Disease surveillance: a public health informatics approach ; [epidemiology, analytics, information technology]
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| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Hoboken, NJ
Wiley
2007
|
| Subjects: | |
| Online Access: | Contributor biographical information Publisher description Table of contents only Inhaltsverzeichnis |
| Physical Description: | XXIII, 458 S. Ill., graph. Darst., Kt. |
| ISBN: | 9780470068120 0470068124 |
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MARC
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| 245 | 1 | 0 | |a Disease surveillance |b a public health informatics approach ; [epidemiology, analytics, information technology] |c ed. by Joseph S. Lombardo ... |
| 264 | 1 | |a Hoboken, NJ |b Wiley |c 2007 | |
| 300 | |a XXIII, 458 S. |b Ill., graph. Darst., Kt. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Public health surveillance | |
| 650 | 4 | |a Medical informatics | |
| 650 | 4 | |a Population Surveillance |x methods | |
| 650 | 4 | |a Public Health Informatics | |
| 650 | 0 | 7 | |a E-Health |0 (DE-588)7542254-2 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a E-Health |0 (DE-588)7542254-2 |D s |
| 689 | 0 | |C b |5 DE-604 | |
| 700 | 1 | |a Lombardo, Joseph S. |e Sonstige |4 oth | |
| 856 | 4 | |u http://www.loc.gov/catdir/enhancements/fy0741/2006053118-b.html |3 Contributor biographical information | |
| 856 | 4 | |u http://www.loc.gov/catdir/enhancements/fy0741/2006053118-d.html |3 Publisher description | |
| 856 | 4 | |u http://www.loc.gov/catdir/enhancements/fy0741/2006053118-t.html |3 Table of contents only | |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016586103&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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Record in the Search Index
| _version_ | 1804137787208761344 |
|---|---|
| adam_text | Contents
Contributors
xvii
Preface
xix
Acknowledgments
xxiii
1
Disease Surveillance, a Public Health Priority
1
Joseph S.
Lombardo,
David Ross
1.1
Introduction
1
1.2
The Emerging Role oflnformatics in Public Health Practice
2
1.3
Harly Use of Technology for Public Health Practice
5
1.3.1
Harly Use of Analytics, Visualization, and Communications
5
1.3.2
Early Informatics Applications in Medicine
&
Public Health
6
1.3.3
Public Health Records Archiving
9
1.4
Guiding Principles for Development of Public Health Applications
10
1.5
Information Requirements for Automated Disease Surveillance
12
1.6
Historical Impact of Infectious Disease Outbreaks
14
1.6.1
Smallpox
14
1.6.2
Plague
15
1.6.3
Spanish Influenza,
1918 16
1.6.4
Influenza Pandemics after
1918 18
1.7
Disease as a Weapon
20
1.7.1
Bioterrorism
25
1.8
Modern Disease Surveillance Applications
26
1.8.1
Components of an Early Recognition Disease Surveillance
System
26
1.8.2
Modern Surveillance Applications for Use by State and Local
Health Departments
30
1.8.3
National Disease Surveillance Initiatives
32
1.9
Summary
35
References
35
Part I: System Design and Implementation
41
viii CONTENTS
2
Understanding the Data: Health Indicators in Disease Surveillance
43
Steven
Babin,
Steven Magruder. Shilpa Hakre. Jacqueline Coherly.
Joseph S.
