Infectious Disease Informatics:
Overview and The BioPortal
Experience
Hsinchun Chen, Ph.D.
Artificial Intelligence Lab, U. of Arizona
NSF BioPortal Research Center
Acknowledgement: NSF, CIA, DHS, CDC,
NCI
2016/7/12
1
Medical Informatics: The computational, algorithmic, database
and information-centric approach to the study of medical and
health care problems.
Infectious Disease Informatics: Medical informatics for infectious
disease, public health, and biodefence.
Hsinchun Chen et al., 2005
Hsinchun Chen, et al., 2010
IDI and Syndromic Surveillance
Systems
 Data sources and collection strategies
 Formal-informal (sequence to epi), standards,
data entry and transmission, security
 Data analysis and outbreak detection
 Syndromic classification, outbreak detection
methods (temporal, spatial, spatial-temporal),
multiple data streams
 Data visualization, information
dissemination, and alerting
 GIS, temporal, sequence, text, interactive
 System assessment and evaluation
 Algorithms, data collection, information
dissemination, interface, usability
2016/7/12
3
Syndromic Surveillance Data Sources in Different Stages of
Developing a Disease  Reaching Situational Awareness
2016/7/12
Reproduced from Mandl et. al. (2004)
4
Syndromic Surveillance Systems
 Generation 1, paper-based: paper, fax, TEL,
TEL directory, etc.
 Generation 2, email-based: email,
Word/Access, pager, cell phone, etc.
 Generation 3, database-driven: database,
standards, messaging, tabulation, GIS,
graphs, text, etc.
 Generation 4, search engine-based: realtime, interactive, web services, visualized,
GIS, graphs, texts, sequences, contact
networks, etc.
2016/7/12
5
Syndromic Surveillance System
Survey
Projects
User population
Stakeholders
RODS
-Pennsylvania, Utah, Ohio, New Jersey, Michigan etc
RODS laboratory,
-418 facilities connected to RODS
U of Pittsburgh
STEM
N/A
IBM
ESSENCE II
300 world wide DOD medical facilities
DoD
EARS
-Various city, county, and state public health officials
in the United States and abroad of US
CDC
BioSense
Various city, county, and state public health officials in
the United States and abroad of US
CDC
RSVP
Rapid Syndrome Validation Project; Kansas, NM
Sandia NL, NM
BioPortal
NY, CA, Kansas, AZ, Taiwan
U of Arizona
2016/7/12
6
Sample Systems and Data Sources
Utilized
Projects
Data sources/Techniques
RODS
- Chief complaints (CC); OTC medication sales
- Free-text Bayesian disease classification
STEM
- Simulated disease data
- Disease modeling and visualization, SIR
ESSENCE II
- Military ambulatory visits; CC; Absenteeism data
EARS
- 911 calls; CC; Absenteeism; OTC drug sales
- Human-developed CC classification rules
BioSense
- City/state generated geocoded clinical data
- Graphing/mapping displays
RSVP
- Clinical and demographic data
- PDA entry and access
BioPortal
- Geo-coded clinical data; Gemonic sequences; Multilingual CC
- Real-time access and visualization; Web based hotspot
analysis; Sequence visualization; Multilingual ontologybased CC classification
2016/7/12
7
COPLINK System
8
COPLINK News
•The New York Times November 2, 2002
•ABC News April 15, 2003
•Newsweek Magazine March3, 2003
Dark Web System
Dark Web News
Project Seeks to Track Terror
Web Posts, 11/11/2007
Researchers say tool could trace online
posts to terrorists, 11/11/2007
Mathematicians Work to Help Track
Terrorist Activity, 9/14/2007
Team from the University of
Arizona identifies and tracks
terrorists on the Web,
9/10/2007
BioPortal: Overview, West Nile
Virus
(real-time information collection,
sharing, access, visualization,
and analysis, Epi data across
species)
2016/7/12
12
BioPortal Project Goals
 Demonstrate and assess the technical
feasibility and scalability of an infectious
disease information sharing (across species
and jurisdictions), alerting, and analysis
framework.
 Develop and assess advanced data mining and
visualization techniques for infectious disease
data analysis and predictive modeling.
 Identify important technical and policy-related
challenges in developing a national infectious
disease information infrastructure.
