Basic Investigation of Outbreaks

Karin Galil, MD MPHCenters for Disease Control and Prevention

Atlanta, Georgia

Outline

Identify the outbreak Investigate the outbreak Interpret results Institute control measures Report results

Identify Potential Outbreaks

What is an outbreak ?

How can one detect outbreaks ?

Why should one look for outbreaks ?

Outbreak: Definition

An increase in the occurrence of a complication or disease above the background rate

One rare event e.g. GAS surgical site infection

Many episodes of common occurrence e.g. MRSA surgical site infections

Background Rate of Disease

Ongoing surveillance Determine rates—compare within and

between institutions Trends Requires common, accepted case

definitions

Retrospective review of data

Pitfalls in Rate Estimates Case definitions

Numerator Different definition increased or

decreased number

Population at risk Denominator Different definition increased or

decreased rate

Who Identifies Potential Outbreaks ?

Routine surveillance Infection control Registries

Clinical staff

Laboratory staff

Reasons to Investigate

Outbreak control

Increased knowledge Pathogen Risk factors for acquisition Transmission Epidemiology

Clusters that Suggest Nosocomial Transmission

Similar cases on one unit or among similar patients

Cases associated with invasive device HCW and patients with same infection Typical nosocomial pathogen

multiply-resistant opportunistic

Determining Risk Factors for Disease

Known risk factors in hospital-acquired infections: Invasive devices Severe illness or underlying disease

Environmental factors Especially immunocompromised patients

(e.g. aspergillosis)

Institute Control Measures

Immediate control measures needed even before investigation begun or completed

Simple: e.g. improved handwashing

Complex: cohorting patients, closing unit, halting use of device or product

Before the Investigation

Cooperation All involved personnel and administration

Laboratory capacity Antimicrobial susceptibility testing, typing

(molecular and nonmolecular methods) Resources

Personnel, supplies, lead investigator, statistician

The Investigation

Define “case” Find cases Confirm outbreak Review charts Describe epidemiology Generate hypothesis Test hypothesis Analyze data Communicate results

Case Definitions

“Working” case definition Person, place, time Clinical, laboratory or diagnostic findings Confirmed vs. possible cases

Case definitions usually change during the investigation

Example: Case Definition

“A case of multi-drug resistant tuberculosis was defined as any patient in Hospital X diagnosed with active tuberculosis from January 1, 1999

to December 31, 1999 whose isolate was resistant to at least isoniazid and rifampin.”

Case Finding

Use case definition to find other cases in the source population Large potential source population: discharge

diagnoses, microbiology log books, emergency room visits, use of diagnostic technique

Small population (unit of hospital): review charts of entire cohort

Line Listing

Name Age Sex Ward Onset Outcome

Confirm the Outbreak

Calculate background rate of disease

Compare rate during outbreak with background rate

Define periods from incubation timeto last case (or present)

Rate Ratio=

attack rate (outbreak period)attack rate (background period)

Pseudo-Outbreaks

Clusters of positive cultures in patients without evidence of disease

Perceived increase in infections New or enhanced surveillance Different laboratory methods

Descriptive Epidemiology

Line listing of case-patients (person, place, time) Demographic information Clinical information

Epidemic curve Point source Person-to-person

Point Source Outbreak

Shorter duration

Sharp peak in epidemic curve

Rapid resolution May resolve without intervention

Epidemic Curve:Point Source Outbreak

0

5

10

15

20

25

30

35

Day 1 Day 2 Day 3 Day 4 Day 5

Day of Onset

No.

of

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Epidemic Curve:Contaminated Product

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1995 1996

N=87

Bloodstream Infections and Pyrogenic ReactionsExtrinsic Contamination

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ases

Bloodstream infection Pyrogenic reaction

Person-to-Person or Contaminated Equipment

Poor infection control technique or contaminated patient equipment

Long duration May not resolve without intervention

If HCW and patients affected, plot separately and together to determine mode of transmission

Clues

Location Tb skin test conversion associated with

outpatient HIV clinicair flow

Patient characteristics Immunocompromised patients Persons of a certain age Persons with same disease/procedure

Hypotheses

What caused the outbreak ? Available data from the outbreak Published literature Expert opinion

Hypothesis testing

Epidemiologic Studies

Case-control studies Cases : disease Controls : equal likelihood of

exposure as cases

Cohort studies Cohort selected on the basis of

exposure status

Case-Control Study

Advantages: small number of cases, better for rare diseases, diseases with long latency periods, multiple exposures

