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High throughput analysis and alerting of disease outbreaks from the grey literature Nigel Collier Associate Professor National Institute of Informatics, Tokyo [email_address] http://research.nii.ac.jp/~collier
Background ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Text mining ,[object Object],[object Object],[object Object]
Projects [1] Collier, N.  et al ., "The GENIA project: corpus-based knowledge acquisition and information extraction from genome research papers", in Proc. of the Annual Meeting of the European Association for Computational Linguistics (EACL-99), pp.271-272, Norway , 1999. [2] Mizuta, Y.  et al . (2006), “Zone analysis in biology articles as a basis for information extraction”, International Journal of Medical Informatics, Elsevier, Vol. 75, Issue 6, pp. 468-487. [3] Collier, N.  et al . (2007), "Detecting Web rumours with a multilingual ontology supported text classification system", Advances in Disease Surveillance, vol. 4, pp. 242. 1998  2000  2002  2004  2006  2008  2010 GENIA PIA ZAISA BioCaster Support for database curation & resource building (PI:Tsujii) Linking biomedical annotations to SW ontologies Locating biomedical results in full research papers Early detection and alerting of PH threats
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
RESEARCH CONTEXT
Alerting real world events Cholera, 2007, Iraq 1. Real world event 2. Grey literature response 4. Detecting unusual events News volume Time 3. Text mining on unstructured news Alert level 5. Issue alert
Globalization: a problem in one location is everybody’s headache … . + many  hundreds more each year Plague, 2005, DRC Nipah, 1998, Malaysia Anthrax, 2001, USA SARS, 2003 ,HK Cholera, 2007, Iraq H5N1 flu, 2003- Ebola, 2007, DRC Foot & mouth, 2001, UK
Early detection Timely intervention ,[object Object],[object Object],[object Object],[object Object],Source:  2008 May report of the Auditor General of Canada: Chapter 5 – Surveillance of Infectious Diseases – Public Health Agency of Canada
Typical operational flow Local field workers GP reports EMS visits Over the counter sales Grocery sales School absentees Reference labs Local labs Chief medical officer/Cabinet Timeliness  Rumours WHO Disease Control Centre See also: [4] Mandl K. D.  et al.  (2004), “Implementing syndromic surveillance: a practical guide informed by early experience”, Journal of the American Medical Informatics Association, vol. 11, no. 2, Mar/Apr 2004, pp. 141-150.
Trans-national issues in health security ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
BioCaster ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Grey literature ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Free Text
Typical operational flow [2] Local field workers GP reports EMS visits Over the counter sales Grocery sales School absentees Reference labs Local labs Chief medical officer/Cabinet Timeliness  Rumours WHO Disease Control Centre Grey literature analysis
Detecting the ‘unusual’ ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Existing systems * non-governmental systems GPHIN ProMed* Argus MedISys BioCaster* Location Canada USA USA EU Japan Automatic? Automatic & Manual Manual volunteers Automatic & Manual Automatic Automatic Language coverage UN official languages All? ~36? EU official languages Asia-Pacific (en,jp,th,vn,sp,zh…)  Access Closed Open Closed Closed Mixed Open source? No NA No No Yes
THEME 1: TEXT MINING SYSTEM Funding source: [A] JSPS grant in aid for scientific research on priority  areas (18049071), PI, 4/2006-3/2007 [B] JSPS grant in aid for scientific research : Young researcher award category A (18680015), PI, 4/2006-3/2008
BioCaster system overview
High throughput infrastructure Dedicated power, cooling, very high speed networking and high level of security Physically located at NII’s Chiba annex 1 hour from Tokyo ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The nature of the task: ambiguity Confusion South Sudan  hit by Ebola-like fever Zika virus  in  Micronesia  ( Yap ) Vista  attacked by 13-year old  virus Obama fever  builds as black   Americans  await a new era Undiagnosed disease  in  Java Bird flu  outbreak drill spooks Manitoba  town Boredom  causing   outbreaks of  petrol sniffing
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],The nature of the task: uncontrolled vocabularies
Entity analysis ,[object Object],[object Object],Target >80
Entity analysis issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Bio or Non-Bio? ,[object Object],[object Object],[object Object],[object Object],[4] Doan, S., Kawazoe, A. and Collier, N. (2007), "The Role of Roles in Classifying Annotated Biomedical Texts", in proceedings of BioNLP 2007, Prague, Czech Republic, June, pp. 17-24.
