Transcript Document

I is for Investigation
Outbreak Investigation Methods from
Mystery to Mastery
Session I
Recognizing an Outbreak
Session Overview
• Overview of outbreak investigation
• Identifying a potential outbreak
• Verifying the diagnosis and confirming the
outbreak
• Defining and finding cases
• Orienting data by person, place, and time
Learning Objectives
• Identify steps of an outbreak investigation
• Develop a case definition
• Identify a process for case finding in an
outbreak
• Apply methods used to orient data by
person, place, and time
• Create and interpret epidemic curves
Overview of Outbreak
Investigation
What is an Outbreak?
The occurrence of more cases of a disease than
expected for a particular place and time
35
Number of cases
30
25
20
15
Unexpected
10
5
Expected number of cases
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Days
Basic Steps of an
Outbreak Investigation
1.
2.
3.
4.
5.
6.
7.
8.
Verify the diagnosis and confirm the outbreak
Define a case and conduct case finding
Tabulate and orient data: time, place, person
Take immediate control measures
Formulate and test hypothesis
Plan and execute studies
Implement and evaluate control measures
Communicate findings
Exceptions to the Rule
Basic steps provide a model for systematic
outbreak investigations
• No two outbreaks are alike!
• Steps of an outbreak could…
– occur in a different order
– occur simultaneously
– be repeated
Identifying a Potential
Outbreak
Outbreak Information Sources
• Laboratory-confirmed reports
of notifiable diseases
• Clinician reports of notifiable
disease and unusual
increases in disease
• Concerned parent/citizen
reports to health department
• Media
Gathering Information from
Case Reports
Collect:
– As much information as possible
– Negative as well as positive information
– Food history
• 3 days (72 hrs) to 5 days, if unknown agent
• Within incubation period, if known agent
– Exposure sources such as water, people, animals
Disease Surveillance: Case Report
What questions would you ask an ill person?
WHO:
age, sex, occupation, any others ill
WHAT:
physical condition, symptoms,
medication, and medical care sought
WHEN:
when did the affected become ill
WHERE:
city/school, address, telephone number
of ill person(s)
WHY/HOW: suspected cause of illness, risk factors,
modes of transmission, notes on people
who did not become ill
Disease Surveillance:
What Next?
• File the report and
stop?
• Investigate further?
Deciding to Investigate
• Ideally, all reports of possible outbreaks
should be investigated to:
– Prevent other persons from becoming ill
– Identify potentially problematic practices
– Add to the knowledge of infectious diseases
Why Investigate?
• Surveillance detects
increases in cases of
disease
• Characterize the problem
• Prevention and control
• Research and answer
scientific questions
• Train epidemiologists
• Political / legal concerns
Maybe You Should Investigate...
• If illness is severe (life-threatening)
• If there are confirmed clusters or large
numbers of a similar illness
• If foodborne illness is from a food handler
• If illness is associated with commerciallydistributed food
• If there is outside pressure to investigate
(media, politicians)
Maybe You Shouldn’t Investigate...
• If affected persons might not have the same illness
• If affected persons are not able to provide adequate
information for investigation
• If the diagnosis and/or clinical symptoms are not
consistent with the related exposures
• If there are repeated complaints made by the same
individual(s) for which prior investigations revealed
no significant findings
Verifying the Diagnosis and
Confirming the Outbreak
Verify the Diagnosis
Evaluate:
 Predominant signs and symptoms
 Incubation period
 Duration of symptoms
 Suspected food
 Suspected toxin, virus, or bacteria
 Laboratory testing of stool, blood, or vomitus
Identify the Pathogen
• Ensure all suspect patients
have the same pathogen
• Identify the potential
incubation period for
hypothesis generation
• Can proceed while waiting
for laboratory diagnosis
Verify the Diagnosis
Potential reasons for negative laboratory
results:
• Illness could be due to an organism that
wasn’t tested for
• Mishandling of specimen resulting in death
of the pathogen (during storage, transport,
processing, or culture)
• Specimens collected too late in the illness
Defining and Finding Cases
Case Definition
A standard set of criteria for deciding
whether an individual should be classified as
having the disease of interest, including:
• Clinical criteria (signs, symptoms, and laboratory
tests)
• Person, place, and time criteria
Case Definition
• Can be modified as more data are
obtained
• Should not include a possible cause of the
outbreak
Case Finding
• Contact local care providers
• Contact schools, large businesses
• Contact state health department /
neighboring health departments
• Ask case-patients if they know of others
who are ill
Additional sources may be appropriate, depending
on the outbreak.
