Transcript Gastroenteritis at a University in Texas

is for Epi
Epidemiology basics
for non-epidemiologists
Session IV
Part II
Federal Public Health
Surveillance
CDC’s Role in Surveillance
• Support the states
– Provide training and consultation in public
health surveillance
– Distribute and oversee funding
• Receive, collate, analyze, and report data
• Suggest changes to be considered in public
health surveillance activities
• Report to the World Health Organization as
required and appropriate
CDC Surveillance Data Reporting
TABLE II. Provisional cases of selected notifiable diseases, United States, weeks ending
June 5, 2004, and May 31, 2003 (22nd week)
Federal Data Sources
• Over 100 federal surveillance systems
• Collect data on over 200 infectious and noninfectious conditions such as:
– Foodborne Diseases Active Surveillance Network
(FoodNet)
– National West Nile Virus Surveillance System
(ArboNet)
– Viral Hepatitis Surveillance Program (VHSP)
– Waterborne-Disease Outbreak Surveillance System
– Influenza Sentinel Physicians Surveillance Network
Federal Surveillance Resources
• CDC Morbidity and Mortality Weekly
Report (MMWR)
http://www.cdc.gov/mmwr
• CDC Office of Surveillance
http://www.cdc.gov/ncidod/osr/index.htm
Council of State and Territorial
Epidemiologists (CSTE)
http://www.cste.org
• Collaborates with CDC to recommend
changes in surveillance, including what
should be reported / published in MMWR
• Develops case definitions
• Develops reporting procedures
Example: ArboNet
• ArboNet is a cooperative surveillance
system maintained by CDC and 57 state
and local health departments for
detecting and reporting the occurrence of
domestic arboviruses.
ArboNet - Data
• Human
– Encephalitis, meningitis, fever, viremic blood
donors, other
•
•
•
•
•
Dead bird
Equine
Mosquito
Sentinel animals (chicken, pigeon, horse)
Other non-human mammals
What is West Nile Virus?
• Transmitted to humans via bites from
infected mosquitoes
• Infection usually asymptomatic; some
people have fever, headache, rash,
swollen lymph glands.
• No infections documented in the Western
Hemisphere until 1999; then 46 U.S.
states reported WNV activity in 2003!
ArboNet – Surveillance Issues
• “Real-time” reporting
– Novel occurrence of West Nile virus
– Web-based reporting (states)
– Still relies on paper-based reporting (local)
• Incorporates ecologic data
• NEDSS compatible
• Duplicity of human case reporting
Example: Influenza
U.S. Influenza Surveillance
1. World Health Organization (WHO) and
National Respiratory and Enteric Virus
Surveillance System (NREVSS) collaborating
laboratories
2. State and Territorial Epidemiologists’ Reports
3. 122 Cities Mortality Reporting System
4. U.S. Influenza Sentinel Providers Surveillance
Network (voluntary)
•
States may have state-specific sentinel/active
or passive surveillance systems
U.S. Influenza Surveillance
Does. . .
• Find out when and where
influenza is circulating
• Determine what type of
influenza viruses are
circulating
• Detect changes in the
influenza viruses
• Track influenza-related
illness
• Measure the impact
influenza is having on
deaths in the United
States
Does Not. . .
Ascertain how many
people have become ill
with influenza during the
influenza season
Influenza-like Illness
Case Definition
The Influenza-Like Illness case definition
for CDC’s surveillance system is:
1. Fever of 100 degrees Fahrenheit or
higher
AND
2. Cough OR sore throat.
CDC
Sentinel Influenza Surveillance
http://www.cdc.gov/flu/weekly/
Techniques for Analysis of
Surveillance Data
Overview
• Considerations when working with
surveillance data
• Access online census data
• Analyze surveillance data
Considerations
• Surveillance data primarily yield
descriptive statistics
• Know the inherent strengths and
weaknesses of a data set
• Examine data from the broadest to
narrowest
Rely on Computers to:
• Generate Simple, Descriptive Statistics
– Tables: frequencies, proportions, rates
– Graphs: bar, line, pie
– Maps: census tracts, counties, districts
• Aggregate or Stratify Rates
– State versus county
– Multiple weeks or months or years
– Entire population versus age, gender, or race
specific
Rely on Public Health
Professionals to:
• Contact health care providers and
laboratories to obtain missing data
• Interpret laboratory tests
• Make judgments about epidemiological
linkages
• Identify or correct mistakes in data entry
• Determine if epidemics are in progress
Surveillance Data
Descriptive Epidemiology
Person, Place, and Time
Person: What are the patterns of a disease
among different populations?
Place: What are the patterns of a disease in
different geographic locations?
Time: What are the patterns of a disease
when compared at different times (e.g., by
month, year, decade)?
Tuberculosis Cases: United States
1992 - 2002
US born
Foreign born
Overall
30000
# of cases
25000
20000
15000
10000
20
02
20
00
19
98
19
96
19
94
19
92
5000
Source: http://www.cdc.gov/epo/dphsi/annsum/2002/02graphs.htm
Raw Numbers versus Rates
Ratio
A ratio is any [fraction] obtained by dividing
one quantity by another; the numerator
and denominator are distinct quantities,
and neither is a subset of the other.
