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Cluster Investigations of Non-Infectious Health Events. Goals. Describe cluster investigations of non-infectious health events Discuss key factors which should be considered before carrying out a cluster investigation Outline the basic steps of a cluster investigation.

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  • Describe cluster investigations of non-infectious health events
  • Discuss key factors which should be considered before carrying out a cluster investigation
  • Outline the basic steps of a cluster investigation
cluster investigations of non infectious diseases
Cluster investigations of non-infectious diseases
  • Critical public health function
  • May link specific exposures to diseases
  • Example: Limb deformities in infants related to maternal use of thalidomide in Europe in 1960s (1)
    • Led to U.S. legislation requiring rigorous testing process for approval of new pharmaceutical products
non infectious disease cluster investigations may be difficult
Non-infectious disease cluster investigations may be difficult
  • Hard to confirm apparent geographic or temporal excess in case numbers
  • Supposed clusters may represent normal disease patterns
  • Confounding factors such as age
  • Different pathogenic processes may result in diseases that look alike but are not linked
    • Example—primary brain cancer vs. brain metastases spread from cancer in another organ
non infectious disease cluster investigations may be difficult6
Non-infectious disease cluster investigations may be difficult
  • Often impossible to establish a definitive cause-and-effect relationship
    • Small case numbers
    • Problems isolating single potential exposure
    • Difficulty in reconstructing exposure histories (2)
  • Large-scale epidemiologic studies may be required
    • Difficult to carry out
ensuring a successful investigation
Ensuring a successful investigation
  • Standardized step-wise process for receiving/evaluating cluster reports
    • Centralized tracking system, data collection tools, clear lines of communication
  • Well-trained staff and adequate resources
    • Experienced investigators, access to laboratories
  • Perceived problems must be addressed responsibly and sympathetically
    • Effective, credible communication with public and other agencies
to investigate or not
To investigate or not?
  • Investigating a link between exposure and disease may be impossible but it is important to respond to threats perceived by the public
  • Keep in mind:
    • Value of using a step-wise process with clear decision points
    • Share policy of using step-wise process with medical community, general public, media
    • Deliberate and transparent approach when carrying out any investigation
    • Recognize local concern but stay within stated investigation process
    • Develop effective methods of communication
basic steps in investigating non infectious disease clusters
Basic steps in investigating non-infectious disease clusters

Figure 1. Flowchart of cluster investigation

  • Each step in a cluster investigation requires:
    • Collecting and analyzing data
    • Decision to take immediate action (if needed)
    • Decision to proceed to next step or not (3)
step 1 initial ascertainment of cluster
Step 1: Initial ascertainment of cluster
  • Begin by collecting data:
    • Identifying information from person reporting the cluster
    • Demographic information for cluster cases
    • Clinical information on cluster cases
    • Identifying information for cluster cases
step 1 continued
Step 1—continued
  • Enter information collected into a tracking system
    • Example: EpiInfo, Microsoft Access or Excel
  • Notify health department staff, local health officers and appropriate agencies
  • Begin seeking information on disease causes and compare this information with the reported cluster
first decision point
First decision point
  • Based on initial information decide whether to continue the investigation
  • Criteria for continuing include:
    • Clinically similar health events without a plausible alternative etiology
    • Apparent excess occurrence of such health events
    • Plausible temporal association with the possible exposure(s)
    • A disease present in an demographic group where it is not usually found
    • One or more cases of a very rare disease
if investigation ends
If investigation ends
  • Create a brief summary report and share with person reporting cluster and health department supervisors
  • If investigation is halted, explain why to person reporting.
    • Example: variety in diagnoses (e.g., different types of cancers) argues against a common origin
step 2 assessment of excess occurrence
Step 2: Assessment of excess occurrence
  • Estimating excess occurrence
    • Confirm whether the number of cluster cases is greater than expected
    • Estimate an occurrence rate

Number of people with the health event

Total population at risk

    • Population at risk = all people in the geographic area where the exposure occurred over a designated time period
to estimate an occurrence rate
To estimate an occurrence rate
  • Select an appropriate geographic area and time period
    • Geographic area should include all persons at risk for the health event but not large enough to include those not at risk
    • Designated time period should be consistent with time period during which supposed exposure took place
  • Defining the geographic area and time period too narrowly or too broadly may over- or under-estimate problem
how size of geographic area affects occurrence rate
How size of geographic area affects occurrence rate

Figure 2. Finding the occurrence rate in the population at risk

  • Occurrence rate of 20% (left) vs. 8% (right)
determining cases and finding a reference population
Determining cases and finding a reference population
  • Determine which cases from the reported cluster to include in a preliminary analysis
  • Find a reference population comparable to the population in which the cluster appeared
    • Example—residents from a similar geographic area
  • Estimate an expected occurrence rate for the reference population from existing surveillance data
compare occurrence rates
Compare occurrence rates
  • Compare observed occurrence rate based on the cluster with the expected rate from the reference population
  • Use appropriate statistical tests to compare rates
    • 5 or more cases and appropriate denominator—Chi-square tests or Poisson regression
    • Small case numbers—group cases across geographic areas or time periods
case verification
Case Verification
  • Case definition should include clinical criteria and restrictions on time, place, and person
  • Sensitive case definition
    • Broad criteria, may include several related diseases or health events, captures more true cases but includes false positives
  • Specific case definition
    • Narrow criteria, focuses on one health event, uses confirmatory testing, excludes true cases (false negatives)
  • Example—cluster of cancer cases linked to benzene exposure
    • Sensitive case definition = diagnosis of any form of blood cancer
    • Specific case definition = diagnosis of leukemia
using multiple case definitions
Using multiple case definitions
  • Example – investigation of childhood cancer cases in Dover Township and Toms River, NJ, 1995 (4)
  • Industrial pollutants released into Toms River contaminated Dover’s municipal well
  • Investigation of all childhood cancers and subgroups of selected cancers
childhood cancer cases in new jersey 1995 4
Childhood cancer cases in New Jersey, 1995 (4)
  • Observed and expected occurrence rates compared by calculating standardized incidence ratios and 95% confidence intervals
  • SIR = observed cases (or rate)