Lombardo
2.1
Data Source Concepts
44
2.2
Data from Pharmacy Chains
49
2.3
Data from EMS and
911 58
2.4
Data from Telephone Triage Hotlines
60
2.5
Data from School Absenteeism and School Nurses
63
2.6
Data from Hospital Visits
65
2.7
Data from Physicians Office Visits
66
2.8
Laboratories Role in pre-diagnostic Surveillance
68
2.9
Other Health Indicator Data
70
2.9.1
Environmental Data
70
2.9.2
Animal Health Data
7.2
2.10
Data Source Evaluation
74
2.10.1
Approach and Methodology
75
2.10.2
Example: Wildfires (October
2003) 76
2.10.3
Example: Influenza Outbreak (December
2003) 79
2.10.4
Example: Gastrointestinal Illness (January-February
2004) 83
2.10.5
Conclusions
85
2.11
Study Questions
85
References
87
3
Obtaining the Data
91
Richard Wojcik, Logan
Hauenstein,
Carol Sniegoski, Rekha Holtry
3.1
Introduction to Data Collection and Archiving
91
3.1.1
The Internet: Universal Connectivity
92
3.1.2
Databases: Flexible Data Storage
95
3.1.3
Summary
97
3.2
Obtaining Access to Surveillance Data
98
3.2.1
Sharing Health Indicator Data
98
3.2.2
Data-Sharing Issues ]03
3.2.3
HIPAA and Disease Surveillance
104
3.2.4
Summary of Data Sharing
112
3.3
The Role of Standards in Data Exchange
1
1
3
3.3.1
Types of Standards
114
3.3.2
Standards Development
1)5
3.3.3
Standards for Health Indicator Data in Biosurveillence
117
3.4
CONTENTS
IX
3.3.4
National Health Information Systems
—
Implementing
Standards
119
Establishing the Data Feeds
119
3.4.1
Information Systems of the Data Provider or Source
120
3.4.2
Setting Up the Data Feed
121
3.4.3
Data Characteristics
123
3.4.4
Data Fields or Elements
125
3.4.5
Data Transfer Format
129
3.4.6
Data Transfer Protocol
132
3.4.7
Security Considerations
134
3.4.8
Data Import Methods
135
3.4.9
Data Cleaning
135
3.4.10
Data Quality
136
3.4.11
Summary
137
Study Questions
137
References
138
3.5
4
Alerting Algorithms for
Biosurveillance
143
Howard
Burkom
4.1
Statistical Alerting Algorithms
143
4.2
Features of Alerting Algorithms
147
4.2.1
Expected Data Behavior and the Denominator Problem
147
4.2.2
Recognizing the Unexpected
149
4.2.3
Use of Data Covariates
150
4.2.4
Components of an Alerting Algorithm
151
4.2.5
Steps in Algorithmic Processing
153
4.3
Outbreak Detection as a Signal-to-Noise Problem
154
4.3.1
Understanding the Noise Background
154
4.3.2
Characterizing the Outbreak Signal
155
4.3.3
Importance of Data Aggregation Decisions
158
4.4
Algorithms Based on Time-Series Data
158
4.4.1
Control Charts for Public Health Monitoring
158
4.4.2
Data Forecasting for Public Health Monitoring.
167
4.5
Spatiotemporal
Alerting Methods
176
4.5.1
The Search for Hotspots and the Spatial Baseline
176
4.5.2
Spatial Scan Statistics and Enhancements
177
4.5.3
Global Clustering Methods and Adaptations
182
4.6
Methods Considering Multiple Data Sources
183
4.6.1
Decision Making with Multiple Data Sources
183
CONTENTS
4.7
Study Questions
References
°
Putting It Together: The
Biosurveillance
Information System
193
Logan
Hauenstein,
Richard Wojcik, Wayne
Loschen,
RajAshar, Carol Sniegoski,
Nathaniel
Tabernero
5.1
Introduction
93
5.2
System Architectures for Disease Surveillance
195
5.2.1
Stand-Alone System Application Design
195
5.2.2
Thick Client vs. Thin Client
196
5.2.3
Three-Tier and Multitier Architectures
197
5.3
Databases
199
5.3.1
Database Design
199
5.3.2
Database Server Software
200
5.3.3
Database Server Hardware
200
5.3.4
Database Server Costs
202
5.3.5
DBMS Vendor Overview
202
5.4
Web Applications
203
5.4.1
Web Servers
205
5.4.2
Web Applications and Browsers
206
5.4.3
Web Applications and Geographic Information Systems
208
5.4.4
Web-Based Application Integration and Automation
209
5.5
Implementing
Syndromie
Grouping
210
5.5.1
Fixed Vocabulary Data
210
5.5.2
Free-Text Data
212
5.6
Implementing Detectors
216
5.6.1
When Will Detectors Be Used?
