1. Data presentation Tables, graphs and maps Integrated Disease Surveillance Programme (IDSP) district surveillance officers (DSO) course

2. 2 Outline of the session 1.Analogical versus digital information 2.Tables 3.Graphs 4.Maps

3. 3 Communicating quantitative information Analogical communication: Graphs  Less precise  More graphic  Provides overall understanding Digital communication: Tables  Precise  Numeric  Provides detailed and exact description 7:00 am Digital and analogical information

4. 4 Number of cases Month of onset Cases of monkeypox by month of onset, Katako-Kombe, Zaire, 1996-1997 0 5 10 15 20 25 30 FebMarAprMayJun 1996 JulAugSepOctNovDecJan 1997 Feb Secondary cases Primary cases Example: Analogical display of information (Graph) WHO-CDC Digital and analogical information

5. 5 Cases of Monkeypox by month of onset, Katako-Kombe, Zaire, 1996-1997 Example: Digital display of information (Table) Digital and analogical information

6. 6 Tables Presentation of detailed analyzed data Do not present raw data  E.g., lists Present analyzed data with summary statistics Tables

7. 7 Column headings Data Footnotes Title Row headings Typical table layout with components

8. 8 Tables How to make sure that the cells of the table are understandable without referral to other material Title  Time, Place and Person information  Any measurement found in all columns Row and column headings  Content of the row or column  Any modifier applied to all cells of a row or column  Unit of measurement (Abbreviations, if necessary) Footnotes  Clarify potential ambiguities  Explain abbreviations, symbols, codes  Note exclusions  Mention data source

9. 9 Selected suggestions for data arrangement in tables 1.Summarize rows and columns 2.Compare numbers in columns 3.Arrange key data by magnitude 4.Align numbers by decimal Tables

10. 10 YearMF Both Sexes 197350099600 197058087670 196846089550 196626071330 Mean43086520 Summary of the columns Summary of the rows 1. Summarize rows and columns Summarize rows and columns with totals, averages or other statistics Tables

11. 11 Compare numbers in columns 23 42 34 109 87 42 27 98 114 75 Difficult to compare numbers in rows 23 42 34 109 87 42 27 98 114 75 1st improvement: Right-justify numbers vertically 23 27 34 42 75 87 98 109 114 2nd improvement: Sort numbers 2. Compare numbers in columns Tables

12. 12 Organize data by magnitude Exposure Cases (1000s)Rate A112.9 B069.9 C345.4 None272.3 3. Arrange key data by magnitude Tables Which is the most important column you would use to sort the table? Exposure Cases (1000s)Rate B69.9 C345.4 A112.9 None272.3

13. 13 Align columns by decimal 23 42 34 10.9 8.7 42 27 9.8 114 75 23.0 42.0 34.0 10.9 8.7 42.0 27.0 9.8 114.0 75.0 Difficult to compare numbers in rows Keeping the zeros or not is a question of personal style 4. Align numbers by decimal Tables

14. 14 Age distribution of a sample of 100 villagers Example of one way table: Data tabulated by one variable Age group (years)Number 0-419 5-1425 15-4440 45+16 Total100 Tables

15. 15 Example of two way table: Data tabulated by two variable Age group (years)MaleFemaleNumber 0-410919 5-14121325 15-4420 40 45+7916 Total4951100 Age and sex distribution of a sample of 100 villagers Tables

16. 16 Incidence of cholera by age and sex, Kachua, West Bengal, India, 2004 PopulationCases Incidence per thousand Age group (years) 0-412915116 5-142101886 15-293831334 30-44334824 45-5915916 60+9900 Sex Male6662842 Female6482742 Total1,3145542 Classical table of incidence by age and sex

17. 17 Use one graph to get one general idea across Don’t use a graph if there is nothing to say Frame the idea to communicate Identify the graph that matches this idea Eliminate unnecessary information If there are two ideas, use two graphs Add a title with time, place and person information Graphs

18. 18 Proportion of eligible patients whose blood slides were examined for malaria, Dhenkanal district, Orissa, 1996-2002 0 2 4 6 8 10 12 14 16 1996199719981999200020012002 Years Proportion (%) Is the graph useful? Graphs

19. 19 Keep the ink-to-data ratio low All elements on a graph must be justified Eliminate distracting, non-essential elements  Secondary axis  Gridlines  3-D effects  Bordering lines  Etc… Graphs

20. 20 Dracunculiasis rates, India, 1984-2000 (High ink to data ratio) Graphs 1984 1986 1988 1990 1992 1994 1996 1998 2000 39792 30950 23070 17031 12023 7881 4798 2185 1081 755 371 60 9 0 0 0 0 0 5000 10000 15000 20000 25000 30000 35000 40000 Number of cases Year

21. 21 Dracunculiasis rates, India, 1984-2000 (Simpler, better, low ink-to-data ratio) Graphs 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 19841985198619871988198919901991199219931994199519961997199819992000 Year Number of cases

