SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics

Dengue fever is an acute mosquito-borne viral infection that results in a heavy social burden in many tropical and subtropical regions. Accurate forecasts of dengue outbreak allow the local health officials to take proactive action such as positioning mosquito control equipment or preparing medical...

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Autores principales:	Chunlin Yi, Lee W. Cohnstaedt, Caterina M. Scoglio
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Ensemble Kalman filter estimation of disease outbreak dynamics vector-borne disease modeling forecast of dengue cases Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/1c50e2193be6472cb77b2a46a1ba2122
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spelling	oai:doaj.org-article:1c50e2193be6472cb77b2a46a1ba21222021-12-02T00:00:26ZSEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics2169-353610.1109/ACCESS.2021.3129997https://doaj.org/article/1c50e2193be6472cb77b2a46a1ba21222021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9624940/https://doaj.org/toc/2169-3536Dengue fever is an acute mosquito-borne viral infection that results in a heavy social burden in many tropical and subtropical regions. Accurate forecasts of dengue outbreak allow the local health officials to take proactive action such as positioning mosquito control equipment or preparing medical resources. We developed a new model for dengue outbreak estimation and forecast that adopts the vector-borne disease model SEIR-SEI with compartments Susceptible-Exposed-Infectious-Recovered (for host) and Susceptible-Exposed-Infectious (for vector) into the ensemble Kalman filtering (EnKF) assimilation method. The SEIR-SIR-EnKF model was first validated using synthetic dengue outbreak in twin experiments. Then, the model produced good performance when applied to estimate and forecast the dengue outbreak dynamics with real historical time-series cases in 3 different cities. Furthermore, we compared the accuracy of the real-time predictions between SEIR-SEI-EnKF model, SEIR-EnKF model, and SIR-EnKF model; we found the SEIR-SEI-EnKF model had the most accurate predictions.Chunlin YiLee W. CohnstaedtCaterina M. ScoglioIEEEarticleEnsemble Kalman filterestimation of disease outbreak dynamicsvector-borne disease modelingforecast of dengue casesElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 156758-156767 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Ensemble Kalman filter estimation of disease outbreak dynamics vector-borne disease modeling forecast of dengue cases Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Ensemble Kalman filter estimation of disease outbreak dynamics vector-borne disease modeling forecast of dengue cases Electrical engineering. Electronics. Nuclear engineering TK1-9971 Chunlin Yi Lee W. Cohnstaedt Caterina M. Scoglio SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics
description	Dengue fever is an acute mosquito-borne viral infection that results in a heavy social burden in many tropical and subtropical regions. Accurate forecasts of dengue outbreak allow the local health officials to take proactive action such as positioning mosquito control equipment or preparing medical resources. We developed a new model for dengue outbreak estimation and forecast that adopts the vector-borne disease model SEIR-SEI with compartments Susceptible-Exposed-Infectious-Recovered (for host) and Susceptible-Exposed-Infectious (for vector) into the ensemble Kalman filtering (EnKF) assimilation method. The SEIR-SIR-EnKF model was first validated using synthetic dengue outbreak in twin experiments. Then, the model produced good performance when applied to estimate and forecast the dengue outbreak dynamics with real historical time-series cases in 3 different cities. Furthermore, we compared the accuracy of the real-time predictions between SEIR-SEI-EnKF model, SEIR-EnKF model, and SIR-EnKF model; we found the SEIR-SEI-EnKF model had the most accurate predictions.
format	article
author	Chunlin Yi Lee W. Cohnstaedt Caterina M. Scoglio
author_facet	Chunlin Yi Lee W. Cohnstaedt Caterina M. Scoglio
author_sort	Chunlin Yi
title	SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics
title_short	SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics
title_full	SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics
title_fullStr	SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics
title_full_unstemmed	SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics
title_sort	seir-sei-enkf: a new model for estimating and forecasting dengue outbreak dynamics
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/1c50e2193be6472cb77b2a46a1ba2122
work_keys_str_mv	AT chunlinyi seirseienkfanewmodelforestimatingandforecastingdengueoutbreakdynamics AT leewcohnstaedt seirseienkfanewmodelforestimatingandforecastingdengueoutbreakdynamics AT caterinamscoglio seirseienkfanewmodelforestimatingandforecastingdengueoutbreakdynamics
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SEIR-SEI-EnKF: A New Model for Estimating and Forecasting Dengue Outbreak Dynamics

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