1. Introduction to epidemiology
HCAI Information for Action 2009
Introduction to epidemiology
Meirion Evans
Communicable Disease Surveillance Centre
Oct 2009

2. What is epidemiology?
The study of the distribution and determinants of health-related states or events in specified populations and the application of this study to control health problems.
(JM Last. Dictionary of Epidemiology)

3. Epidemiology & clinical medicine
“You’ve got whatever it is that’s going around”

4. Epidemiology & clinical medicine
Populations
Studies
Prevention
Evaluation
Planning
Individuals
Diagnosis
Treatment
Curing
Caring

5. The uses of epidemiology
Describe characteristics of disease
Help define and classify disease
Understand natural history of disease
Define health care needs & plan services
Analyse causes of disease
Determine aetiology & quantify individual risk
Identify opportunities for prevention
Evaluate prevention, treatment and care
Assess effectiveness and efficiency

6. Five essential questions

7. Methods Surveillance Outbreak investigations Observational studies
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Methods
Surveillance
Outbreak investigations
Observational studies
Case series
Case-control studies
Cohort studies
Experimental studies
RCTs

8. Purpose DESCRIBE SUMMARISE COMPARE INFER
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Purpose
DESCRIBE
Time, Place, Person (When, Where, Who)
SUMMARISE
Mean & SD
COMPARE
Odds ratios & Relative risks
INFER
Confidence intervals
Hypothesis testing

9. DESCRIBE - Time WHEN does the disease occur?
HCAI Information for Action 2009
DESCRIBE - Time WHEN does the disease occur?
Secular trends (long term)
Point epidemics (short term)
Cyclical change
Seasonal variation

10. Time - the epidemic curve
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Time - the epidemic curve
Figure 1. Cases of gastroenteritis (n=45) in Hospital X, Wales by date of onset, January and February 2009
1 patient case
1 staff case

11. Time - patterns of spread
cases
cases
Persistent source
Point source
days
days
cases
cases
Person to person transmission
Propagated source
weeks
days

12. Time - estimating time of exposure A community outbreak of hepatitis A15
50 days
one case
30 days
Number of cases 10 5
15 days 2 8 14 20 26 2 8 14 20 26 1 7
Exposure
Date of onset

13. Time trends MRSA cases before and after handwashing intervention
D Pittet, et al. Lancet 2000;356:

14. DESCRIBE - Place WHERE does the disease occur?
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DESCRIBE - Place WHERE does the disease occur?
In the community
Place of residence
Place of work
In hospital
Floor
Ward or unit
Operating theatre
Outpatient departments

15. The one-variabletable
Table 1. Cases of MRSA in Area X, 2009, by area of residence
HCAI Information for Action 2009
The one-variabletable

16. HCAI Information for Action 2009
The spot map
Figure 1. Cases of MRSA in Area X, 2009 by place of residence.
1 dot = 1 case

17. HCAI Information for Action 2009
The area map
Figure 2. Incidence rate (per 100,000) of MRSA in Area X, 2009 by area of residence.

18. Plan view of intensive therapy unit Shading indicates location of MRSA cases
Source:
J Hosp Infect 1996;32:

19. DESCRIBE - Person WHO is getting the disease?
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DESCRIBE - Person WHO is getting the disease?
Sex and age group
Ethnicity
Pre-existing conditions
Medication
Invasive procedures
Surgical treatment

20. The two-variable table
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The two-variable table
Area X, 2008

21. HCAI Information for Action 2009
Grouped bar chart
Area X, 2008

22. HCAI Information for Action 2009
Stacked bar chart
Area X, 2008

23. HCAI Information for Action 2009
Component bar chart
Area X, 2008

24. Source: DH Third prevalence survey of HCAI in England
Grouped bar chart
Figure. HCAI prevalence by age group and gender, England 2006
Source: DH Third prevalence survey of HCAI in England

25. SUMMARISING data Measures of centrality Mean Median Mode
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SUMMARISING data
Measures of centrality
Mean
sum of the data divided by no. of observations
Median
middle value (half above, half below)
Mode
most frequently observed value

