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FMD-VS: A virtual sensor to index FMD virus scattering

Foot-and-mouth disease (FMD) models—analytical models for tracking and analyzing FMD outbreaks—are known as dominant tools for examining the spread of the disease under various conditions and assessing the effectiveness of countermeasures. There has been some remarkable progress in modeling research...

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Detalles Bibliográficos
Autores principales: Takatsuka, Kayoko, Sekiguchi, Satoshi, Yamaba, Hisaaki, Aburada, Kentaro, Mukunoki, Masayuki, Okazaki, Naonobu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485836/
https://www.ncbi.nlm.nih.gov/pubmed/32915804
http://dx.doi.org/10.1371/journal.pone.0237961
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author Takatsuka, Kayoko
Sekiguchi, Satoshi
Yamaba, Hisaaki
Aburada, Kentaro
Mukunoki, Masayuki
Okazaki, Naonobu
author_facet Takatsuka, Kayoko
Sekiguchi, Satoshi
Yamaba, Hisaaki
Aburada, Kentaro
Mukunoki, Masayuki
Okazaki, Naonobu
author_sort Takatsuka, Kayoko
collection PubMed
description Foot-and-mouth disease (FMD) models—analytical models for tracking and analyzing FMD outbreaks—are known as dominant tools for examining the spread of the disease under various conditions and assessing the effectiveness of countermeasures. There has been some remarkable progress in modeling research since the UK epidemic in 2001. Several modeling methods have been introduced, developed, and are still growing. However, in 2010 when a FMD outbreak occurred in the Miyazaki prefecture, a crucial problem reported: Once a regional FMD outbreak occurs, municipal officials in the region must make various day-to-day decisions throughout this period of vulnerability. The deliverables of FMD modeling research in its current state appear insufficient to support the daily judgments required in such cases. FMD model can be an efficient support tool for prevention decisions. It requires being conversant with modeling and its preconditions. Therefore, most municipal officials with no knowledge or experience found full use of the model difficult. Given this limitation, the authors consider methods and systems to support users of FMD models who must make real-time epidemic-related judgments in the infected areas. We propose a virtual sensor, designated “FMD-VS,” to index FMD virus scattering in conditions where there is once a notion of FMD; and (2) shows how we apply the developed FMD-VS technique during an outbreak. In (1), we show our approach to constructing FMD-VS based on the existing FMD model and offer an analysis and evaluation method to assess its performance. We again present the results produced when the technique applied to 2010 infection data from the Miyazaki Prefecture. For (2), we outline the concept of a method that supports the prevention judgment of municipal officials and show how to use FMD-VS.
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spelling pubmed-74858362020-09-21 FMD-VS: A virtual sensor to index FMD virus scattering Takatsuka, Kayoko Sekiguchi, Satoshi Yamaba, Hisaaki Aburada, Kentaro Mukunoki, Masayuki Okazaki, Naonobu PLoS One Research Article Foot-and-mouth disease (FMD) models—analytical models for tracking and analyzing FMD outbreaks—are known as dominant tools for examining the spread of the disease under various conditions and assessing the effectiveness of countermeasures. There has been some remarkable progress in modeling research since the UK epidemic in 2001. Several modeling methods have been introduced, developed, and are still growing. However, in 2010 when a FMD outbreak occurred in the Miyazaki prefecture, a crucial problem reported: Once a regional FMD outbreak occurs, municipal officials in the region must make various day-to-day decisions throughout this period of vulnerability. The deliverables of FMD modeling research in its current state appear insufficient to support the daily judgments required in such cases. FMD model can be an efficient support tool for prevention decisions. It requires being conversant with modeling and its preconditions. Therefore, most municipal officials with no knowledge or experience found full use of the model difficult. Given this limitation, the authors consider methods and systems to support users of FMD models who must make real-time epidemic-related judgments in the infected areas. We propose a virtual sensor, designated “FMD-VS,” to index FMD virus scattering in conditions where there is once a notion of FMD; and (2) shows how we apply the developed FMD-VS technique during an outbreak. In (1), we show our approach to constructing FMD-VS based on the existing FMD model and offer an analysis and evaluation method to assess its performance. We again present the results produced when the technique applied to 2010 infection data from the Miyazaki Prefecture. For (2), we outline the concept of a method that supports the prevention judgment of municipal officials and show how to use FMD-VS. Public Library of Science 2020-09-11 /pmc/articles/PMC7485836/ /pubmed/32915804 http://dx.doi.org/10.1371/journal.pone.0237961 Text en © 2020 Takatsuka et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Takatsuka, Kayoko
Sekiguchi, Satoshi
Yamaba, Hisaaki
Aburada, Kentaro
Mukunoki, Masayuki
Okazaki, Naonobu
FMD-VS: A virtual sensor to index FMD virus scattering
title FMD-VS: A virtual sensor to index FMD virus scattering
title_full FMD-VS: A virtual sensor to index FMD virus scattering
title_fullStr FMD-VS: A virtual sensor to index FMD virus scattering
title_full_unstemmed FMD-VS: A virtual sensor to index FMD virus scattering
title_short FMD-VS: A virtual sensor to index FMD virus scattering
title_sort fmd-vs: a virtual sensor to index fmd virus scattering
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485836/
https://www.ncbi.nlm.nih.gov/pubmed/32915804
http://dx.doi.org/10.1371/journal.pone.0237961
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