216
5.6.2
Designing the Detector Interface
217
5.7
Visualization in a Disease Surveillance Application
218
5.7.1
Detection-Focused Visualizations
218
5.7.2
Information System Interfaces
226
5.7.3
Visualizing Data and Information
227
5.8
Communication Among Surveillance Users
240
5.8.1
User Comments
241
5.8.2
Embedding User Comments into System Components
241
5.9
Security
242
5.9.1
Design and Implementation of a Secure System
245
5.9.2
User Authentication
248
5.9.3
Access Privilege Management Overview
250
CONTENTS xi
5.9.4 User
Responsibilities
251
5.10 System Administration 252
5.10.1
Physical
Administration 253
5.10.2
Maintaining
Software 254
5.10.3 User Management 254
5.11
Summary
255
5.12
Study Questions
255
References
256
Part II: Case Studies
263
6
Modern Disease Surveillance Systems in Public Health Practice
265
Sheri Happel Lewis, Kathy Hurt-Mullen, Colleen Martin, Haobo Ma,
Jerome
1.
Tokars,
Joseph S.
Lombardo,
Steven
Babin
6.1
Public Health Surveillance Requirements
265
6.1.1
Disease Reporting Requirements
266
6.1.2
Existing Automated Disease Surveillance Systems
269
6.2
Identification of Abnormal Health Conditions
273
6.2.1
Monitoring Surveillance System Outputs
273
6.2.2
Characterization of Anomalies
274
6.2.3
Case Studies
278
6.2.4
Summary of Anomaly Characterization
284
6.2.5
Assessing the Public Health Importance of Findings
285
6.3
Utility at the Local Level
285
6.3.1
Specific System Features and Utility to Public Health Officials
286
6.3.2
Local Perspective on Implementation
286
6.3.3
Regional Perspective
288
6.4
Electronic
Biosurveillance
at the National Level
291
6.4.1
В
ioSense System Description
291
6.4.2
Monitoring of BioSense Application for National Surveillance
295
6.4.3
Movement Toward Surveillance System Standardization
297
6.5
Summary
298
6.6
Study Questions
298
References
299
7
Canadian Applications of
Modera
Surveillance Informatics
303
Jeff Aramini, Shamir Nizxir Mukhi
7.1
Introduction: Disease Surveillance in Canada
303
7.1.1
Understanding the True Public Health Needs
303
XU CONTENTS
7.1.2
Developing and Harnessing the Right Technology
304
7.2
Disease-Specific Surveillance Enabled Through Technology
307
7.2.1
Introduction
307
7.2.2
Working with Stakeholders to Improve Disease-Specific
Surveillance Through the Implementation of Technology
307
7.2.3
Lessons Learned Through Disease-Specific Surveillance
Application Development
314
7.3
Real-Time
Syndromie
Surveillance
315
7.3.1
Canadian Early Warning System
316
7.3.2
Unique Solution for a Unique Problem: FARMS
320
7.4
Conclusions: Public Health Surveillance
328
7.4.1
Importance of Communication and Collaboration
328
7.4.2
Integrating Surveillance into a Comprehensive Public Health
Information Management Framework
329
7.4.3
Future Opportunities in Public Health Surveillance
330
7.5
Study Questions
331
References
333
8
Case Study: Use of Tele-health Data for
Syndromie
Surveillance in
England and Wales
335
Duncan Cooper
8.1
Introduction
335
8.1.1
What Is Tele-health?
336
8.1.2
The UK Experience: NHS Direct
336
8.1.3
Using Telephone Triage Data for
Syndromie
Surveillance
338
8.2
System Design and Epidemiological Considerations
340
8.2.1
Data Availability
340
8.2.2
System Design
340
8.2.3
Investigating Exceedances
342
8.3
Results from the NHS Direct
Syndromie
Surveillance System
345
8.3.1
Stages
1
to
3 345
8.3.2
What Have the Data Detected?
