Tables, graphs, and diagrams Barbara Schimmer Jurmala, Latvia, 2006 Based on EPIET material

Tables, graphs, and diagrams

Barbara SchimmerJurmala, Latvia, 2006

EpidemiologyTra ining

Based on EPIET material

Contents

• Use of tables, graphs and graphics

• Graphics in descriptive epidemiology° describe

• Graphics in analytical epidemiology° compare

• Designing graphics

Background

Epidemiology

Purpose• Description

° Time° Place° Person

• Clinical features

• Comparison° Odds ratios° Relative risks

Methods• Surveillance• Outbreak

investigations• Other studies:

clinical epidemiologyfield trialsexperimental epidemiology

Use of data tables and graphics?

Process data

• Organisetriage,

cleaning

• Summariseaggregate

• Explore° trends° relationships° errors

Present data

• Communicate

• Paper• Poster• Screen

static animated

Paper vs. screen

Paper

• Time unlimited• Repetition• Details

notes?• White, grey and

black

Screen

• Time < 1 min• No repetition• Less details• Colours possible

Tables, graphics, and diagrams

• Self-explanatory

• Simple!

• Title

(what, who, where, when)

• Define abbreviations and symbols

• Note data exclusions

• Reference the source

Time

The epidemic curve 1

Figure 1. Reported cases of campylobacteriosis (n=45) in Svolvær, Norway, by

date of onset J anuary and February 1997.

10 = 1 primary case

= 1 secondary household case

5

22 23 24 25 26 27 28 29 30 31 1 2 3 4 5 6 7 8 9 10

J anuary February

The epidemic curve 2

• Histogram° Area proportional to number

° No space between columns

° One population

• X-axis = time° Start before epidemic, continue after

° Interval ≤1/4 of incubation period

• Y-axis = number of cases° Usually one square = one case

Easy to make in Excel

The arithmetic-scale line graph 1

Figure 2. Incidence rate of gonorrhoea and syphilis in Norway, 1975-1999

0

100

200

300

400

1975 1978 1981 1984 1987 1990 1993 1996 1999Year

Gonorrhoea

Syphilis

Cases per 100,000

Source: Folkehelsa

The arithmetic-scale line graph 2

• For time series

• Show actual changes in magnitude

• X-axis = time

• Y-axis = rate (or number) of cases° Start at 0

° Breaks possible, clearly marked

The semilogarithmic-scale line graph 1

Figure 3. Incidence rate of gonorrhoea and syphilis in Norway, 1975-1999

0,1

10

1000

1975 1978 1981 1984 1987 1990 1993 1996 1999Year

Gonorrhoea

Syphilis

Cases per 100,000

The semilogaritmic-scale line graph 2• For time series when

° interested in rate of change

• X-axis = time arithmetic

• Y-axis = rate (or number) of cases, logarithmic° Straight slope = constant rate of change

° Steep slope = constant rapid change

° Parallell lines = same rate of change

° Change in slope = acceleration deceleration of rate

° Start at lowest cycle, e.g. 0.1-1 or 1-10

° No breaks

In graphs...

• Labels for axes, scales and legends

• Legends or keys if >1 variable

• Scale divison, appropriate scale

• Units of measurements in title

• No grid, no numbers

• No 3D

Place

The one-variabletable

Table 4. Cases of meningococcal

disease in Dublin 1998 by area of

residence

Area

n %

1 2 5

2 1 3

3 2 5

4 2 5

5 8 22

6 7 19

7 10 27

8 2 5

9 2 5

10 1 3

Total 37 100

Cases

The spot map

8

67

12

34

5

910

Figure 1. Cases of meningococcal disease in Dublin 1998 by place of residence.

1 dot = 1 case

The area dot (or dot density) map

8

67

12

34

5

910

Figure 2. Cases of meningococcal disease in Dublin 1998 by area of residence.

1 dot = 1 case

The area map

8

67

12

34

5

910

Figure 3. Incidence rate (per 100,000) of meningococcal disease in Dublin 1998 by area of residence.

Person

The two-variable table

Table 1. Cases of Salmonella

Typhimurium-infection by age-group and sex,

Herøy, Norway, 1999

Age group Total

(years) Male Female

0 - 9 7 5 12

10 - 19 5 5 10

20 - 29 5 5 10

30 - 39 1 4 5

40 - 49 2 3 5

50 - 59 0 3 3

60 - 69 2 1 3

70 - 2 4 6

Total 24 30 54

Sex

Grouped bar chart

Figure 1. Cases of S Typhimurium-infection by age-group and sex, Herøy, Norway, 1999

0

2

4

6

8

0 - 9 10 - 19 20 - 29 30 - 39 40 - 49 50 - 59 60 - 69 70 -

Age-group

Male

Female

Number of cases

Stacked bar chartFigure 1. Cases of S Typhimurium-infection by age-group and sex, Herøy, Norway, 1999

0 2 4 6 8 10 12 14

0 - 9

10 - 19

20 - 29

30 - 39

40 - 49

50 - 59

60 - 69

70 -

Age-group

Number of cases

Male

Female

Component bar chartFigure 1. Cases of S Typhimurium-infection by age-group and sex, Herøy, Norway, 1999

0 %

20 %

40 %

60 %

80 %

100 %

0 - 9 10 - 19 20 - 29 30 - 39 40 - 49 50 - 59 60 - 69 70 -

Age-group

Male FemaleProportional distribution by sex

Bar charts

• Order° Natural

° Decreasing or increasing

• Vertical or horizontal

• Same width of bars

• Length = frequency

• Space between bars and groups, but not within groups

• Tables are often better

Pie chart

Figure 4. Cases of S Typhimurium-infection by age-group, Herøy, Norway, 1999.