Event capture using a regular expression language (SRL) [5] McCrae, J., Conway, M. and Collier, N. (2009), “Simple Rule Language editor and handbook”, available from http://code.google.com/p/srl-editor/
Single slot relations [1] disease(D);species(“human”) :-  PERSON(P,matches(@victim)) skipwords(2) DISEASE(D) species human disease measles species human disease chickenpox
Single slot relations [2] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multi-slot frame ,[object Object],[object Object],[object Object],[object Object],<EVENT name=”OUTBREAK”> <SLOT name=”HAS_DISEASE” type=”DISEASE” content=”” alt=”” root_term=”” bid=””/> <SLOT name=”HAS_LOCATION.COUNTRY” type=”LOCATION” content=”” alt=”” root_term=”” bid=””/> <SLOT name=”HAS_LOCATION.PROVINCE” type=”LOCATION” content=”” alt=”” root_term=”” bid=””/> <SLOT name=”HAS_LOCATION.OTHER” type=”LOCATION” content=””/> <SLOT name=”HAS_AGENT” type=”micro_organism” content=”” alt=”” root_term=”” bid=””/> <SLOT name=”HAS_SPECIES” type=”animal” content=””/> <SLOT name=”TIME.relative” type=”string” content=””/> # Historical, Recent_Past,Present,Hypothetical <SLOT name=”INTERNATIONAL_TRAVEL” type=”Boolean” content=””/> <SLOT name=”DELIBERATE_RELEASE” type=”Boolean” content=””/> <SLOT name=”ZOONOSIS” type=”Boolean” content=””/> <SLOT name=”DRUG_RESISTANCE” type=”Boolean” content=””/> <SLOT name=”FOOD_CONTAMINATION” type=”Boolean” content=””/> <SLOT name=”HOSPITAL_WORKER” type=”Boolean” content=””/>  <SLOT name=”FARM_WORKER” type=”Boolean” content=””/> <SLOT name=”MALFORMED_PRODUCT” type=”Boolean” content=””/> <SLOT name=”NEW_TYPE_AGENT”> type=”Boolean” content=””/> <SLOT name=”COMMENT” type=”string” content=””/> </EVENT>
Multi-slot challenge Is the disease outbreak ongoing or historical? Is there an outbreak ongoing now in Switzerland? San Diego  measles outbreak In  San Diego  Measles, one of the most contagious diseases, has infected 11 children…  Over the past month  officials have tracked …  The latest  victim is an 8-year-old who may have spread the virus during  a visit to Whole Foods Market in  Hillcrest  and  later  to a Cirque du Soleil performance… This is the most measles cases in the city  in 17 years … The outbreak is believed to have started with a child who caught measles in  Switzerland , then returned to the  United States .
Multi slot relations disease measles city San Diego country United States species human Simple discourse rules OUTBREAK has_disease:  measles has_location_country: United States has_location_province: California has_agent: rubeola virus has_species: human international_travel: true
Health alerts Here is the lastest BioCaster post for All diseases in combination with United Kingdom Avian influenza update: two further swans positive for H5N1 - Media Newswire (press release) Date: 2008-02-15 Source: Google News URL:  http://media-newswire.com/release_1060198.html ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Establishing task evaluation metrics ,[object Object],[object Object],[object Object],[object Object]
Challenges: non-events ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Challenges: pre-diagnostic data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Global health monitor Key figures: >1900 news sources >9000 news reports analysed/day  http://www.biocaster.org and http://born.nii.ac.jp
THEME 2: MULTILINGUAL ONTOLOGY Funding source: [C] Trandisciplinary integration center project fund from ROIS, PI, 4/2006-3/2008 [D] JST Sakigake grant in aid for scientific research , PI, 10/2008-9/2011
The BioCaster Ontology ,[object Object],[object Object],[object Object],[object Object]
[9] Kawazoe, A., Chanlekha, H., Shigematsu, M. and Collier, N. (2008), “Structuring an event ontology for disease outbreak detection”, in BMC Bioinformatics (in press). [10] Collier, N., Kawazoe, A., Jin, L., Shigematsu, M., Dien, D. Barrero, R., Takeuchi , K.and Kawtrakul, A. (2007), “A multilingual ontology for infectious disease surveillance: rationale, design and challenges”, Language Resources and Evaluation, Elsevier, DOI: 10.1007/s10579-007-9019-7. A closer look
Example BCO classes* Language ar en fr id ja ko ma ru sp th vi zh Link ICD10 (232) ICD9 (185) LOINC (316) MeSH (1119) MedDRA (218) NCIMetaThesaurus (338) OIE (18) PHAC (53) Pathport (34) SNOMED CT (485) Wikipedia (685) Term arabicTerm (968) englishTerm (4113) frenchTerm (1281) indonesianTerm (1081) japaneseTerm (2077) koreanTerm (1176) malaysianTerm (1001) russianTerm (1187) spanishTerm (1171) thaiTerm (1485) vietnameseTerm (1297) chineseTerm(1142) Diseases AvianDisease (22) BeeDisease (6) BovineDisease (24) CanineDisease (4) CaprineDisease (14) CervineDisease (2) EquineDisease (17) FelineDisease (4) FishDisease (2) HumanDisease (216) LaomorphDisease (2) Non-humanPrimateDisease (16) OtherDisease (2) RodentDisease (8) SwineDisease (12) * Figures in brackets indicate current number of individuals
Simple rules to fill in the gaps ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ontology construction and maintenance ,[object Object],[object Object],[object Object],[object Object],[5] Collier, N.,  et al.  (2007), “A multilingual ontology for infectious disease surveillance: rationale, design and challenges”, Language Resources and Evaluation, Elsevier, DOI: 10.1007/s10579-007-9019-7. [6] Kawazoe, A.  et al.  (2008), “Structuring an event ontology for disease outbreak detection”, in BMC Bioinformatics, 9 (Suppl 3): S8, DOI: 10.1186/1471-2105-9-S3-S8. [7] Kawazoe, A. et al. “The development of a schema for the annotation of terms in the BioCaster disease detection/tracking system” invited paper for a special edition of the journal of Applied Ontology. [8] McCrae, J. and Collier, N. (2008), “Synonym set extraction from the biomedical literature by lexical discovery”, in BMC Bioinformatics, 9:159, DOI: 10.1186/1471-2105-9-159.
