Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System.

Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports t...
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Gespeichert in:

Autor*in:	Elena Arsevska [verfasserIn] Sarah Valentin [verfasserIn] Julien Rabatel [verfasserIn] Jocelyn de Goër de Hervé [verfasserIn] Sylvain Falala [verfasserIn] Renaud Lancelot [verfasserIn] Mathieu Roche [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Übergeordnetes Werk:	In: PLoS ONE - Public Library of Science (PLoS), 2007, 13(2018), 8, p e0199960
Übergeordnetes Werk:	volume:13 ; year:2018 ; number:8, p e0199960

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1371/journal.pone.0199960

Katalog-ID:	DOAJ030272122

Internformat


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520			\|a Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.
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Indexfelder

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publishDate	2018
allfields	10.1371/journal.pone.0199960 doi (DE-627)DOAJ030272122 (DE-599)DOAJ9c5e9331823942958ce2152bcf0a0754 DE-627 ger DE-627 rakwb eng Elena Arsevska verfasserin aut Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively. Medicine R Science Q Sarah Valentin verfasserin aut Julien Rabatel verfasserin aut Jocelyn de Goër de Hervé verfasserin aut Sylvain Falala verfasserin aut Renaud Lancelot verfasserin aut Mathieu Roche verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 13(2018), 8, p e0199960 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:13 year:2018 number:8, p e0199960 https://doi.org/10.1371/journal.pone.0199960 kostenfrei https://doaj.org/article/9c5e9331823942958ce2152bcf0a0754 kostenfrei http://europepmc.org/articles/PMC6075742?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2018 8, p e0199960
spelling	10.1371/journal.pone.0199960 doi (DE-627)DOAJ030272122 (DE-599)DOAJ9c5e9331823942958ce2152bcf0a0754 DE-627 ger DE-627 rakwb eng Elena Arsevska verfasserin aut Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively. Medicine R Science Q Sarah Valentin verfasserin aut Julien Rabatel verfasserin aut Jocelyn de Goër de Hervé verfasserin aut Sylvain Falala verfasserin aut Renaud Lancelot verfasserin aut Mathieu Roche verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 13(2018), 8, p e0199960 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:13 year:2018 number:8, p e0199960 https://doi.org/10.1371/journal.pone.0199960 kostenfrei https://doaj.org/article/9c5e9331823942958ce2152bcf0a0754 kostenfrei http://europepmc.org/articles/PMC6075742?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2018 8, p e0199960
allfields_unstemmed	10.1371/journal.pone.0199960 doi (DE-627)DOAJ030272122 (DE-599)DOAJ9c5e9331823942958ce2152bcf0a0754 DE-627 ger DE-627 rakwb eng Elena Arsevska verfasserin aut Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively. Medicine R Science Q Sarah Valentin verfasserin aut Julien Rabatel verfasserin aut Jocelyn de Goër de Hervé verfasserin aut Sylvain Falala verfasserin aut Renaud Lancelot verfasserin aut Mathieu Roche verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 13(2018), 8, p e0199960 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:13 year:2018 number:8, p e0199960 https://doi.org/10.1371/journal.pone.0199960 kostenfrei https://doaj.org/article/9c5e9331823942958ce2152bcf0a0754 kostenfrei http://europepmc.org/articles/PMC6075742?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2018 8, p e0199960
allfieldsGer	10.1371/journal.pone.0199960 doi (DE-627)DOAJ030272122 (DE-599)DOAJ9c5e9331823942958ce2152bcf0a0754 DE-627 ger DE-627 rakwb eng Elena Arsevska verfasserin aut Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively. Medicine R Science Q Sarah Valentin verfasserin aut Julien Rabatel verfasserin aut Jocelyn de Goër de Hervé verfasserin aut Sylvain Falala verfasserin aut Renaud Lancelot verfasserin aut Mathieu Roche verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 13(2018), 8, p e0199960 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:13 year:2018 number:8, p e0199960 https://doi.org/10.1371/journal.pone.0199960 kostenfrei https://doaj.org/article/9c5e9331823942958ce2152bcf0a0754 kostenfrei http://europepmc.org/articles/PMC6075742?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2018 8, p e0199960
allfieldsSound	10.1371/journal.pone.0199960 doi (DE-627)DOAJ030272122 (DE-599)DOAJ9c5e9331823942958ce2152bcf0a0754 DE-627 ger DE-627 rakwb eng Elena Arsevska verfasserin aut Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively. Medicine R Science Q Sarah Valentin verfasserin aut Julien Rabatel verfasserin aut Jocelyn de Goër de Hervé verfasserin aut Sylvain Falala verfasserin aut Renaud Lancelot verfasserin aut Mathieu Roche verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 13(2018), 8, p e0199960 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:13 year:2018 number:8, p e0199960 https://doi.org/10.1371/journal.pone.0199960 kostenfrei https://doaj.org/article/9c5e9331823942958ce2152bcf0a0754 kostenfrei http://europepmc.org/articles/PMC6075742?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2018 8, p e0199960
language	English
source	In PLoS ONE 13(2018), 8, p e0199960 volume:13 year:2018 number:8, p e0199960
sourceStr	In PLoS ONE 13(2018), 8, p e0199960 volume:13 year:2018 number:8, p e0199960
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Medicine R Science Q
isfreeaccess_bool	true
container_title	PLoS ONE
authorswithroles_txt_mv	Elena Arsevska @@aut@@ Sarah Valentin @@aut@@ Julien Rabatel @@aut@@ Jocelyn de Goër de Hervé @@aut@@ Sylvain Falala @@aut@@ Renaud Lancelot @@aut@@ Mathieu Roche @@aut@@
publishDateDaySort_date	2018-01-01T00:00:00Z
hierarchy_top_id	523574592
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author	Elena Arsevska
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title	Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System.
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author_browse	Elena Arsevska Sarah Valentin Julien Rabatel Jocelyn de Goër de Hervé Sylvain Falala Renaud Lancelot Mathieu Roche
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title_sort	web monitoring of emerging animal infectious diseases integrated in the french animal health epidemic intelligence system
title_auth	Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System.
abstract	Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.
abstractGer	Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.
abstract_unstemmed	Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.
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title_short	Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System.
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score	7.400139

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Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System.

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