21 %

19 %

19 %

9 %

9 %

6 %

6 %

11 % 0 - 9

10 - 19

20 - 29

30 - 39

40 - 49

50 - 59

60 - 69

70 -

Clinical features

TableTable 5. Clinical symptoms among 54 patients with S

Typhimurium-infection, Oslo, Norway, May 1998

Symptoms

n %

Diarrhoea 54 100

Fever 35 65

Headache 12 22

J oint pain 4 7

Muscle pain 4 7

Cases

Birth weight of 36217 newbornsDistribution of newborns by birth weight (2500-4500g)

0

200

400

600

800

1000

1200

2500

2550

2610

2660

2705

2750

2790

2824

2870

2920

2950

2990

3010

3042

3070

3102

3149

3190

3230

3265

3305

3350

3380

3410

3440

3460

3520

3560

3615

3655

3690

3740

3765

3810

3850

3900

3940

3980

4025

4055

4090

4150

4210

4237

4280

4340

4390

4440

4500

weight

co

un

t

Anything wrong with the distribution ?Distribution of newborns by birth weight (3300-3500g)

0

200

400

600

800

1000

1200

3300

3305

3310

3320

3330

3340

3345

3350

3355

3357

3360

3365

3370

3380

3385

3390

3395

3400

3401

3410

3415

3420

3430

3431

3434

3440

3441

3445

3449

3450

3455

3460

3470

3480

3490

3500

weight (g)

ca

se

s

Anything else than the relation ?Relation of birth weight and birth length

0

10

20

30

40

50

60

70

0 1000 2000 3000 4000 5000 6000

weight (g)

len

gth

(cm

)

Comparison

The 2x2 table for a cohort study

Table 5. Association between fish consumption and

gastrointestinal illness among customers at Uncle Mike's Fish &

Chips, Cambridge, October 1 2000

Ill Well Total Attack rate

Ate fish 42 16 58 0.72

Did not eat fish 5 59 64 0.078

Relative risk: 9.3 (95% confidence interval 3.9 - 22)

The 2x2 table for a case control study

Table 6. Association between fish consumption and

gastrointestinal illness among customers at Uncle Mike's Fish &

Chips, Cambridge, October 1 2000

Cases Controls Total

Ate fish 34 20 54

Did not eat fish 8 62 70

Total 42 82 124

Odds ratio: 13 (95% confidence interval 5.3 - 33)

Table from a case control study

Table 5. Association between exposures and campylobacteriosis in case-control

study, Oslo, Norway, 1998. Univariate, matched analysis.

Exposure Cases Controls Odds 95% conf.

ratio interval

Eaten at pizza restaurant 9/37 12/70 1.8 0.62 - 5.0

Eaten at party 10/36 9/74 3.2 0.97 - 11

Eaten foods from deli 23/37 42/74 1.2 0.56 - 2.7

Eaten unpeeled fruits 19/37 54/74 0.27 0.10 - 0.78

Close contact with a case 7/35 2/72 13 1.5 - 110

Drank >4 glas of water per day 21/37 33/74 1.7 0.73 - 3.9

Customer of water company B 27/37 33/74 4.0 1.3 - 7.3

Design

Think data-ink

Every bit of ink should have a reason

Designing graphics

• Show the data

• Use ink for the data

• Remove unnecessary ink

• Remove gimmicks

• No 3D

• Careful with colours

Standard symbols in tablesAvereage BMI by category of weight

weight men women

40-49  - .

50-59 19,8 21,8

60-69 23,1 24,8

70-79 25,0 27,6

80-89 27,4 30,5

90-99 29,8 34,2

explanation of symbols- = we measured, no case in this category, we can´t say that it is 0. = we measured, but we cant calculate the average of 1 case

Standard symbols in tables

Cause specific mortality

Cause of death men women

CVD 50 35

Pneumonia 45 30

CA prostatae 10 x

CA cervicis uteri x 10

explanation of symbolsx = not displayed for logical reasons

0102030405060708090

No.

of

case

s

B C Y W Unknown

Serogroup

Cases of meningococcal disease in Dublin by serogroup

Cases of meningococcal disease in Dublin by serogroup

0

10

20

30

40

50

60

70

80

90

B C Y W Unknown

Serogroup

No.

of

case

s

Cases of meningococcal disease in Dublin by serogroup

0

10

20

30

40

50

60

70

80

90

B C Y W Unknown

Serogroup

No.

of

case

s

Cases of meningococcal disease in Dublin by serogroup

0

20

40

60

80

B C Y W Unknown

Serogroup

No.

of

case

s

Summary

• Use of graphics Explore and present• Presentation Paper vs screen• Description

° Time - line graphs or epicurves° Place - maps or tables° Person - tables or bar charts° Clinical - tables

• Analysis° Comparison - 2x2 tables, other tables

• Design Save your ink!