Orienting Data by Person and
Place
Descriptive Epidemiology
• Comprehensively describes the outbreak
– Person
– Place
– Time
• Line listings
• Graphs
– Bar graphs
– Histograms
• Measures of central tendency
Line Listing
Signs/Symptoms
Lab
Demographics
Case
#
Report
Date
Onset
Date
Physician
Diagnosis
N
V
J
HAIgM
Sex
Age
1
10/12/02
10/5/02
Hepatitis A
1
1
1
1
M
37
2
10/12/02
10/4/02
Hepatitis A
1
0
1
1
M
62
3
10/13/02
10/4/02
Hepatitis A
1
0
1
1
M
38
4
10/13/02
10/9/02
NA
0
0
0
NA
F
44
5
10/15/02
Hepatitis A
1
1
0
1
M
17
6
10/16/02
Hepatitis A
0
0
1
1
F
43
10/13/02
10/6/02
Bar Graph (Person)
Histogram (Person)
Measures of Central Tendency
Mean (Average)
• Equals the sum of all values divided by the
number of values.
• Example:
– Cases: 7,10, 8, 5, 5, 37, 9 years old
– Mean = (7+10+8+5+5+37+9)/7
– Mean = 11.6 years of age
Measures of Central Tendency
Median (50th percentile)
• The value that falls in the middle position
when the measurements are ordered from
smallest to largest
• Example:
– Ages: 7,10, 8, 5, 5, 37, 9
– Ages sorted: 5, 5, 7, 8, 9,10, 37
– Median age = 8
Calculate a Median Value
• If the number of measurements is odd:
– Median = value with rank (n+1) / 2
– n = the number of values
• Example:
–
–
–
–
5, 5, 7, 8, 9,10, 37
n=7
(n+1) / 2 = (7+1) / 2 = 4
The 4th value = 8
Calculate a Median Value
• If the number of measurements is even:
– Median=average of the two values with:
• rank of n / 2 and rank of (n / 2) + 1
• Example
–
–
–
–
–
–
5, 5, 7, 8, 9, 10, 12, 37
n=8
(8 / 2) = 4, so “8” is the first value
(8 / 2) + 1 =5, so “9” is the second value
(8 + 9) / 2 = 8.5
The median value = 8.5
Descriptive Epidemiology: Place
Spot map
• Shows where cases live, work, spend time
• If population size varies between locations being
compared, use location-specific attack rates
instead of number of cases
Descriptive Epidemiology: Place
Source: http://www.phppo.cdc.gov/PHTN/catalog/pdf-file/LESSON4.pdf
Orienting Data by Time
Epidemic Curves
2/
1
1/ 2
3/
12
1/
4/
12
1/
5/
12
1/
6/
12
1/
7/
12
1/
8/
12
1/
9/
1/ 12
10
/1
1/ 2
11
/
1/ 12
12
/1
1/ 2
13
/1
2
1/
# of Cases
Descriptive Epidemiology: Time
20
18
16
14
12
10
8
6
4
2
0
Day
Descriptive Epidemiology: Time
• An epidemic curve (epi curve) is a
graphical depiction of the number of cases
of illness by the date of illness onset
• Can provide information on the outbreak’s:
– Pattern of spread
– Magnitude
– Outliers
– Time trend
– Exposure and / or disease incubation period
Epi Curve: Pattern of Spread
The overall shape of the epi curve can
reveal the type of outbreak (the pattern of
spread)
• Common source
– Intermittent
– Continuous
– Point source
• Propagated
Common Source Outbreak
• People are exposed to a common harmful
source
• Period of exposure may be
– brief (point source)
– long (continuous) or
– intermittent
Epi Curve: Common Source Outbreak
with Point Source Exposure
Pattern of Spread
Epi Curve: Common Source Outbreak
with Continuous Exposure
Pattern of Spread
Epi Curve: Common Source Outbreak
with Intermittent Exposure
Pattern of Spread
Epi Curve: Propagated Outbreak
Pattern of Spread
Epidemic Curves: Magnitude of
the Outbreak
Magnitude
Epi Curves Provide Information
about the Time Trend of an Outbreak
Number of cases
• Date of illness onset for the first case
• Date when the outbreak peaked
• Date of illness onset for the last case
35
30
25
20
15
10
5
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Days
Clues from the Epi Curve
• Incubation period
– The time from the moment of exposure to an
infectious agent until signs and symptoms of
the disease appear
• Period of exposure
– Point source outbreak
– Timeframe during which the exposure likely
occurred
Using Epi Curves to Estimate the
Incubation Period
• Use when timing of exposure is known
and agent is unknown
• Estimated incubation period is between
– Time of suspected exposure
– Time of peak of epi curve
Using Epi Curves to Estimate
Period of Exposure
• Use when incubation period for the
disease is known
• Period of exposure is between
– Peak of epi curve counting back the average
incubation period
– Earliest case, counting back the minimum
incubation period
Calculating the Exposure Period
Centers for Disease Control.