346
8.3.3
Weekly Reporting
351
8.4
Adding Value to the Surveillance Data
352
8.4.1
Linking
Syndromie
Data with Traditional Laboratory Sources
352
8.4.2
A Statistical Model: Types of Infections That Cause People
to Phone Telephone Triage Systems
354
8.5
Conclusions
356
8.5.1
Main Benefits of the System
356
CONTENTS
ХІІІ
8.5.2 System Evaluation 358
8.5.3
Cautionary Note for Future Work
358
8.5.4 Integration
with Other UK Primary Care Surveillance
359
8.5.5
Recommendations
359
8.5.6
Final Remarks
361
8.6
Study Questions
361
References
362
9
Surveillance for Emerging Infection Epidemics in Developing
Countries: EWORS and
Alerta
DISAMAR
367
Jean-Paul Chretien, David Blazes, Cecilia Mundaca, Jonathan Glass.
Sheri Happel Lewis. Joseph S.
Lombardo,
R.
Loren
Eriekson
9.1
Improving Surveillance in Resource-Poor Settings
368
9.2
U.S. Military Overseas Public Health Capacity Building
369
9.3
Case Study
1 :
KWORS (Southeastern Asia and Peru)
371
9.3.1
System Development. Configuration, and Operation
371
9.3.2
Outbreak Detection and Response
373
9.3.3
System Flexibility
378
9.3.4
Summary
379
9.4
Case Study
2:
Alerta
DISAMAR
(Peru)
380
9.4.1
System Development, Configuration, and Operation
380
9.4.2
Outbreak Detection and Response
384
9.4.3
System Flexibility
387
9.4.4
Summary
390
9.5
Conclusions
390
9.6
Study Questions
391
References
392
Part HI: Evaluation, Education, and the Future
397
10
Evaluating Automated Surveillance Systems
399
David L. Buckeridge, Michael V. Thompson, Steven
Babin, Manin
L.
Sikes
10.1
The Context of Evaluation
399
10.1.1
Why?—The Need to Evaluate
399
10.1.2
What?
—
The Focus of Evaluation
400
10.1.3
How?
—
The Methods of Evaluation
401
10.2
Defining the Evaluation
401
10.2.1
Question and Scope
401
J
0.2.2
System Configuration
402
xiv CONTENTS
10.2.3
Outbreak
Scenario
402
10.2.4
Evaluation Plan
402
10.3
Identifying or Creating Evaluation Data
403
10.3.1
Data for Evaluation
403
10.3.2
Authentic Outbreaks
405
10.3.3
Simulated Outbreaks
405
10.3.4
Simulated Background
409
10.4
Applying Detection Algorithms and Response Protocols
410
10.4.1
Combining Background and Outbreak Data
410
10.4.2
Applying Outbreak Detection Algorithms
410
10.4.3
Applying Response Protocols
410
10.5
Measuring Performance
411
10.5.1
Outbreak Detection
412
10.5.2
Response Protocols
420
10.6
Summary
420
10.7
Study Questions
421
References
421
11
Educating the Workforce: Public Health Informatics Training
425
Harold
Lehmann
11.1
Competencies for Disease Surveillance
425
11.2
Professions of Disease Surveillance
432
11.3
Training Opportunities in Public Health Education
432
11.4
Informatics Training
433
11.4.1
Training Opportunities in Public Health Informatics
435
11.5
Conclusions
436
11.6
Study Questions
436
References
437
12
The Road Ahead: The Expanding Role of Informatics in Disease
Surveillance
443
Joseph S.
Lombardo
12.1
Introduction
443
12.2
Integration of Disease Surveillance Systems
444
12.2.1
Data Privacy and Public Health Networks
445
12.2.2
Standards for Information Sharing
446
12.2.3
Regional and National Networks
447
12.3
Surveillance System Enhancements
448
12.3.1
Better Health Indicators
448
CONTENTS
XV
12.3.2 Biostatistics 450
12.3.3 Information Technology 451
12.3.4 Health Department Business
Processes
452
12.4
Study
Questions
452
References
453
Index
455
|
| adam_txt |
Contents
Contributors
xvii
Preface
xix
Acknowledgments
xxiii
1
Disease Surveillance, a Public Health Priority
1
Joseph S.
