1 / 60

Basic Investigation of Outbreaks

Basic Investigation of Outbreaks. Karin Galil, MD MPH Centers 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 ?

amalian
Download Presentation

Basic Investigation of Outbreaks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Basic Investigation of Outbreaks Karin Galil, MD MPH Centers for Disease Control and Prevention Atlanta, Georgia

  2. Outline • Identify the outbreak • Investigate the outbreak • Interpret results • Institute control measures • Report results

  3. Identify Potential Outbreaks • What is an outbreak ? • How can one detect outbreaks ? • Why should one look for outbreaks ?

  4. 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

  5. Background Rate of Disease • Ongoing surveillance • Determine rates—compare within and between institutions • Trends • Requires common, accepted case definitions • Retrospective review of data

  6. Pitfalls in Rate Estimates • Case definitions • Numerator • Different definition increased or decreased number • Population at risk • Denominator • Different definition increased or decreased rate

  7. Who Identifies Potential Outbreaks ? • Routine surveillance • Infection control • Registries • Clinical staff • Laboratory staff

  8. Reasons to Investigate • Outbreak control • Increased knowledge • Pathogen • Risk factors for acquisition • Transmission • Epidemiology

  9. 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

  10. 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)

  11. 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

  12. 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

  13. The Investigation • Define “case” • Find cases • Confirm outbreak • Review charts • Describe epidemiology • Generate hypothesis • Test hypothesis • Analyze data • Communicate results

  14. Case Definitions • “Working” case definition • Person, place, time • Clinical, laboratory or diagnostic findings • Confirmed vs. possible cases • Case definitions usually change during the investigation

  15. 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.”

  16. 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

  17. Line Listing

  18. Confirm the Outbreak • Calculate background rate of disease • Compare rate during outbreak with background rate • Define periods from incubation timeto last case (or present)

  19. Rate Ratio=attack rate (outbreak period)attack rate (background period)

  20. Pseudo-Outbreaks • Clusters of positive cultures in patients without evidence of disease • Perceived increase in infections • New or enhanced surveillance • Different laboratory methods

  21. Descriptive Epidemiology • Line listing of case-patients (person, place, time) • Demographic information • Clinical information • Epidemic curve • Point source • Person-to-person

  22. Point Source Outbreak • Shorter duration • Sharp peak in epidemic curve • Rapid resolution • May resolve without intervention

  23. Epidemic Curve:PointSource Outbreak

  24. Epidemic Curve:Contaminated Product N=87 Number of persons with abscess 1995 1996

  25. Bloodstream infection Pyrogenic reaction Bloodstream Infections and Pyrogenic ReactionsExtrinsic Contamination

  26. 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

  27. Clues • Location • Tb skin test conversion associated with outpatient HIV clinicair flow • Patient characteristics • Immunocompromised patients • Persons of a certain age • Persons with same disease/procedure

  28. Hypotheses • What caused the outbreak ? • Available data from the outbreak • Published literature • Expert opinion • Hypothesis testing

  29. Epidemiologic Studies • Case-control studies • Cases : disease • Controls : equal likelihood of exposure as cases • Cohort studies • Cohort selected on the basis of exposure status

  30. 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)

  31. Cohort Study • Advantages: can study rare exposures, can calculate disease incidence rates, selection bias less likely • Disadvantages: feasibility, not suited to rare diseases

  32. Collect Data • Complete: same data for cases and controls • Unbiased: same way to avoid bias

  33. Potential Types of Bias • Selection bias • Self-selection • Diagnostic bias • Information bias • Differential vs. misclassification • Recall bias

  34. Questionnaire • Design questionnaire • Demographic information • Potential risk factors • Outcomes • Field test • Complete for on all patients

  35. Enter and Clean Data • Line listing • Statistical program • EpiInfo, SAS, STATA • Clean data • Correct errors

  36. Data Analysis • Descriptive statistics • Univariate analysis • Stratified analysis • Complex analysis

  37. Descriptive Statistics • Vital first step • Describe person, place, time • Describe frequency of all variables collected • Look for errors • Decide on further analysesbased on these results

  38. Disease . Yes No Yes Exposure No

  39. Risk Estimate • OR/RR >> 1 • Strong positive association • OR/RR = 1 • No association • OR/RR << 1 • Strong negative association

  40. Statistical Significance • Confidence Intervals • Include 1 • Exclude 1 • P value • p > 0.05 • p << 0.05

  41. Univariate Analysis:Categorical Variables • Categorical variables (yes/no; young/old) • Odds Ratio (OR)  case-control study • Relative Risk (RR)  cohort study

  42. 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

  43. Odds RatioOR = ad / bc

  44. Odds Ratio

  45. Calculating the Odds RatioOR = ad / bcOR = (14)(8) / (7)(5)OR = 3.2

  46. Relative Risk • Cohort study • RR = risk ratio = incidence rate ratio = relative rate • RR = risk of disease among exposed compared to risk among the unexposed

  47. Relative RiskRR = a(c+d) / c(a+b)

  48. 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

  49. 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

  50. 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

More Related