Disadvantages: selection and recall bias, not good if exposure is rare, cannot measure disease incidence rate (OR vs. RR)

Cohort Study

Advantages: can study rare exposures, can calculate disease incidence rates, selection bias less likely

Disadvantages: feasibility, not suited to rare diseases

Collect Data

Complete: same data for cases and controls

Unbiased: same way to avoid bias

Potential Types of Bias

Selection bias Self-selection Diagnostic bias

Information bias Differential vs. misclassification Recall bias

Questionnaire

Design questionnaire Demographic information Potential risk factors Outcomes

Field test

Complete for on all patients

Enter and Clean Data

Line listing

Statistical program EpiInfo, SAS, STATA

Clean data Correct errors

Data Analysis

Descriptive statistics

Univariate analysis

Stratified analysis

Complex analysis

Descriptive Statistics

Vital first step Describe person, place, time Describe frequency of all

variables collected Look for errors Decide on further analyses

based on these results

.

a b a+b

c d c+d

a+c b+d N

Exp

osu

re Yes

No

Disease

Yes No

Risk Estimate

OR/RR >> 1 Strong positive association

OR/RR = 1 No association

OR/RR << 1 Strong negative association

Statistical Significance

Confidence Intervals Include 1 Exclude 1

P value p > 0.05 p << 0.05

Univariate Analysis:Categorical Variables

Categorical variables (yes/no; young/old)

Odds Ratio (OR) case-control study

Relative Risk (RR) cohort study

Odds Ratio

Case-control study

OR = odds that person with disease was exposed compared to odds that a person without disease was not exposed to risk factor

OR estimates the relative risk

Odds Ratio

OR = ad / bc

Odds Ratio

Disease No disease

Exposure 14 7 21

No exposure

5 8 13

19 15 34

Calculating the Odds Ratio

OR = ad / bc

OR = (14)(8) / (7)(5)OR = 3.2

Relative Risk

Cohort study

RR = risk ratio = incidence rate ratio = relative rate

RR = risk of disease among exposed compared to risk among the unexposed

Relative Risk

RR = a(c+d) / c(a+b)

Confidence Intervals

Sampling estimates the OR or RR

95% confidence Intervals—if we resampled numerous times, our estimate would fall within these bounds 95% of the time

Finite population correction

Statistical Tests for 2x2 Tables

Chi-square test

Fisher’s exact test—if value of any cell <5

P value indicates level of certainty that association was not due to chance alone

Risk Estimate vs. P Value

OR or RR –direction & strength of association >>1: strong association = 1 : no association <<1: strong inverse association

P Value—level of certainty about the estimate of the association <<.05: unlikely to be due to chance

Univariate Analysis: Continuous Variables

Continuous variables (e.g. age, bp) Distribution

Normal (bell-shaped)• Mean and standard deviation

Not normal• Median and range

Stratified Analysis

Simple stratified analysis Control for one variable

Logistic/linear regression models Control for multiple variables at once Control for confounding and effect

modification Non-linear relationships

Microbiologic Investigation

Alert lab: save all specimens + positive cultures

Typing of organisms Species identification Biotyping Antimicrobial susceptibility testing Advanced typing (serotyping, plasmid analysis,

phage typing, isoenzyme electrophoresis, genetic fingerprinting)

Environmental Investigation

Are inanimate objects linked with the outbreak ?

Were infections clustered in one area ?

Consider infected devices, medications/products, airflow patterns

Interpret Results

Is there an association ? It is statistically significant ? Was study biased ? Are the results plausible ? Did the exposure precede the outcome ? Are results consistent with other studies ? Is there a dose-response effect ?

Control the Outbreak

Routine infection control procedures Guidelines for universal precautions Specific guidelines for patient-care equipment

Specific interventions for the ongoing outbreak Clues—person, place, time

Evaluate Control Measures Did the control measures stop the outbreak?

Were there multiple modes of transmission ?

Were control measures implemented properly ?

Were control measures sufficient ?

Implement Successful Control Measures

Report Results

Inform all concerned parties of results Hospital staff, consultants, health department

Contaminated products/devices—government authorities, manufacturers

Media — spokesperson

Investigations are:

ChallengingTime - consumingImperfect