Lombardo,
David Ross
1.1
Introduction
1
1.2
The Emerging Role oflnformatics in Public Health Practice
2
1.3
Harly Use of Technology for Public Health Practice
5
1.3.1
Harly Use of Analytics, Visualization, and Communications
5
1.3.2
Early Informatics Applications in Medicine
&
Public Health
6
1.3.3
Public Health Records Archiving
9
1.4
Guiding Principles for Development of Public Health Applications
10
1.5
Information Requirements for Automated Disease Surveillance
12
1.6
Historical Impact of Infectious Disease Outbreaks
14
1.6.1
Smallpox
14
1.6.2
Plague
15
1.6.3
Spanish Influenza,
1918 16
1.6.4
Influenza Pandemics after
1918 18
1.7
Disease as a Weapon
20
1.7.1
Bioterrorism
25
1.8
Modern Disease Surveillance Applications
26
1.8.1
Components of an Early Recognition Disease Surveillance
System
26
1.8.2
Modern Surveillance Applications for Use by State and Local
Health Departments
30
1.8.3
National Disease Surveillance Initiatives
32
1.9
Summary'
35
References
35
Part I: System Design and Implementation
41
viii CONTENTS
2
Understanding the Data: Health Indicators in Disease Surveillance
43
Steven
Babin,
Steven Magruder. Shilpa Hakre. Jacqueline Coherly.
Joseph S.
Lombardo
2.1
Data Source Concepts
44
2.2
Data from Pharmacy Chains
49
2.3
Data from EMS and
911 58
2.4
Data from Telephone Triage Hotlines
60
2.5
Data from School Absenteeism and School Nurses
63
2.6
Data from Hospital Visits
65
2.7
Data from Physicians' Office Visits
66
2.8
Laboratories Role in pre-diagnostic Surveillance
68
2.9
Other Health Indicator Data
70
2.9.1
Environmental Data
70
2.9.2
Animal Health Data
7.2
2.10
Data Source Evaluation
74
2.10.1
Approach and Methodology
75
2.10.2
Example: Wildfires (October
2003) 76
2.10.3
Example: Influenza Outbreak (December
2003) 79
2.10.4
Example: Gastrointestinal Illness (January-February
2004) 83
2.10.5
Conclusions
85
2.11
Study Questions
85
References
87
3
Obtaining the Data
91
Richard Wojcik, Logan
Hauenstein,
Carol Sniegoski, Rekha Holtry
3.1
Introduction to Data Collection and Archiving
91
3.1.1
The Internet: Universal Connectivity
92
3.1.2
Databases: Flexible Data Storage
95
3.1.3
Summary
97
3.2
Obtaining Access to Surveillance Data
98
3.2.1
Sharing Health Indicator Data
98
3.2.2
Data-Sharing Issues ]03
3.2.3
HIPAA and Disease Surveillance
104
3.2.4
Summary of Data Sharing
112
3.3
The Role of' Standards in Data Exchange
1
1
3
3.3.1
Types of Standards
114
3.3.2
Standards Development
1)5
3.3.3
Standards for Health Indicator Data in Biosurveillence
117
3.4
CONTENTS
IX
3.3.4
National Health Information Systems
—
Implementing
Standards
119
Establishing the Data Feeds
119
3.4.1
Information Systems of the Data Provider or Source
120
3.4.2
Setting Up the Data Feed
121
3.4.3
Data Characteristics
123
3.4.4
Data Fields or Elements
125
3.4.5
Data Transfer Format
129
3.4.6
Data Transfer Protocol
132
3.4.7
Security Considerations
134
3.4.8
Data Import Methods
135
3.4.9
Data Cleaning
135
3.4.10
Data Quality
136
3.4.11
Summary
137
Study Questions
137
References
138
3.5
4
Alerting Algorithms for
Biosurveillance
143
Howard
Burkom
4.1
Statistical Alerting Algorithms
143
4.2
Features of Alerting Algorithms
147
4.2.1
Expected Data Behavior and the Denominator Problem
147
4.2.2
Recognizing the Unexpected
149
4.2.3
Use of Data Covariates
150
4.2.4
Components of an Alerting Algorithm
151
4.2.5
Steps in Algorithmic Processing
153
4.3
Outbreak Detection as a Signal-to-Noise Problem
154
4.3.1
Understanding the Noise Background
154
4.3.2
Characterizing the Outbreak Signal
155
4.3.3
Importance of Data Aggregation Decisions
158
4.4
Algorithms Based on Time-Series Data
158
4.4.1
Control Charts for Public Health Monitoring
158
4.4.2
Data Forecasting for Public Health Monitoring.