22. 22 Choosing a type of graph Graphs

23. 23 Malaria in Kurseong block, Darjeeling District, West Bengal, India, 2000-2004 20002001200220032004 Months Incidence of malaria per 10,000 Incidence of malaria Incidence of Pf malaria Line graph for time series Graphs

24. 24 Histogram to display a frequency distribution Graphic representation of the frequency distribution of a continuous variable Rectangles drawn in such a way that their bases lie on a linear scale representing different intervals Areas are proportional to the frequencies of the values within each of the intervals No spaces between columns No scale breaks Equal class intervals Epidemic curve is an example of histogram with time on the x axis Graphs

25. 25 0 20 40 60 80 0-19.920-49.950-99.9100-300> 300 Urinary Iodine Excretion levels (µg/L) Percentage Histogram Urinary iodine excretion status, 24 N Parganas, West Bengal, India, 2004 Graphs

26. 26 Acute hepatitis by week of onset in 3 villages, Bhimtal block, Uttaranchal, India, July 2005 0 10 20 30 40 50 60 70 80 90 1st week 2nd week 3rd week 4th week 1st week 2nd week 3rd week 4th week 1st week 2nd week 3rd week4th week 1st week 2nd week 3rd week4th week 1st week MayJuneJulyAugustSeptember Week of onset Number of cases Epidemic curve Graphs

27. 27 Proportions of a total presenting selected characteristics Breakdown of a total in proportions:  Pie chart Breakdown of more than one total into proportion:  Juxtaposed bar charts cumulated to 100% Graphs

28. 28 Road 10% Fall 32% Bites 16% Burns 7% Minor injuries 35% Types of unintentional injuries, Tiruchirappalli, Tamil Nadu, India, 2003 Incidence: 9.6 per 100 person-month (95% C.I. 8-11 Pie chart for the breakdown of a total in proportions Graphs

29. 29 Estimated and projected proportion of deaths due to non-communicable diseases, India, 1990-2010 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 199020002010 Year Proportion (%) Injuries Communicable diseases Non communicable diseases Cumulated bar chart for the breakdown of more than one total in proportions Graphs

30. 30 Comparing proportions No logical order: Horizontal bar chart  Sort according to decreasing proportions Logical order: Vertical bar chart Graphs

31. 31 Causes of non vaccination as reported by the mothers, Bubaneshwar, Orissa, India, 2003 0%20%40%60%80%100% Lack of money Lack of facility Lack of time Lack of motivation Irregularity by health staff Child sick Lack of awareness India FETP Horizontal bar chart Graphs

32. 32 0 10 20 30 40 50 60 70 30-3940-4950-5960-6970 + Age group (years) % Male Female Prevalence of hypertension by age and sex, Aizawl, Mizoram, India, 2003 Vertical bar chart Graphs

33. 33 Maps Use maps to display information by place  Do not use tables! Two types of maps:  Spot maps  Incidence maps Use a key Add a title with time, place and person information Maps

34. 34 Drawing a spot map during an outbreak investigation Rough sketch of the setting of an outbreak One dot = One case Other locations of potential importance are also recorded Does not adjust for population density Maps

35. 35 Cholera cases by residence, Kanchrapara, N-24 Parganas, West Bengal, India, 2004 Spot map - Does not adjust for population density Maps

36. 36 An incidence map adjusts for population density List the cases Regroup cases by location for which population denominator is available  Look up census data Divide the number of cases by the population denominator Choose gradients of colours to represent increasing levels of prevalence Maps

37. 37 Cholera attack rate and water supply, Sirunavalur, Tamil Nadu, India, 2002 Centre east Valluvar | street Main road PL street Reddiar street MuthurajaColony 0-5% 5 –10 % > 10 % Attack rate by area Old well used only in the summer Water tank filled with well water Main road Incidence map - Adjusts for population density Maps

38. 38 Preparing an incidence rate map: What you will need A hardcopy of your map A transparency Cello tape Permanent markers Computer Drawing software Incidence by geographical area

39. 39 Step 1: Place transparency on the hardcopy of map to draw map with permanent marker

40. 40 Step 2: Stick the transparency on the screen with cello tape and follow the guide to draw map with the mouse in a drawing software

41. 41 Step 3: Remove the transparency and edit the map in the drawing software

42. 42 Step 4: Filling the map with data Have a table of incidence by area Rank the areas by increasing level of incidence Sort the areas in four groups in which there is about the same number of area  Add a fifth group if needed for incidence = 0 Assign a colour per group Draw the map

43. Rate of disease X by country, South East Asia WHO region, 200X Yearly incidence per 100,000 0 0-19 20-49 50-99 100+

44. 44 Using colours in maps The cold / warm scale  Represents violent contrasts Increasing density in one colour  Represents increasing levels of magnitude Complementary colours  Use equivalent intensity  Represents unrelated notions Maps

45. 45 Take home messages 1.Choose whether you want to represent an overall message (Analogical) or whether you want to describe detailed data (digital) 2.Present analyzed data in tables with summary rows and columns 3.Display general ideas in graphs that carry one single message 4.Use maps to display information by place