26. Normal distribution curve
Score or measure
Total number of scores 9 8 7 6 5 4 3 2 1

27. Skewed distributions Positive or Right Skew Distribution
mean
median
mode
Positive or Right Skew Distribution
mean
median
mode
Negative or Left Skew Distribution

28. Skewed distributions Ratio of ICNs to total number of beds in NHS Trusts
Source: NAO report, 2004

29. SUMMARISING data Measures of variability (dispersion)
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SUMMARISING data
Measures of variability (dispersion)
Range (percentiles, interquartile range)
difference between largest and smallest value
Variance
how far each value differs from the mean
(square ea. difference, add results together, divide by no. of measurements minus one)
Standard deviation (SD)
square root of the variance

30. Different distributions
Small Standard Deviation
Large Standard Deviation
Different Means
Different Standard Deviations
Same Standard Deviations
Same Means

31. Range – percentiles Incidence of SSI by category of surgical procedure, 1997-2003
Source: NAO report, 2004

32. COMPARING data Comparing exposures in case and non-cases
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COMPARING data
Comparing exposures in case and non-cases
What are the risk factors for disease?
Cross-sectional studies
Cohort studies
Case-control studies

33. COMPARING data Relative risk (RR) cross-sectional and cohort studies
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COMPARING data
Measures of association:
Relative risk (RR)
cross-sectional and cohort studies
Odds ratio (OR)
case-control studies

34. The 2x2 table for a cohort study
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The 2x2 table for a cohort study
Incidence
ill
not ill
exposed
50 %
not exposed
40 %
Risk difference % % = 10%
Relative risk % / 40% =

35. The 2x2 table for a case-control study
HCAI Information for Action 2009
The 2x2 table for a case-control study
ill
not ill
exposed
not exposed
Odds
49/4
49/6
12.3
8.2
Odds ratio / 8.2 = 1.5

36. Table from a case control study Risk factors for MRSA bacteraemia
HCAI Information for Action 2009
Table from a case control study Risk factors for MRSA bacteraemia
Exposure
Cases n=42
Controls n=90
Odds Ratio
On admission
Indwelling catheter on admission 5 3
3.9
Prior admission 35 66
1.8
On or during admission
Bed sore 1
12.0
Skin ulcer
2.3
During admission
Central line during admission 17
60.5
Urinary catheter during admission 22 2
48.4
Blood transfusion 15 7
6.6

37. Making INFERENCES Estimation Hypothesis testing
HCAI Information for Action 2009
Making INFERENCES
Estimation
To describe population parameters using information obtained from samples
Point estimate e.g. sample mean
Interval estimate e.g. confidence interval
Hypothesis testing
To reject or accept a hypothesis by testing whether observed data is consistent with it

38. Description vs Inference
Graphical
Data tables
Bar graphs & pie charts
Numerical
Percentages
Averages
Range
Relationships
Correlation coefficient
Regression analysis
Inference
Confidence interval
Compare means of two samples
Pre/post scores
t test
Compare frequency in two groups
Risk factors
RR and OR

39. I am 95% confident that μ is between 40 & 60
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Making INFERENCES
Population
Random Sample
I am 95% confident that μ is between 40 & 60
Mean
x = 50
Mean μ is unknown
Sample

40. Interval estimation using a sample to estimate the population mean
Population distribution
Parameter B A
Sample distribution
Sample distribution
Interval estimate

41. Confidence Intervals +/- 1 SD +/- 2 SD +/- 3 SD 68% Samples
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Confidence Intervals
+/- 1 SD
68% Samples
+/- 2 SD
95% Samples
+/- 3 SD
99.7% Samples

42. Interval estimation Estimate popn mean from sample mean
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Interval estimation
Estimate popn mean from sample mean
Confidence interval
the range of values within which the true population mean (μ) will lie
95%CI = x +/- (1.96 x SEM)
x = sample mean
SEM = standard error of mean = SD/√n
SD = standard deviation, n = no. in sample

43. Prevalence of HCAI by infection type
Source: DH Third prevalence survey of HCAI in England

44. Prevalence of HCAI by infection type
Source: DH Third prevalence survey of HCAI in England