Get started
Work

Analyzing Covid-19 Data using SIRD Models

Year: 2020
Type: preprint
Abstract: Summary The goal of this analysis is to estimate the effects of the diverse government intervention measures implemented to mitigate the spread of the Covid-19 epidemic. We use a process model based on a compartmental epidemiological framework Susceptible-Infected-Recovered-Dead (SIRD). Analysis of case data with such a mechanism-based model has advantages over purely phenomenological approaches because the parameters of the SIRD model can be calibrated using prior knowledge. This approach can be used to investigate how governmental interventions have affected the Covid-19-related transmission and mortality rate during the epidemic.
Source: medRxiv
DOI: 10.1101/2020.05.28.20115527
Authors: Abhijit Chakraborty, Jiaying Chen, Amélie Desvars-Larrive, Peter Klimek, Erwin Flores Tames, David Garcia, Leonhard Horstmeyer, Michaela Kaleta, Jana Lasser, Jenny Reddish, Beate Pinior, Johannes Wachs, Peter Turchin
Institutions: International Institute for Applied Systems Analysis, Complexity Science Hub, Karolinska Institutet, Medical University of Vienna, University of Veterinary Medicine Vienna, Vienna University of Economics and Business, University of Connecticut
Language: English
Open Access status: green
OpenAlex ID: W3028969552
Cites: 23
Cited by: 12
Related to: 10