expected cases (or rate)

where = 1 no excess occurrence > 1 possible excess occurrence < 1 observed is less than expected

childhood cancer cases in new jersey 1995
Childhood cancer cases in New Jersey, 1995
  • Table 2. Childhood cancer incidence in Toms River census tracts, 1979-1995, children 0-4 years
case verification23
  • Examine case-patients’ medical records
  • Refer to relevant health registries
  • Obtain copies of relevant laboratory, pathology, or other reports
  • Obtain clinical/laboratory re-evaluations (e.g. retest biopsy or other specimens)
  • May need to do additional case-finding
case finding
  • In an expanded assessment:
    • Reconsider initial case definition
    • Reassess geographic/time boundaries
    • Ascertain all potential cases within geographic and time boundaries
    • Identify appropriate database sources
    • Perform literature review
    • Assess likelihood that clustered events are related to supposed exposure(s)
case finding25
  • Review additional data sources or medical records
    • Formal surveys of the community reserved for later stages in the investigation
  • If excess occurrence of disease confirmed with evidence of association with supposed exposure, consider etiologic study
  • If excess occurrence not confirmed or confirmed with no plausible relationship to supposed exposure, conclude investigation
step 3 determining the feasibility of an etiologic study
Step 3: Determining the feasibility of an etiologic study
  • First, determine epidemiologic and logistical feasibility of an etiologic study
  • Construct a testable hypothesis
    • Clearly state hypothesis
    • Include the target population, health event(s) and exposure(s) of interest
determining feasibility
Determining feasibility
  • Pros and cons of different study designs
  • Potential challenges and ways to address them
  • Potential for finding additional cases, expanding the case definition and changing the time/geographic periods
  • Collecting additional data and associated costs
etiologic study measuring exposure
Etiologic study—measuring exposure
  • Do clinical or environmental tests for the exposure exist?
    • How sensitive are they?
    • Given the lapse of time since exposure will the test be useful?
  • Is the reported exposure history a good predictor of true exposure?
determining study benefits
Determining study benefits
  • May be difficult to determine whether an etiologic study will justify the effort
  • Etiologic studies may not be successful unless disease is rare or frequency has suddenly increased
  • Etiologic agent must be measurable and leave a physiologic response
  • Appropriate unexposed control group is needed—levels of exposure must vary within population to carry out study (6)
assess study implications
Assess study implications
  • Consider epidemiologic and policy implications
  • Consider community reactions
  • If etiologic study is feasible and likely benefits justify the effort, carry out study
  • If etiologic study is logistically impossible, too expensive or will not affect policies or programs, end investigation
step 4 conducting an etiologic investigation
Step 4: Conducting an etiologic investigation
  • Etiologic study should generate knowledge about broader epidemiologic and public health issues raised
  • Begin by writing a formal study protocol
  • Lay out steps in data collection, processing, quality assurance and data analysis
  • Further study design decisions will be unique to the particular study
  • Cluster investigations allow public health officials to interact with the community and be responsive to public needs
  • May provide information about previously unsuspected exposure-disease relationships
  • Can be an unproductive drain on public health resources

1. Lenz W. Kindliche mißbildungen nach medikament-einnahme während der gravidat [Malformations in children after a drug taken during pregnancy]. Dtsch Med Wochenschr. 1961;86:2555–2556.

2. Cartwright RA. Cluster investigations: Are they worth it? Med J Aust. 1999;171(4):172. 171_4_160899/cartwright/cartwright.html. Accessed August 13, 2008.

3. CDC. Guidelines for investigating clusters of health events. MMWR Morb Mortal Wkly Rep. 1990;39(RR-11):1-16. Accessed August 13, 2008.

4. New Jersey Department of Health and Senior Services and ATSDR. Childhood Cancer Incidence Health Consultation: A Review and Analysis of Cancer Registry Data, 1979-1995, for Dover Township (Ocean County), New Jersey. 1997. Accessed August 13, 2008.


5. Bender AP, Williams AN, Johnson RA, Jagger HG. Appropriate public health responses to clusters: The art of being responsibly responsive. Am J Epidemiol. 1990;132:S48-S52.

6. Rothman KJ. A sobering start for the cluster busters’ conference. Am J Epidemiol 1990;132:S6-S13.

7. Fischoff B, Lichtenstein S, Slovic P, et al. Acceptable Risk. Cambridge, UK: Cambridge Univ Press; 1981.

8. Greenberg MR, Wartenberg D. Understanding mass media coverage of disease clusters. Am J Epidemiol. 1990;132:S192-5.

9. Covello VT, Allen F. Seven Cardinal Rules of Risk Communication. Washington, DC: US Environmental Protection Agency, Office of Policy Analysis; 1988. OPA publication 87-020.