- Teutsch and Churchill (1994).
Rates, Proportions, and Percentages are
all some form of a Ratio.
What Do Rates Do?
• Measures the frequency of an event over
a period of time
• Numerator
– e.g., disease frequency for a period of time
• Denominator
– e.g., population size
Why Use Rates?
Raw
Surveillance
Data
Total
Crude
Population Rate
X 104
City A
10
1,000
.01
100 per
10,000
City B
10
1,000,000
.00001
.1 per
10,000
Rates provide frequency measures within the context of the population.
Crude versus Specific Rates
Crude Rate: Rate calculated for the total
population
Specific Rate: Rate calculated for a subset of the population (e.g., race, gender,
age)
Sample Analyses
1. Graph of Giardia cases for 2 states over time
(by year)
 Raw data
 Rates
2. Maps of Salmonella rates by county: North
Carolina, 2000
 Raw Data versus Rates
 Choropleth
Line Graph: Raw Data
Giardiasis case reports, 1998–2002
350
Number of Cases
300
250
200
Nebraska
150
Kansas
100
50
0
1998
1999
2000
2001
2001
Line Graph: Rates
Giardiasis case reports, 1998–2002
20
18
Rate per 100,000
16
14
12
Nebraska
10
Kansas
8
6
4
2
0
1998
1999
2000
2001
2001
350
300
Number of Cases
Giardiasis,
1998-2001
Raw Data
250
200
Nebraska
150
Kansas
100
50
0
1998
1999
2000
2001
2001
20
18
Rate per 100,000
16
Rates
14
12
Nebraska
10
Kansas
8
6
4
2
0
1998
1999
2000
2001
2001
Epi Map Instruction
“Generating Maps”
http://www.sph.unc.edu/nccphp/training/all_trainings/at_epi_info.htm
Raw Data Map
North Carolina Salmonella Cases by County: 2002
Data source: NC Communicable Disease Data by county for 2000, General
Communicable Disease Control Branch, Epidemiology Section, Division of Public Health
Choropleth Map
North Carolina Salmonella Cases by County: 2002
Data source: NC Communicable Disease Data by county for 2000, General
Communicable Disease Control Branch, Epidemiology Section, Division of Public Health
Choropleth Map
North Carolina Salmonella Rates by County: 2002
Rate numerators: NC Communicable Disease Data for 2000
Rate denominators: U.S. Census population data, by county, for 2000
Raw Data
Rates
Data Interpretation:
Considerations
•
•
•
•
•
Underreporting
Inconsistent Case Definitions
Has reporting protocol changed?
Has the case definition changed?
Have new providers or geographic regions
entered the surveillance system?
• Has a new intervention (e.g., screening or
vaccine) been introduced?
Session Summary: Surveillance
• Surveillance: Ongoing systematic collection,
analysis, and interpretation of health data,
essential to planning, implementation, and
evaluation of public health practice, closely
integrated with the timely dissemination to those
who need to know
• Three broad forms of surveillance
– Passive, active, and syndromic
• Applications: public health priorities; resource
allocation; assessing programs; determining
baseline rates; early detection of epidemics
Session Summary: Surveillance
• Limitations
– Uneven technology, reporting burden, training and
standardization needed
• Federal and state or local surveillance
– Collaborative, reciprocal pathway for data collection
and reporting
• Analysis and interpretation of surveillance data
– Graph rates versus raw data
– Investigate broad, total population rates prior to
specific rates
References and Resources
•Bonetti, M. et al (August 2003). Syndromic Surveillance PowerPoint
Presentation. Harvard Center for Public Health Preparedness.
•CDC case definitions
http://www.cdc.gov/epo/dphsi/casedef/case_definitions.htm
•CDC infectious disease surveillance systems
http://www.cdc.gov/ncidod/osr/site/surv_resources/surv_sys.htm
•CDC Integrated project: National electronic diseases surveillance
system
http://www.cdc.gov/od/hissb/act_int.htm
•CDC nationally notifiable infectious diseases
http://www.cdc.gov/epo/dphsi/phs/infdis2004.htm
•CDC Notifiable diseases/deaths in selected cities weekly information.
MMWR. June 4, 2004/53(21); 460-468
http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5321md.htm.
References and Resources
•
CDC Division of Public Health Surveillance and Informatics, Epidemiology
Program Office: http://www.cdc.gov/epo/dphsi
•
General Communicable Disease Control Branch, Epidemiology Section,
Division of Public Health, NC Department of Health and Human Services.
Reportable Communicable Diseases – North Carolina.
•
Klein, R. and Schoenborn, C. (January 2001). Age Adjustment Using the
2000 Projected U.S. Population. Healthy People 2010 Statistical Notes: No.
20. National Center for Health Statistics, Centers for Disease Control and
Prevention.
•
Last, J.M. (1988). A Dictionary of Epidemiology, Second Edition. New York:
Oxford University Press.
•
Teutsch, S. and Churchill, R. (1994). Principles and Practice of Public
Health Surveillance. New York: Oxford University Press.
•
U.S. Department of the Interior, U.S. Geological Survey (January 19, 2005).
http://westnilemaps.usgs.gov/background.html