167
4.5
Spatiotemporal
Alerting Methods
176
4.5.1
The Search for Hotspots and the Spatial Baseline
176
4.5.2
Spatial Scan Statistics and Enhancements
177
4.5.3
Global Clustering Methods and Adaptations
182
4.6
Methods Considering Multiple Data Sources
183
4.6.1
Decision Making with Multiple Data Sources
183
CONTENTS
4.7
Study Questions
References
'
°"
Putting It Together: The
Biosurveillance
Information System
193
Logan
Hauenstein,
Richard Wojcik, Wayne
Loschen,
RajAshar, Carol Sniegoski,
Nathaniel
Tabernero
5.1
Introduction
'93
5.2
System Architectures for Disease Surveillance
195
5.2.1
Stand-Alone System Application Design
195
5.2.2
Thick Client vs. Thin Client
196
5.2.3
Three-Tier and Multitier Architectures
197
5.3
Databases
199
5.3.1
Database Design
199
5.3.2
Database Server Software
200
5.3.3
Database Server Hardware
200
5.3.4
Database Server Costs
202
5.3.5
DBMS Vendor Overview
202
5.4
Web Applications
203
5.4.1
Web Servers
205
5.4.2
Web Applications and Browsers
206
5.4.3
Web Applications and Geographic Information Systems
208
5.4.4
Web-Based Application Integration and Automation
209
5.5
Implementing
Syndromie
Grouping
210
5.5.1
Fixed Vocabulary Data
210
5.5.2
Free-Text Data
212
5.6
Implementing Detectors
216
5.6.1
When Will Detectors Be Used?
216
5.6.2
Designing the Detector Interface
217
5.7
Visualization in a Disease Surveillance Application
218
5.7.1
Detection-Focused Visualizations
218
5.7.2
Information System Interfaces
226
5.7.3
Visualizing Data and Information
227
5.8
Communication Among Surveillance Users
240
5.8.1
User Comments
241
5.8.2
Embedding User Comments into System Components
241
5.9
Security
242
5.9.1
Design and Implementation of a Secure System
245
5.9.2
User Authentication
248
5.9.3
Access Privilege Management Overview
250
CONTENTS xi
5.9.4 User
Responsibilities
251
5.10 System Administration 252
5.10.1
Physical
Administration 253
5.10.2
Maintaining
Software 254
5.10.3 User Management 254
5.11
Summary
255
5.12
Study Questions
255
References
256
Part II: Case Studies
263
6
Modern Disease Surveillance Systems in Public Health Practice
265
Sheri Happel Lewis, Kathy Hurt-Mullen, Colleen Martin, Haobo Ma,
Jerome
1.
Tokars,
Joseph S.