Applying OntoClean to the BCO ,[object Object],[object Object],[object Object],[object Object],[11] Guarino N, Welty C. Ontological analysis of taxonomic relations. Lander A, Storey V (eds.) Proceedings of ER-2000: The International Conference on Conceptual Modeling, vol. 1920, 210-224, Springer Verlag LNCS, Berlin, Germany.  [12] Kawazoe, A., Jin, L., Shigematsu, M., Barrero, R., Taniguchi, K. and Collier, N. (2006), &quot;The development of a schema for the annotation of terms in the BioCaster disease detection/tracking system&quot;, Proceedings of the KR-MED 2006, Baltimore, Maryland, USA.
THEME 3: EARLY ALERTING Funding source: [D] JST Sakigake grant in aid for scientific research , PI, 10/2008-9/2011
Overview ,[object Object],[object Object],[object Object],[object Object]
Basic approach Frequencies for daily disease- country counts are compared  against the 7 day history; An abnormal trend signals a possible alert Possible alerts are compared against  human gold standard alerts to calculate accuracy
Automatic alerting in action at http://born.nii.ac.jp
FUTURE DEVELOPMENTS
Future work ,[object Object],[object Object],[object Object]
Many thanks to ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
THANK YOU ,[object Object]

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High throughput analysis and alerting of disease outbreaks from the grey literature

  • 1. High throughput analysis and alerting of disease outbreaks from the grey literature Nigel Collier Associate Professor National Institute of Informatics, Tokyo [email_address] http://research.nii.ac.jp/~collier
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  • 4. Projects [1] Collier, N. et al ., &quot;The GENIA project: corpus-based knowledge acquisition and information extraction from genome research papers&quot;, in Proc. of the Annual Meeting of the European Association for Computational Linguistics (EACL-99), pp.271-272, Norway , 1999. [2] Mizuta, Y. et al . (2006), “Zone analysis in biology articles as a basis for information extraction”, International Journal of Medical Informatics, Elsevier, Vol. 75, Issue 6, pp. 468-487. [3] Collier, N. et al . (2007), &quot;Detecting Web rumours with a multilingual ontology supported text classification system&quot;, Advances in Disease Surveillance, vol. 4, pp. 242. 1998 2000 2002 2004 2006 2008 2010 GENIA PIA ZAISA BioCaster Support for database curation & resource building (PI:Tsujii) Linking biomedical annotations to SW ontologies Locating biomedical results in full research papers Early detection and alerting of PH threats
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  • 7. Alerting real world events Cholera, 2007, Iraq 1. Real world event 2. Grey literature response 4. Detecting unusual events News volume Time 3. Text mining on unstructured news Alert level 5. Issue alert
  • 8. Globalization: a problem in one location is everybody’s headache … . + many hundreds more each year Plague, 2005, DRC Nipah, 1998, Malaysia Anthrax, 2001, USA SARS, 2003 ,HK Cholera, 2007, Iraq H5N1 flu, 2003- Ebola, 2007, DRC Foot & mouth, 2001, UK
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  • 10. Typical operational flow Local field workers GP reports EMS visits Over the counter sales Grocery sales School absentees Reference labs Local labs Chief medical officer/Cabinet Timeliness Rumours WHO Disease Control Centre See also: [4] Mandl K. D. et al. (2004), “Implementing syndromic surveillance: a practical guide informed by early experience”, Journal of the American Medical Informatics Association, vol. 11, no. 2, Mar/Apr 2004, pp. 141-150.
