Serveur d'exploration MERS

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Investigation of nonlinear epidemiological models for analyzing and controlling the MERS outbreak in Korea

Identifieur interne : 000D30 ( Main/Exploration ); précédent : 000D29; suivant : 000D31

Investigation of nonlinear epidemiological models for analyzing and controlling the MERS outbreak in Korea

Auteurs : Inkyung Ahn [Corée du Sud] ; Seongman Heo [Corée du Sud] ; Seunghyun Ji [Corée du Sud] ; Kyung Hyun Kim [Corée du Sud] ; Taehwan Kim [Corée du Sud] ; Eun Joo Lee [Corée du Sud] ; Jooyoung Park [Corée du Sud] ; Keehoon Sung [Corée du Sud]

Source :

RBID : PMC:7094113

Descripteurs français

English descriptors

Abstract

Highlights

By fitting the SIQ model, which employs a squashing-type function for β(t), to the real data on the confirmed cases and the quarantined cases, we obtained reasonable performance. Also, it turned out that the resultant estimated parameters belonged to plausible ranges. By comparison, the conventional SIQ model utilizing a constant transmission probability could not explain the observed data well.

As a practical guideline to avoid another similar unexpected outbreak, we draw the conclusion that combined efforts in the early stage are critically important, and sharing information including the names of affected hospitals or countries, clinical situations, and prevention methods might be important for global public health control.

We applied optimal control theory to the controlled SIQ model with the goal of minimizing the infectious compartment population and the cost of implementing the quarantine and isolation strategies. Simulation results show that the number of the MERS cases can be controlled reasonably well via the optimal control approach.


Url:
DOI: 10.1016/j.jtbi.2017.10.004
PubMed: 29031518
PubMed Central: 7094113


Affiliations:


Links toward previous steps (curation, corpus...)


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<p id="para0001">By fitting the SIQ model, which employs a squashing-type function for
<italic>β</italic>
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<p id="para0002">As a practical guideline to avoid another similar unexpected outbreak, we draw the conclusion that combined efforts in the early stage are critically important, and sharing information including the names of affected hospitals or countries, clinical situations, and prevention methods might be important for global public health control.</p>
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<label></label>
<p id="para0003">We applied optimal control theory to the controlled SIQ model with the goal of minimizing the infectious compartment population and the cost of implementing the quarantine and isolation strategies. Simulation results show that the number of the MERS cases can be controlled reasonably well via the optimal control approach.</p>
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<name sortKey="Oboho, I K" uniqKey="Oboho I">I.K. Oboho</name>
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<li>Corée du Sud</li>
</country>
</list>
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<name sortKey="Ahn, Inkyung" sort="Ahn, Inkyung" uniqKey="Ahn I" first="Inkyung" last="Ahn">Inkyung Ahn</name>
</noRegion>
<name sortKey="Heo, Seongman" sort="Heo, Seongman" uniqKey="Heo S" first="Seongman" last="Heo">Seongman Heo</name>
<name sortKey="Ji, Seunghyun" sort="Ji, Seunghyun" uniqKey="Ji S" first="Seunghyun" last="Ji">Seunghyun Ji</name>
<name sortKey="Kim, Kyung Hyun" sort="Kim, Kyung Hyun" uniqKey="Kim K" first="Kyung Hyun" last="Kim">Kyung Hyun Kim</name>
<name sortKey="Kim, Taehwan" sort="Kim, Taehwan" uniqKey="Kim T" first="Taehwan" last="Kim">Taehwan Kim</name>
<name sortKey="Lee, Eun Joo" sort="Lee, Eun Joo" uniqKey="Lee E" first="Eun Joo" last="Lee">Eun Joo Lee</name>
<name sortKey="Park, Jooyoung" sort="Park, Jooyoung" uniqKey="Park J" first="Jooyoung" last="Park">Jooyoung Park</name>
<name sortKey="Sung, Keehoon" sort="Sung, Keehoon" uniqKey="Sung K" first="Keehoon" last="Sung">Keehoon Sung</name>
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</affiliations>
</record>

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