2016/7/12
13
Information Sharing Infrastructure Design
2016/7/12
Data Ingest Control
Module
Cleansing / Normalization
Adaptor
Adaptor
SSL/RSA
Adaptor
SSL/RSA
Info-Sharing Infrastructure
Portal Data Store
(MS SQL 2000)
PHINMS
Network
XML/HL7
Network
NYSDOH
CADHS
New
14
Data Access Infrastructure Design
Public health
professionals,
researchers, policy
makers, law enforcement
agencies & other users
WNV-BOT Portal
Browser (IE/Mozilla/…)
Data Search
and Query
SpatialTemporal
Visualization
SSL connection
Analysis /
Prediction
HAN or
Personal
Alert
Management
Web Server (Tomcat 4.21 / Struts 1.2)
Data Store
User Access Control API (Java)
2016/7/12
Dataset
Privileges
Management
Data Store
(MS SQL 2000)
Access
Privilege
Def.
15
Spatial-Temporal Visualization
 Integrates four visualization techniques




GIS View
Periodic Pattern View
Timeline View
Central Time Slider
 Visualizes the events in multiple dimensions
to identify hidden patterns





2016/7/12
Spatial
Temporal
Hotspot analysis
Phylogenetic tree
Contact network analysis
16
BioPortal Prototype Systems
2016/7/12
17
Outbreak Detection & Hotspot
Analysis
 Hotspot is a condition indicating
some form of clustering in a spatial
and temporal distribution (Rogerson & Sun
2001; Theophilides et. al. 2003; Patil & Tailie 2004;
Zeng et. al. 2004; Chang et. al. 2005)
 For WNV, localized clusters of dead birds
typically identify high-risk disease areas
(Gotham et. al. 2001); automatic detection of
dead bird clusters can help predict
disease outbreaks and allocate
prevention/control resources effectively
2016/7/12
18
Retrospective Hotspot Analysis
Problem Statement
2016/7/12
19
Risk-Adjusted Support Vector
Clustering (RSVC)
Feature space
Minimum sphere
High baseline density makes two
points far apart in feature space
Estimate baseline density
2016/7/12
20
Study II: NY WNV (birds, mosquitoes, and
humans)
140 records
March 5
224 records
May 26
baseline
July 2
new cases
 On May 26, 2002, the first dead bird
with WNV was found in NY
 Based on NY’s test dataset
2016/7/12
21
Dead Bird Hotspots Identified
2016/7/12
22
Dataset name
Advanced
Spatial / Temporal
Search criteria
Select background maps
Results
listedlist
in table
Available
dataset
User main page
Positive cases
Time range
Select NY / CA
population, river and
lakes
County / State
Choose WNV disease
data
Select CA dead bird,
chicken and NY dead
bird data
Positive cases
User Login
Positive cases
Start STV
2016/7/12
Specify bird
species
23
NYSpatial
dead bird
distribution
temporal
distribution
pattern
pattern
GIS
Timeline
Close
Zoom in
NY
Zoom in
Periodic
Pattern
Year 2001
data
Control
panel
2016/7/12
Move time
slider, year 3
2
2 weeks
View1 all
year
3 year
window
window indata
3 year span
Concentrated
Similar time
Overall pattern
in May
pattern
/ Jun
24
Spatial distribution
Overlay population map
pattern
Dead bird cases
Dead
birdlong
cases
migrate
from
island
distribute
along
Into upstate
NY
populated areas near
Hudson river
Enable
population
map
Season end
2016/7/12
Move time
slider
25
BioPortal HotSpot Analysis:
RSVC,
SaTScan, and CrimeStat Integrated (first visual, realtime hotspot analysis system for disease surveillance)
 West Nile virus in California
2016/7/12
26
Hotspot Analysis-Enabled STV
Select hotspot
Regular STV
to highlight
Selectcase points
algorithms
Hotspots
found!
Select baseline and
case periods
Select
Select
baseline
targetand
geographic
case periods
area
2016/7/12
27
BioPortal – FMD
(many species; phylogenetic
tree and news)
2016/7/12
28
FMD Global Surveillance: Lessons Learned
 Must understand risks, and
nature of changing risks, in
order to develop strategies for
prevention and mitigation on a
global scale
 Must understand the global
situation in order to prepare
locally
 United Kingdom FMD
outbreak, 2001; $12B, 5060% of 4M farm animals
(cows, pigs, sheep)
slaughtered
2016/7/12
29
International FMD BioPortal
 Real time web-based situational awareness of FMD
outbreaks worldwide through the establishment of an
international information technology system.
 FMDv characterization at the genomic level integrated
with associated epidemiological information and
modeling tools to forecast national, regional and/or
international spread and the prospect of importation
into the US and the rest of North America.
 Web-based crisis management of resources—facilities,
personnel, diagnostics, and therapeutics.