Lombardo,
Steven
Babin
6.1
Public Health Surveillance Requirements
265
6.1.1
Disease Reporting Requirements
266
6.1.2
Existing Automated Disease Surveillance Systems
269
6.2
Identification of Abnormal Health Conditions
273
6.2.1
Monitoring Surveillance System Outputs
273
6.2.2
Characterization of Anomalies
274
6.2.3
Case Studies
278
6.2.4
Summary of Anomaly Characterization
284
6.2.5
Assessing the Public Health Importance of Findings
285
6.3
Utility at the Local Level
285
6.3.1
Specific System Features and Utility to Public Health Officials
286
6.3.2
Local Perspective on Implementation
286
6.3.3
Regional Perspective
288
6.4
Electronic
Biosurveillance
at the National Level
291
6.4.1
В
ioSense System Description
291
6.4.2
Monitoring of BioSense Application for National Surveillance
295
6.4.3
Movement Toward Surveillance System Standardization
297
6.5
Summary
298
6.6
Study Questions
298
References
299
7
Canadian Applications of
Modera
Surveillance Informatics
303
Jeff Aramini, Shamir Nizxir Mukhi
7.1
Introduction: Disease Surveillance in Canada
303
7.1.1
Understanding the True Public Health Needs
303
XU CONTENTS
7.1.2
Developing and Harnessing the Right Technology
304
7.2
Disease-Specific Surveillance Enabled Through Technology
307
7.2.1
Introduction
307
7.2.2
Working with Stakeholders to Improve Disease-Specific
Surveillance Through the Implementation of Technology
307
7.2.3
Lessons Learned Through Disease-Specific Surveillance
Application Development
314
7.3
Real-Time
Syndromie
Surveillance
315
7.3.1
Canadian Early Warning System
316
7.3.2
Unique Solution for a Unique Problem: FARMS
320
7.4
Conclusions: Public Health Surveillance
328
7.4.1
Importance of Communication and Collaboration
328
7.4.2
Integrating Surveillance into a Comprehensive Public Health
Information Management Framework
329
7.4.3
Future Opportunities in Public Health Surveillance
330
7.5
Study Questions
331
References
333
8
Case Study: Use of Tele-health Data for
Syndromie
Surveillance in
England and Wales
335
Duncan Cooper
8.1
Introduction
335
8.1.1
What Is Tele-health?
336
8.1.2
The UK Experience: NHS Direct
336
8.1.3
Using Telephone Triage Data for
Syndromie
Surveillance
338
8.2
System Design and Epidemiological Considerations
340
8.2.1
Data Availability
340
8.2.2
System Design
340
8.2.3
Investigating Exceedances
342
8.3
Results from the NHS Direct
Syndromie
Surveillance System
345
8.3.1
Stages
1
to
3 345
8.3.2
What Have the Data Detected?
346
8.3.3
Weekly Reporting
351
8.4
Adding Value to the Surveillance Data
352
8.4.1
Linking
Syndromie
Data with Traditional Laboratory Sources
352
8.4.2
A Statistical Model: Types of Infections That Cause People
to Phone Telephone Triage Systems
354
8.5
Conclusions
356
8.5.1
Main Benefits of the System
356
CONTENTS
ХІІІ
8.5.2 System Evaluation 358
8.5.3
Cautionary Note for Future Work
358
8.5.4 Integration
with Other UK Primary Care Surveillance
359
8.5.5
Recommendations
359
8.5.6
Final Remarks
361
8.6
Study Questions
361
References
362
9
Surveillance for Emerging Infection Epidemics in Developing
Countries: EWORS and
Alerta
DISAMAR
367
Jean-Paul Chretien, David Blazes, Cecilia Mundaca, Jonathan Glass.
Sheri Happel Lewis. Joseph S.
Lombardo,
R.
Loren
Eriekson
9.1
Improving Surveillance in Resource-Poor Settings
368
9.2
U.S. Military Overseas Public Health Capacity Building
369
9.3
Case Study
1 :
KWORS (Southeastern Asia and Peru)
371
9.3.1
System Development. Configuration, and Operation
371
9.3.2
Outbreak Detection and Response
373
9.3.3
System Flexibility
378
9.3.4
Summary
379
9.4
Case Study
2:
Alerta
DISAMAR
(Peru)
380
9.4.1
System Development, Configuration, and Operation
380
9.4.2
Outbreak Detection and Response
384
9.4.3
System Flexibility
387
9.4.4
Summary
390
9.5
Conclusions
390
9.6
Study Questions
391
References
392
Part HI: Evaluation, Education, and the Future
397
10
Evaluating Automated Surveillance Systems
399
David L. Buckeridge, Michael \V. Thompson, Steven
Babin, Manin
L.
Sikes
10.1
The Context of Evaluation
399
10.1.1
Why?—The Need to Evaluate
399
10.1.2
What?
