Author: Chakraborty, A.; Chen, J.; Desvars-Larrive, A.; Klimek, P.; Flores Tames, E.; Garcia, D.; Horstmeyer, L.; Kaleta, M.; Lasser, J.; Reddish, J.; Pinior, B.; Wachs, J.; Turchin, P.
Title: Analyzing Covid-19 Data using SIRD Models Cord-id: 8dg8neq5 Document date: 2020_5_30
ID: 8dg8neq5
Snippet: 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 t
Document: 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.
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