NPDN Epidemiology Subcommittee

Carla Thomas

Chair

The NPDN Epidemiology Committee

The goal of the Epidemiology Committee is to design, develop and implement analyses using the NPDN diagnostic record data as well as other data from other sources, to detect outbreaks at the earliest stage possible, whether intentionally introduced or not.

Outbreaks may be local, state, regional or national events.

Epidemiology Committee Governance

The governance - is conducted by a committee of NPDN staff and members who contribute to operational efforts in epidemiology.

NPDN Epidemiology Committee Members

• Carla Thomas, Chair, Plant Pathology and Epidemiology, UCD• Andrew Coggshall, IT, Diagnostic Database Management, GIS, UCD• Paul Jepson, Entomology and Epidemiology, IPPC, OSU• Len Coop, Entomology, Weather-based Models, GIS , IPPC, OSU• Hans Luh, Relational Database Design and Analysis, Text Mining, GIS,

IPPC, OSU• David Barber, IT, Diagnostic Database Management, U of GA• Will Baldwin, IT, Diagnostic Database Management, KSU• Howard Beck, IT and Diagnostic Database Management, Relational

Database Taxonomy and Design, Distance Learning, U of FL• Forrest Nutter, Plant Pathology and Epidemiology, ISU• Casey Estep, IT, Diagnostic Database Management, Pathway Analysis,

CDFA• Mike Hill, IT, Diagnostic Database Management, Analyst, CERIS, Purdue• Shen Wang, IT and GIS, CERIS, Purdue• Eileen Luke, IT, Database Management, Project Management, CERIS,

Purdue

Epidemiology Workshop 2003

• Carla Thomas - UCD • Richard Bostock – UCD• Frank Ferrandino -

Connecticut Experiment Station

• Jim Marois - University of Florida

• Borys Tkacz - USFS • Eileen Luke – CERIS• Jim Pheasant – CERIS• Kitty Cardwell – USDA-

CSREES• Annette Sobel - Sandia Labs

• Stella Coakley - Oregon State University

• Paul Jepson - Oregon State University

• Larry Madden - Ohio State University

• Bob Zeigler - Kansas State University

• Roger Magarey – APHIS• Coanne O’Hearn – APHIS• Nandun Padokum - Silico

Insights

Definition of Anomaly Types• Host Characters – appears on new host or new part of host

• Pest Characters – change in pesticide resistance, virulence, etc.

• Geographic – appears in new place

• Temporal – appears at an unusual time of season

• Climatic –appears during unusual weather conditions

• Distribution – spreads in a new way, or at new rates

• Association – shows association with another factor that is new or unusual

Survey and analysis of legacy datasets, 2003

• Sample submission forms from 43 states were collected– Most of these forms were in paper format

• Fields included symptomology, crop history, client information, date and location of sample collection, and host condition.

• Three databases were electronic and had a sufficient number of records: – CDFA 46,264 records covering 7 years– Kansas State University 19,439 records covering 9 years – University of Georgia 2,807 records covering 5 years

• Most of the records in paragraph format text entries • Therefore a text mining approach was adopted.

20 Key Words Indicated Potential for Standardization

• Plant • Leaves• Seed• Fruit• Tip• Stem• Bark• Root• Large

• Spot• Mottled• Yellow• Brown• Discoloration• Burn• Margin• Malform• Canker• Wilting• Rot • Scattered

Phase 1 required fields

• Lab Name - automated reporting• Sample ID reporting• Diagnosis ID association anomalies• State / County geographic, first occurrence• Host Genus Host anomalies• Diagnosis Identification Genus Causal agent

anomalies• Confidence Level reporting• Received Lab Date temporal anomalies

Phase 1 optional fields• Host Common Name host anomalies• Host Species host anomalies• Host Sub-Species host anomalies• Diagnostic Method reporting• Identification Common Name causal agent anomalies• Diagnosis Identification Species causal agent anomalies• Diagnosis Identification Sub-Species causal agent anomalies• Latitude / Longitude geographic anomalies• Zip Code geographic anomalies• Sample Notes general• Diagnostic Notes general• Date Collected temporal anomalies

Phase 2 Proposed Optional Fields

• Date First Observed temporal anomalies• Plant Symptoms / Signs Observed host or causal agent anomalies• Plant Parts Affected host or causal agent anomalies• Entomology / Nematode Fields causal agent anomalies• Host Plant Situation association anomalies, reporting• Purpose of Submission reporting • Program Supported reporting• Submitter Type reporting• Damage Distribution of Affected Plants geographic anomalies, host

or causal agent anomalies• Incidence host or causal agent anomalies• Soil / Water Condition association anomalies, host or causal agent

anomalies

Definition of Anomaly Types• Host Characters – appears on new host or new part of hostHost genus, species, subspecies, plant part affected,

symptomology

• Pest Characters – change in pesticide resistance, virulence, etc.Pest/ Pathogen genus, species, subspecies, plant part affected,

symptomology

• Geographic – appears in new placestate, county, zipcode, lat./long. transportation routes

• Temporal – appears at an unusual time of seasonDate collected, date submitted, date of onset of symptoms, weather,

risk models

Anomalies (cont.)

• Climatic –appears during unusual weather conditions

Weather, climate and risk models

• Distribution – spreads in a new way, or at new ratesCombination of geographic, temporal, and

transportation fields

• Association – shows association with another factor that is new or unusual

Host, pest, ecozone, soils, land use, crop history, satellite imagery

Benefits to Phase 2

• Makes detection of unusual host or pest characteristics possible

• Makes automated programatic reporting possible

• Fills mission of NPDN in detecting and reporting unusual outbreaks earlier

Definition of Anomaly Types• Geographic – appears in new place

• Temporal – appears at an unusual time of season

• Host Characters – appears on new host or new part of host

• Pest Characters – change in pesticide resistance, virulence, etc.

• Association – shows association with another factor that is new or unusual

• Climatic –appears during unusual weather conditions

• Distribution – spreads in a new way, or at new rates

Integrated GIS Platforms

Distributed Integrated Interfaced National Database, Managed locally, distributed nationally

The value of a distributed multi-management system

• Specific expertise maintains specialized database

• Maintains data confidentiality for need to know groups through CERIS data security access

• Allows many different groups to interface.

• Distributes cost of maintenance of layers.

GVIS

• http://pnwpest.org/cgi-bin/usmapmaker.pl

• http://pnwpest.org/US/

• npdn.ceris.purdue.edu