2016/7/12
30
Preliminary Global FMD Dataset





Provider: UC Davis FMD Lab
Information sources: reference labs and OIE
Coverage: 28 countries globally
Dataset size: 30,000+ records of which 6789 records are
complete
Host species: Cattle, Caprine, Ovine, Bovine, Swine, NK,
Elephant, Buffalo, Sheep, Camelidae, Goat
Regionwise Distribution of FMD Data
Europe
14%
Africa
1%
Middle East Asia
4%
Central and South
Asia
15%
Buffaloes
Elephant 3%
0%
Sheep Goats
0%
3%
Camelidae
Cattle
0%
5%
Caprine
4%
Swine
11%
Ovine
37%
South America
2016/7/12
66%
Bovine
37%
31
Global FMD Coverage in BioPortal
2016/7/12
32
FMD Migration Visualization using
BioPortal (cases in South Asia)
FMD Cases travel
back and forth
between countries
2016/7/12
33
BioPortal-Afghanistan
2016/7/12
34
International FMD News
 Provider: UC Davis FMD Lab
 Information sources: Google, Yahoo, and
open Internet sources
 Time span: Oct 4, 2004 – present (realtime messaging under development)
 Data size: 460 events (6/21/05)
 Coverage: 51 countries
(Africa:11, Asia:16,
Europe:12, Americas:12)
UNDEFINED
5%
Africa
11%
Aisa
1%
America
27%
Asia
15%
Australia
14%
2016/7/12
Europe
27%
35
Searching
FMD News


http://fmd.ucdavis.edu/
Searchable by



2016/7/12
Date range
Country
Keyword
36
Visualizing FMD News on BioPortal
2016/7/12
37
FMD Genetic Visualization
 Goal: Extend STV to incorporate 3rd
dimension, phylogenetic distance
 Include a phylogenetic tree.
 Identify phylogenetic groups and color-code the
isolate points on the map.
 Leverage available NCBI tools such as BLAST.
 Proof of concept: SAT 2 & 3 analysis
 Data: 54 partial DNA sequence records in South
Africa received from UC Davis FMD Lab (Bastos,A.D.
et al. 2000, 2003)
 Date range: 1978-1998
 Countries covered: South Africa, Zimbabwe,
Zambia, Namibia, Botswana
2016/7/12
38
Sample FMD
Sequence Records
Color-coded View (MEGA3)
Textual View of Gene Sequence
2016/7/12
39
Phylogenetic Tree
of Sample FMD Data
Group6
Identify 6 groups
within 2 major families
(MEGA3; based on
sequence similarity)
Group1
Group5
Group2
Group4
2016/7/12
Group3
40
Genetic, Spatial, and Temporal
Visualization of FMD Data
Phylogenetic tree
color coded
Isolates’
locations color
coded
Isolates’
appearances in
time
2016/7/12
41
FMD Time Sequence Analysis
First family cases
appeared throughout
the period
2nd family cases exist before
1993 and a comeback lately
Second family cases
existed before 1993 and
reappeared later after
1997
2016/7/12
42
FMD Periodic Pattern Analysis
2nd family concentrated in
Feb. while 1st family
spread evenly
2016/7/12
43
Locations of Family 1 records
Selected only
groups 1, 2, and 3
and found a spatial
cluster
2016/7/12
44
Locations of Family 2 records
Sparse isolate locations
Selected only groups
4, 5, and 6
2016/7/12
45
BioPortal: Influenza, SARS
(chief complaint syndromic
surveillance, contact
network analysis and
visualization)
2016/7/12
46
Existing CC Classification Methods
Classification Method
Systems
Authors
Keyword Match + Synonym
List + Mapping Rules
DOHMH
(NY City),
EARS
Mikosz et. al. (2004)
Weighted Keyword Match
(Vector Cosine Method) +
Mapping Rules
ESSENCE
Sniegoski (2004)
Naïve Bayesian
Bayesian Network
2016/7/12
RODS
N/A
Olszewski (2003), Ivanov et. al
(2002)
Chapman et. al. (2004)
47
Syndromic Categories in Different Systems
System
Details
#
Sdms
CDC
(2002)
11
Botulism, Hemorrhagic, Lymphadenitis,
Cutaneous Lesion, Gastrointestinal,
Respiratory, Neurological, Rash, Specific
Infection, Fever, Severe Illness or Death
EARS
41
Lower Resp., Upper Resp., Neuro, Febrile,
Poison, Hemorrhage, Botulinic, Rash, Fever,
etc. (41 categories)
RODS
8