Hepatitis–Alabama. MMWR
1972:21:439-444
Creating an Epidemic Curve
Number of
cases of
disease
reported during
an outbreak
plotted on the
y-axis
Cases of Disease X in Y Population, Nov-Dec 2012
Pre-epidemic
period included to
show the baseline
number of cases
Time or date of illness
onset plotted on the
x-axis
Creating an Epidemic Curve
Descriptive
title
Cases of Disease X in Y Population, Nov-Dec 2012
Axis labels
Epi Curve X-axis Units
• Depends upon the incubation period
• Begin with a unit one quarter the length of
the incubation period
Example:
1. Mean incubation period for influenza = 36
hours
2. 36 x ¼ = 9
3. Use 9-hour intervals on the x-axis for an
outbreak of influenza lasting several days
Epi Curve X-axis Units
• For an unknown incubation period
– Graph several epi curves with different time
units
– Choose units that best represent the data
• Units may range from hours to months,
depending on the outbreak duration and
known or suspected incubation period
10/1-10/7
10/8-10/14
10/15-10/21
10/22-10/28
Week of Onset
X-axis unit of time = 1 week
# of Cases
# of Cases
50
45
40
35
30
25
20
15
10
5
0
10
/2
/
10 201
/4 2
/2
1
10 0/ 012
/2 6/
2
1010 /20001
/4/8/ 22
/
1100/ 220001
1
/6 0 22
/
1100/ /20200
1
/8 122
101 /22/02
/01/1 0012
101 0/42/20 2
/01/ 0012
1
10 2/62/0 2
1/01 200
/
12
10 41/82/0 2
1/01 200
2
10 /62/020 12
1/01 /2002
10 /82/220 12
1/020 /2002
10 /2/20 12
4
1/022 /2002
/
10 /2 20 12
6
1/024 /2002
/
10 /2 20 1
/ 8 2
1026/ /2002
10 / 20 1
/2 30 022
/
10 8/2200
/3 0122
0/
20
02
# of Cases
Example
X-axis Considerations
10
9
8
7
6
5
4
3
2
1
0
10
9
8
7
6
5
4
3
2
1
0
Day of Onset
Day of Onset
X-axis unit of time = 1 day
Session Summary
• Outbreak
– The occurrence of more cases of disease than
expected for a given place and time
• Outbreak investigation
– Decision to investigate depends on several
factors
– Verification of the diagnosis allows for
identification of the incubation period and is
necessary to hypothesize about the exposure
– Case definition classifies case-patients related to
the outbreak and is used to conduct additional
case finding
Session Summary
• Descriptive epidemiology
– Characterizes the outbreak by time, place, and
person
– Is essential for hypothesis generation
• Measures of central tendency
– Assess distribution of data
– Include mean and median
• Epi curves, spot maps, and line listings are
ways to summarize time, place, and person
elements of descriptive statistics
References and Resources
• Centers for Disease Control and Prevention (1992). Principles of
Epidemiology, 2nd ed. Atlanta, GA: Public Health Practice Program
Office.
• Centers for Disease Control and Prevention. Outbreak of
Meningococcal Disease Associated with an Elementary School-Oklahoma, March 2010; MMWR April 6, 2012 / 61(13);217-221.
http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6113a1.htm?s_cid
=mm6113a1_w
• Centers for Disease Control and Prevention. Brainerd Diarrhea.
Division of Bacterial Disease; October 2006.
http://www.cdc.gov/ncidod/dbmd/diseaseinfo/brainerddiarrhea_g.ht
m
• FOCUS Workgroup. An Overview of Outbreak Investigations.
FOCUS on Field Epidemiology (1):1.
http://cphp.sph.unc.edu/focus/issuelist.htm
References and Resources
• FOCUS Workgroup. Anatomy and Physiology of an Outbreak
Investigation Team. FOCUS on Field Epidemiology (1):2.
http://cphp.sph.unc.edu/focus/issuelist.htm
• Hall, J.A., et al. Epidemiologic profiling: evaluating foodborne
outbreaks for which no pathogen was isolated by routine laboratory
testing: United States, 1982-9. Epidemiol Infect. 2001;127:381-7
• Nelson, A. Embarking on an Outbreak Investigation. FOCUS on
Field Epidemiology (1):3. http://cphp.sph.unc.edu/focus/issuelist.htm
• Torok, M. Case Finding and Line Listing: A Guide for Investigators
FOCUS on Field Epidemiology (1):4.
http://cphp.sph.unc.edu/focus/issuelist.htm
• Torok, M. Epidemic Curves. FOCUS on Field Epidemiology (1):5.
http://cphp.sph.unc.edu/focus/issuelist.htm