tetano
Editor, Senior Moderator
Jos? Enrique Amaro[SUP] 1 [/SUP], J?r?mie Dudouet[SUP] 2 [/SUP], Jos? Nicol?s Orce[SUP] 3 [/SUP]
Affiliations
Abstract
Several analytical models have been developed in this work to describe the evolution of fatalities arising from coronavirus COVID-19 worldwide. The Death or 'D' model is a simplified version of the well-known SIR (susceptible-infected-recovered) compartment model, which allows for the transmission-dynamics equations to be solved analytically by assuming no recovery during the pandemic. By fitting to available data, the D-model provides a precise way to characterize the exponential and normal phases of the pandemic evolution, and it can be extended to describe additional spatial-time effects such as the release of lockdown measures. More accurate calculations using the extended SIR or ESIR model, which includes recovery, and more sophisticated Monte Carlo grid simulations - also developed in this work - predict similar trends and suggest a common pandemic evolution with universal parameters. The evolution of the COVID-19 pandemic in several countries shows the typical behavior in concord with our model trends, characterized by a rapid increase of death cases followed by a slow decline, typically asymmetric with respect to the pandemic peak. The fact that the D and ESIR models predict similar results - without and with recovery, respectively - indicates that COVID-19 is a highly contagious virus, but that most people become asymptomatic (D model) and eventually recover (ESIR model).
Keywords: COVID-19 coronavirus; Death model; Monte Carlo Planck model; extended SIR model.
Affiliations
- PMID: 33110288
- PMCID: PMC7580557
- DOI: 10.1016/j.apm.2020.10.019
Abstract
Several analytical models have been developed in this work to describe the evolution of fatalities arising from coronavirus COVID-19 worldwide. The Death or 'D' model is a simplified version of the well-known SIR (susceptible-infected-recovered) compartment model, which allows for the transmission-dynamics equations to be solved analytically by assuming no recovery during the pandemic. By fitting to available data, the D-model provides a precise way to characterize the exponential and normal phases of the pandemic evolution, and it can be extended to describe additional spatial-time effects such as the release of lockdown measures. More accurate calculations using the extended SIR or ESIR model, which includes recovery, and more sophisticated Monte Carlo grid simulations - also developed in this work - predict similar trends and suggest a common pandemic evolution with universal parameters. The evolution of the COVID-19 pandemic in several countries shows the typical behavior in concord with our model trends, characterized by a rapid increase of death cases followed by a slow decline, typically asymmetric with respect to the pandemic peak. The fact that the D and ESIR models predict similar results - without and with recovery, respectively - indicates that COVID-19 is a highly contagious virus, but that most people become asymptomatic (D model) and eventually recover (ESIR model).
Keywords: COVID-19 coronavirus; Death model; Monte Carlo Planck model; extended SIR model.