Gastrointestinal, Constitutional,
Respiratory, Rash, Hemorrhagic, Botulinic,
Neurological, Other
ESSENCE
8
Death, Gastr, Neuro, Rash, Respi, Sepsi,
Unspe, Other
48
2016/7/12
Overall System Design
Stage 1
Stage 2
Chief
Complaints
symptoms
CC
Standardization
Symptom
Grouping
Weighted
Semantic
Similarity Score
EMT-P
UMLS
Ontology
UMLS
Concepts
2016/7/12
Synonym
List
Stage 3
Symptom
Grouping
Table
EMT-P
EARS
Symptom
Table
Symptom
Groups
Syndromes
Syndrome
Classification
JESS
EARS
Syndrome
Rules
49
Comparing BioPortal to RODS
Trained BioPortal
Syndrome
TP+FN
PPV
Sensitivity
Specificity
F
F2
GI
124
91.41%
94.35%***
98.74%
0.93***
0.93***
HEMO
30
82.86%
96.67%***
99.38%
0.89**
0.92***
RASH
15
66.67%
66.67%**
99.49%
0.67*
0.67**
RESP
110
92.08%
84.55%****
99.10%
0.88***
0.87***
UPPER_RESP
43
80.43%
86.05%
99.06%
0.83
0.84
RODS
Syndrome
TP+FN
PPV
Sensitivity
Specificity
F
F2
GI
124
89.89%
64.52%
98.97%
0.75
0.71
HEMO
30
90.91%
66.67%
99.79%*
0.77
0.73
RASH
15
58.33%
46.67%
99.49%
0.52
0.50
RESP
110
87.84%
59.09%
98.99%
0.71
0.66
UPPER_RESP
43
N/A
N/A
N/A
N/A
N/A
2016/7/12
* p-value < 0.1
** p-value < 0.05
Statistical test is based on 2,500 bootstrapings.
*** p-value < 0.01
50
Comparing BioPortal to EARS
Trained BioPortal
Syndrome
TP+FN
PPV
Sensitivity
Specificity
F
F2
GI
124
91.41%
94.35%***
98.74%
0.93***
0.93***
HEMO
30
82.86%
96.67%***
99.38%
0.89***
0.92***
RASH
15
66.67%
66.67%**
99.49%
0.67
0.67*
RESP
110
92.08%
84.55%****
99.10%
0.88***
0.87***
UPPER_RESP
43
80.4%***
86.05%***
99.06%***
0.83***
0.84***
EARS
Syndrome
TP+FN
PPV
Sensitivity
Specificity
F
F2
GI
124
93.75%*
72.58%
99.32%***
0.82
0.78
HEMO
30
100.00%***
33.33%
100.00%***
0.50
0.43
RASH
15
70.00%
46.67%
99.70%
0.56
0.53
RESP
110
90.36%
68.18%
99.10%
0.78
0.74
UPPER_RESP
43
58.70%
62.79%
98.01%
0.61
0.61
2016/7/12
* p-value < 0.1
** p-value < 0.05
Statistical test is based on 2,500 bootstrapings.
*** p-value < 0.01
51
Chinese CC Preprocessing:
System Design
English Expressions
Stage 0.1
Chinese
Chief
Complaints
Stage 0.2
Chinese
Separate
Chinese
Chinese and Expressions
Phrase
English
Segmentation
Expressions
Chinese
Medical
Phrases
Raw Chinese
CCs
2016/7/12
Segmented
Chinese
Phrases
Common
Chinese
Phrases
Stage 0.3
Chinese
Phrase
Translation
Translated
Chinese
Phrases
Chinese to
English
Dictionary
Mutual
Info.
52
Group by Hospital
2016/7/12
53
Group by Syndrome Classification
2016/7/12
54
Taiwan SARS Contact Network Visualization
Social network visualization with
patients and geographical locations
Scroll bar on time dimension to
see the evolution of a network
2016/7/12
55
Taiwan SARS Network Evolution – Hospital
Outbreak
The index patient of Heping
Hospital began to have symptoms.
2016/7/12
56
BioPortal:
Towards building integrated, real-time
situation awareness for syndromic
surveillance and biodefense
2016/7/12
57
Syndromic Surveillance vs.
BioSurveillance (Species Jumps)
 Data sources and collection strategies
 Levels of data (sequence to epi to social media),
data granularity, automated/manual, integration,
information sharing (incentives and standards)
 Data analysis and outbreak detection
 Biological/genetic modeling/analytics
(hypothesis testing), exploration, hypothesis
generation, sequence to time/space/event
 Data visualization, information
dissemination, and alerting
 Target users (DTRA), dissemination strategies,
surveillance, prediction
 System assessment and evaluation
 Target users (DTRA), acceptance, usability,
2016/7/12 situation awareness, decision making
58
BioPortal Information
 Hsinchun Chen
hchen@eller.arizona.edu
 AI Lab project information
http://ai.arizona.edu
2016/7/12
59