Model studies on the COVID-19 pandemic in Sweden

Abstract

We study the increases of infections and deaths in Sweden caused by COVID-19 with several different models: Firstly an analytical susceptible-infected (SI) model and the standard susceptible-infected-recovered (SIR) model. Then within the SIR framework we study the susceptible-infected-deceased (SID) correlations. All models reproduce well the number of infected cases and give similar predictions. What causes us deep concern is the large number of deaths projected by the SI and SID models. Our analysis shows that, irrespective of the possible uncertainty of our model prediction, the next few days can be critical for determining the future evolution of the death cases (Updated April 02).

References in corpus (2)

• Epidemics, the Ising-model and percolation theory: a comprehensive review focussed on Covid-19
• The D model for deaths by COVID-19

Cited by in corpus (4)

• Social Interaction Layers in Complex Networks for the Dynamical Epidemic Modeling of COVID-19 in Brazil
• Reaction-diffusion spatial modeling of COVID-19: Greece and Andalusia as case examples
• A quantitative framework for exploring exit strategies from the COVID-19 lockdown
• Mathematical Modeling of the Spread of COVID-19 in Moscow and Russian Regions