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Effective graphs and maps

Effective graphs and maps

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Effective graphs and maps

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  1. Effective graphs and maps The visual display of quantitative and geographical information EPIET/EUPHEM introductory course Chris Williams, Adapted from slides Y. Hutin

  2. Communicating quantitative information • Analogue communication (graphs, maps) • Graphic overview • “hand waving” • Less precise • Digital communication (e.g. Tables) • Precise • Numeric (text also?) • Provides detailed and exact description 7:00 am Digital and analogical information

  3. Table, graph or map?(or none of the above)

  4. Vaccine coverage in Yamoussoukro district, Ivory Coast, 1995 The exact % does not add anything and may be distracting Digital and analogical information EPIGEPS course of field epidemiology

  5. Graphs: Key areas • What is the message? • Note the singular • Choose the right graph for the right data, that demonstrates the message clearly • Style and etiquette • Message:ink ratio

  6. Decide on a message • 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 slides Framing the message

  7. No clear messageSymptom surveillance by region

  8. Two messages- too many?Weekly norovirus tests by result

  9. One message- varying proportion positive

  10. Choosing the right graph

  11. Frequency distribution • Histogram • 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 • Epidemic curve is an example of histogram Analog information

  12. Histogram Urinary iodine excretion status, 24 N Parganas, West Bengal, India, 2004 80 60 40 Percentage 20 0 0-19.9 20-49.9 50-99.9 100-300 > 300 Urinary Iodine Excretion levels (µg/L)

  13. Epicurve: gastroenteritis at a music festival

  14. COLD/FLU CALLS:Daily ‘cold/flu’ calls as a proportion of total calls (7-day moving average) by region(2011- 2012). Presentation of time series data

  15. Proportions of a total presenting selected characteristics • Breakdown of a total in proportions: • Pie chart • Breakdown of more than one total into proportion: • Stacked bar charts adding to 100% Analog information

  16. Respiratory virus isolates by type: Pie chart

  17. Cumulated bar chart for the breakdown of many totals in proportions Estimated and projected proportion of deaths due to non-communicable diseases, India, 1990-2010 100% 90% 80% Injuries 70% 60% Communicable Proportion (%) 50% diseases 40% Non communicable 30% diseases 20% 10% Alignment allows comparing proportions across groups 0% 1990 2000 2010 Year

  18. Comparing proportions across groups • No logical order: Horizontal bar chart • Sort according to decreasing proportions • Logical order: Vertical bar chart • Not a continuous variable : Do not display axis • Continuous variable: Display axis Analog information

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

  20. Vertical bar chart: Gradient, but not quantified (No x axis) Maternal education of mothers, vaccine coverage survey, Yamoussoukro, Ivory Cost, 1995 70 60 50 40 Frequency (%) 30 20 10 0 None Prim Sec Sup Level of education Analog information EPIGEPS course of field epidemiology

  21. Prevalence of hypertension by age and sex, Aizawl, Mizoram, India, 2003 6 0 5 0 4 0 3 0 % 2 0 1 0 0 3 0 - 3 9 4 0 - 4 9 5 0 - 5 9 6 0 - 6 9 7 0 + A g e g r o u p ( y e a r s ) Vertical bar chart: Quantified gradient (x Axis)

  22. Deciding the type of graph that is needed (for reference)

  23. Putting it on the map:using maps in epidemiology

  24. Learning objectives Understand the principles of mapping Understand maps of counts and rates Understand how maps can generate hypotheses How to create maps

  25. Two basic tips • Maps in background • Include if location is relevant to your key message • Politics • Some maps/borders/ comparisons are sensitive

  26. Using maps in field epidemiology • Principals of case mapping – spot/count and population-adjusted maps • Using maps to generate hypotheses • Practical and analytic aspects of maps

  27. First, catch your hare • Where are the cases? • What do we mean by “where” • Once we know where they are, we can: • Go back to them for case management/investigation • Create a map to generate hypotheses or convey a message

  28. Geolocation

  29. Choosing a geo-locator • Cases are people (or animals!) • People move around • Options: • Place of residence (temporary residence) • Place of work or study • Healthcare provider location • Bed/room? • Merging into exposure locations e.g. Pools, water sources • Note time also – location when?

  30. General points on mapping • Two types of maps: • Spot maps • Incidence maps • Use a key • Add a title with time, place and person information Field epi map

  31. Techniques for mapping • Pen and paper • Drawing packages (including Excel) • Transparency method • Simple mapping- EpiMap, HPZone • GIS packages- ArcView, MapInfo • Can generate derived geographical variables

  32. Geographic information system (GIS) • A database linked to geographical information • Location obtained: • Directly via GPS devices or similar • Indirectly from information on address/GP/lab • Can serve as case database • Also can generate maps and test hypotheses GPS

  33. 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 (OK in small places) Field epi map

  34. Using simple packages for maps: Excel

  35. Spot map: ornithosis cases by place of residence, East of England 2008, n=3

  36. Spot map: ornithosis cases by place of residence, East of England 2008 (n=10)

  37. Spot map: ornithosis cases by place of work, East of England 2008 (n=10)

  38. 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 incidence Field epi map

  39. Incidence mapInvasive meningococal disease, East of England

  40. 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 Tips

  41. Generating hypotheses • Brainstorm likely geographical links • Map cases plus other relevant features • Water sources • Roads • Cooling towers • Can also map epidemiological indicators by area • Type of ground • Deprivation • Prevalence of another infection/disease

  42. Mapping an area exposure/determinant

  43. Q fever: incidence and spot map

  44. Take home messages • Know how to obtain geolocator information and link to cases • Use spot maps and incidence maps to generate hypotheses • Adjust for population size with rates when needed • Communicate efficiently the spatial distribution of health information • Practice map preparation to produce them rapidly when needed in practice

  45. Graph exercise: reported reasons for not swimming at Lazareto (% responses)

  46. Questions • Message • Graph type • Style

  47. First attempt: Select, Insert graph

  48. Message: comparing proportions of responses

  49. Type: Bar chart showing proportion by category

  50. Style: reduce unnecessary ink