Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019

Abstract African swine fever (ASF) has affected Romania since July 2017, with considerable economic and social consequences, despite the implementation of control measures mainly based on stamping out of infected pig populations. On the basis of the 2973 cumulative recorded cases up to September 201...

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Autores principales:	Mathieu Andraud, Stéphanie Bougeard, Theodora Chesnoiu, Nicolas Rose
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/22252cd2135740949bb0ccc955c1a5af
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spelling	oai:doaj.org-article:22252cd2135740949bb0ccc955c1a5af2021-12-02T10:49:11ZSpatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–201910.1038/s41598-021-81329-x2045-2322https://doaj.org/article/22252cd2135740949bb0ccc955c1a5af2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81329-xhttps://doaj.org/toc/2045-2322Abstract African swine fever (ASF) has affected Romania since July 2017, with considerable economic and social consequences, despite the implementation of control measures mainly based on stamping out of infected pig populations. On the basis of the 2973 cumulative recorded cases up to September 2019 among wild boars and domestic pigs, analysis of the epidemiological characteristics could help to identify the factors favoring the persistence and spread of ASF. A statistical framework, based on a random forest methodology, was therefore developed to assess the spatiotemporal features of the epidemics and their relationships with environmental, human, and agricultural factors. The landscape of Romania was associated with the infection dynamics, particularly concerning forested and wetland areas. Waterways were also identified as a pivotal factor, raising questions about possible waterborne transmission since these waterways are often used as a water supply for backyard holdings. However, human activity was clearly identified as the main risk factor for the spread of ASF. Although the situation in Romania cannot be directly transposed to intensive pig farming countries, the findings of this study highlight the need for strict biosecurity measures on farms, and during transportation, to avoid ASF transmission at large geographic and temporal scales.Mathieu AndraudStéphanie BougeardTheodora ChesnoiuNicolas RoseNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mathieu Andraud Stéphanie Bougeard Theodora Chesnoiu Nicolas Rose Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019
description	Abstract African swine fever (ASF) has affected Romania since July 2017, with considerable economic and social consequences, despite the implementation of control measures mainly based on stamping out of infected pig populations. On the basis of the 2973 cumulative recorded cases up to September 2019 among wild boars and domestic pigs, analysis of the epidemiological characteristics could help to identify the factors favoring the persistence and spread of ASF. A statistical framework, based on a random forest methodology, was therefore developed to assess the spatiotemporal features of the epidemics and their relationships with environmental, human, and agricultural factors. The landscape of Romania was associated with the infection dynamics, particularly concerning forested and wetland areas. Waterways were also identified as a pivotal factor, raising questions about possible waterborne transmission since these waterways are often used as a water supply for backyard holdings. However, human activity was clearly identified as the main risk factor for the spread of ASF. Although the situation in Romania cannot be directly transposed to intensive pig farming countries, the findings of this study highlight the need for strict biosecurity measures on farms, and during transportation, to avoid ASF transmission at large geographic and temporal scales.
format	article
author	Mathieu Andraud Stéphanie Bougeard Theodora Chesnoiu Nicolas Rose
author_facet	Mathieu Andraud Stéphanie Bougeard Theodora Chesnoiu Nicolas Rose
author_sort	Mathieu Andraud
title	Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019
title_short	Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019
title_full	Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019
title_fullStr	Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019
title_full_unstemmed	Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019
title_sort	spatiotemporal clustering and random forest models to identify risk factors of african swine fever outbreak in romania in 2018–2019
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/22252cd2135740949bb0ccc955c1a5af
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Spatiotemporal clustering and Random Forest models to identify risk factors of African swine fever outbreak in Romania in 2018–2019

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