical and Nonlinear Physics Exponential function Autoregressive model infection disease business |
| Zdroj: | Chaos, Solitons & Fractals Chaos, Solitons, and Fractals |
| ISSN: | 0960-0779 |
| DOI: | 10.1016/j.chaos.2020.110039 |
| Popis: | А model of coronavirus incidence is proposed. Process of disease development is represented as analogue of first- and second order phase transition in physical systems. The model is very simple in terms of the data necessary for the calculations. To verify the proposed model, only data on the current incidence rate are required. However, the determination coefficient of model R2 is very high and exceeds 0.95 for most countries. The model permits the accurate prediction of the pandemics dynamics at intervals of up to 10 days. The ADL(autoregressive distributed lag)-model was introduced in addition to the phase transition model to describe the development of the disease at the exponential phase.The ADL-model allows describing nonmonotonic changes in relative infection over the time, and providing to governments and health care decision makers the possibility to predict the outcomes of their decisions on public health. |
| Databáze: | OpenAIRE |
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