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Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States

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Bibliographic Details
Main Authors: Orhun O., Davarci, Emily Y., Yang, Alexander, Viguerie
Format: Book
Language:English
Published: Springer 2023
Subjects:
SEIRD
Online Access:https://link.springer.com/article/10.1007/s00366-023-01816-9
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8344
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spelling oai:localhost:PNK-83442023-04-27T01:50:03Z Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States Orhun O., Davarci Emily Y., Yang Alexander, Viguerie SEIRD CC BY The rapid spread of the numerous outbreaks of the coronavirus disease 2019 (COVID-19) pandemic has fueled interest in mathematical models designed to understand and predict infectious disease spread, with the ultimate goal of contributing to the decision making of public health authorities. Here, we propose a computational pipeline that dynamically parameterizes a modified SEIRD (susceptible-exposed-infected-recovered-deceased) model using standard daily series of COVID-19 cases and deaths, along with isolated estimates of population-level seroprevalence. 2023-04-27T01:50:03Z 2023-04-27T01:50:03Z 2023 Book https://link.springer.com/article/10.1007/s00366-023-01816-9 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8344 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic SEIRD
spellingShingle SEIRD
Orhun O., Davarci
Emily Y., Yang
Alexander, Viguerie
Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States
description CC BY
format Book
author Orhun O., Davarci
Emily Y., Yang
Alexander, Viguerie
author_facet Orhun O., Davarci
Emily Y., Yang
Alexander, Viguerie
author_sort Orhun O., Davarci
title Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States
title_short Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States
title_full Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States
title_fullStr Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States
title_full_unstemmed Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States
title_sort dynamic parameterization of a modified seird model to analyze and forecast the dynamics of covid-19 outbreaks in the united states
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s00366-023-01816-9
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8344
_version_ 1764358630173310976
score 8.891145

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