—
The Focus of Evaluation
400
10.1.3
How?
—
The Methods of Evaluation
401
10.2
Defining the Evaluation
401
10.2.1
Question and Scope
401
J
0.2.2
System Configuration
402
xiv CONTENTS
10.2.3
Outbreak
Scenario
402
10.2.4
Evaluation Plan
402
10.3
Identifying or Creating Evaluation Data
403
10.3.1
Data for Evaluation
403
10.3.2
Authentic Outbreaks
405
10.3.3
Simulated Outbreaks
405
10.3.4
Simulated Background
409
10.4
Applying Detection Algorithms and Response Protocols
410
10.4.1
Combining Background and Outbreak Data
410
10.4.2
Applying Outbreak Detection Algorithms
410
10.4.3
Applying Response Protocols
410
10.5
Measuring Performance
411
10.5.1
Outbreak Detection
412
10.5.2
Response Protocols
420
10.6
Summary
420
10.7
Study Questions
421
References
421
11
Educating the Workforce: Public Health Informatics Training
425
Harold
Lehmann
11.1
Competencies for Disease Surveillance
425
11.2
Professions of Disease Surveillance
432
11.3
Training Opportunities in Public Health Education
432
11.4
Informatics Training
433
11.4.1
Training Opportunities in Public Health Informatics
435
11.5
Conclusions
436
11.6
Study Questions
436
References
437
12
The Road Ahead: The Expanding Role of Informatics in Disease
Surveillance
443
Joseph S.
Lombardo
12.1
Introduction
443
12.2
Integration of Disease Surveillance Systems
444
12.2.1
Data Privacy and Public Health Networks
445
12.2.2
Standards for Information Sharing
446
12.2.3
Regional and National Networks
447
12.3
Surveillance System Enhancements
448
12.3.1
Better Health Indicators
448
CONTENTS
XV
12.3.2 Biostatistics 450
12.3.3 Information Technology 451
12.3.4 Health Department Business
Processes
452
12.4
Study
Questions
452
References
453
Index
455 |
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| illustrated | Illustrated |
| index_date | 2024-07-02T21:24:33Z |
| indexdate | 2024-07-09T21:17:50Z |
| institution | BVB |
| isbn | 9780470068120 0470068124 |
| language | English |
| lccn | 2006053118 |
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| spelling | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] ed. by Joseph S. Lombardo ... Hoboken, NJ Wiley 2007 XXIII, 458 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Public health surveillance Medical informatics Population Surveillance methods Public Health Informatics E-Health (DE-588)7542254-2 gnd rswk-swf E-Health (DE-588)7542254-2 s b DE-604 Lombardo, Joseph S. Sonstige oth http://www.loc.gov/catdir/enhancements/fy0741/2006053118-b.html Contributor biographical information http://www.loc.gov/catdir/enhancements/fy0741/2006053118-d.html Publisher description http://www.loc.gov/catdir/enhancements/fy0741/2006053118-t.html Table of contents only Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016586103&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] Public health surveillance Medical informatics Population Surveillance methods Public Health Informatics E-Health (DE-588)7542254-2 gnd |
| subject_GND | (DE-588)7542254-2 |
| title | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] |
| title_auth | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] |
| title_exact_search | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] |
| title_exact_search_txtP | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] |
| title_full | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] ed. by Joseph S. Lombardo ... |
| title_fullStr | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] ed. by Joseph S. Lombardo ... |
| title_full_unstemmed | Disease surveillance a public health informatics approach ; [epidemiology, analytics, information technology] ed. by Joseph S. Lombardo ... |
| title_short | Disease surveillance |
| title_sort | disease surveillance a public health informatics approach epidemiology analytics information technology |
| title_sub | a public health informatics approach ; [epidemiology, analytics, information technology] |
| topic | Public health surveillance Medical informatics Population Surveillance methods Public Health Informatics E-Health (DE-588)7542254-2 gnd |
| topic_facet | Public health surveillance Medical informatics Population Surveillance methods Public Health Informatics E-Health |
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