An SEIR Model with Time‐Varying Coefficients for Analyzing the SARS‐CoV‐2 Epidemic
Abstract In this study, we propose a time‐dependent susceptible‐exposed‐infected‐recovered (SEIR) model for the analysis of the SARS‐CoV‐2 epidemic outbreak in three different countries, the United States, Italy, and Iceland using public data inherent the numbers of the epidemic wave. Since several...
| Published in: | Risk Analysis |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2021
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1111/risa.13858 https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.13858 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/risa.13858 |
| Summary: | Abstract In this study, we propose a time‐dependent susceptible‐exposed‐infected‐recovered (SEIR) model for the analysis of the SARS‐CoV‐2 epidemic outbreak in three different countries, the United States, Italy, and Iceland using public data inherent the numbers of the epidemic wave. Since several types and grades of actions were adopted by the governments, including travel restrictions, social distancing, or limitation of movement, we want to investigate how these measures can affect the epidemic curve of the infectious population. The parameters of interest for the SEIR model were estimated employing a composite likelihood approach. Moreover, standard errors have been corrected for temporal dependence. The adoption of restrictive measures results in flatten epidemic curves, and the future evolution indicated a decrease in the number of cases. |
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