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  • 14. Typical operational flow [2] Local field workers GP reports EMS visits Over the counter sales Grocery sales School absentees Reference labs Local labs Chief medical officer/Cabinet Timeliness Rumours WHO Disease Control Centre Grey literature analysis
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  • 16. Existing systems * non-governmental systems GPHIN ProMed* Argus MedISys BioCaster* Location Canada USA USA EU Japan Automatic? Automatic & Manual Manual volunteers Automatic & Manual Automatic Automatic Language coverage UN official languages All? ~36? EU official languages Asia-Pacific (en,jp,th,vn,sp,zh…) Access Closed Open Closed Closed Mixed Open source? No NA No No Yes
  • 17. THEME 1: TEXT MINING SYSTEM Funding source: [A] JSPS grant in aid for scientific research on priority areas (18049071), PI, 4/2006-3/2007 [B] JSPS grant in aid for scientific research : Young researcher award category A (18680015), PI, 4/2006-3/2008
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  • 20. The nature of the task: ambiguity Confusion South Sudan hit by Ebola-like fever Zika virus in Micronesia ( Yap ) Vista attacked by 13-year old virus Obama fever builds as black Americans await a new era Undiagnosed disease in Java Bird flu outbreak drill spooks Manitoba town Boredom causing outbreaks of petrol sniffing
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  • 25. Event capture using a regular expression language (SRL) [5] McCrae, J., Conway, M. and Collier, N. (2009), “Simple Rule Language editor and handbook”, available from http://code.google.com/p/srl-editor/
  • 26. Single slot relations [1] disease(D);species(“human”) :- PERSON(P,matches(@victim)) skipwords(2) DISEASE(D) species human disease measles species human disease chickenpox
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  • 29. Multi-slot challenge Is the disease outbreak ongoing or historical? Is there an outbreak ongoing now in Switzerland? San Diego measles outbreak In San Diego Measles, one of the most contagious diseases, has infected 11 children… Over the past month officials have tracked … The latest victim is an 8-year-old who may have spread the virus during a visit to Whole Foods Market in Hillcrest and later to a Cirque du Soleil performance… This is the most measles cases in the city in 17 years … The outbreak is believed to have started with a child who caught measles in Switzerland , then returned to the United States .
  • 30. Multi slot relations disease measles city San Diego country United States species human Simple discourse rules OUTBREAK has_disease: measles has_location_country: United States has_location_province: California has_agent: rubeola virus has_species: human international_travel: true
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  • 35. Global health monitor Key figures: >1900 news sources >9000 news reports analysed/day http://www.biocaster.org and http://born.nii.ac.jp
  • 36. THEME 2: MULTILINGUAL ONTOLOGY Funding source: [C] Trandisciplinary integration center project fund from ROIS, PI, 4/2006-3/2008 [D] JST Sakigake grant in aid for scientific research , PI, 10/2008-9/2011
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  • 38. [9] Kawazoe, A., Chanlekha, H., Shigematsu, M. and Collier, N. (2008), “Structuring an event ontology for disease outbreak detection”, in BMC Bioinformatics (in press). [10] Collier, N., Kawazoe, A., Jin, L., Shigematsu, M., Dien, D. Barrero, R., Takeuchi , K.and Kawtrakul, A. (2007), “A multilingual ontology for infectious disease surveillance: rationale, design and challenges”, Language Resources and Evaluation, Elsevier, DOI: 10.1007/s10579-007-9019-7. A closer look
  • 39. Example BCO classes* Language ar en fr id ja ko ma ru sp th vi zh Link ICD10 (232) ICD9 (185) LOINC (316) MeSH (1119) MedDRA (218) NCIMetaThesaurus (338) OIE (18) PHAC (53) Pathport (34) SNOMED CT (485) Wikipedia (685) Term arabicTerm (968) englishTerm (4113) frenchTerm (1281) indonesianTerm (1081) japaneseTerm (2077) koreanTerm (1176) malaysianTerm (1001) russianTerm (1187) spanishTerm (1171) thaiTerm (1485) vietnameseTerm (1297) chineseTerm(1142) Diseases AvianDisease (22) BeeDisease (6) BovineDisease (24) CanineDisease (4) CaprineDisease (14) CervineDisease (2) EquineDisease (17) FelineDisease (4) FishDisease (2) HumanDisease (216) LaomorphDisease (2) Non-humanPrimateDisease (16) OtherDisease (2) RodentDisease (8) SwineDisease (12) * Figures in brackets indicate current number of individuals
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  • 43. THEME 3: EARLY ALERTING Funding source: [D] JST Sakigake grant in aid for scientific research , PI, 10/2008-9/2011
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  • 45. Basic approach Frequencies for daily disease- country counts are compared against the 7 day history; An abnormal trend signals a possible alert Possible alerts are compared against human gold standard alerts to calculate accuracy
  • 46. Automatic alerting in action at http://born.nii.ac.jp
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