organizing and displaying epidemiologic data with tables and graphs

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  • Slide 1
  • Organizing and Displaying Epidemiologic Data with Tables and Graphs
  • Slide 2
  • 2 Displaying Data Learning Objectives Discuss the difference between tables and graphs for written reports versus oral presentations Create and interpret one and two variable tables Create and interpret a line graph Create and interpret an epidemic curve Create and interpret one and two variable bar charts Describe when to use each type of table, graph, and chart
  • Slide 3
  • 3 Displaying Data Can you summarize the age and sex of the case-patients at a glance? Case No. Date of OnsetAgeSex 121 Nov9M 2 39M 322 Nov29F
  • Slide 4
  • 4 Displaying Data Can you summarize the age and sex of the case-patients at a glance? Case No. Date of OnsetAgeSex 121 Nov9M 2 39M 322 Nov29F 421 Nov10M 522 Nov55F 622 Nov11M
  • Slide 5
  • 5 Displaying Data Can you summarize the age and sex of the case-patients at a glance? Case No.AgeSex 19M 239M 329F 410M 555F 611M 79M 87F 917M 10 M Case No.AgeSex 1110M 126M 139M 1440M 1540F 1610M 1711M 1843F 1971F 209F Case No.AgeSex 2138F 2234F 239M 2410M 256F 2611M 279M 2841M 296M 3011M Case No.AgeSex 3110M 3231F 338F 349M 3510F 3611M 3738M 11M 397M 4016F
  • Slide 6
  • 6 Displaying Data Basic Methods for Organizing and Presenting Data Data can be organized through creation of: Tables Graphs Charts
  • Slide 7
  • 7 Displaying Data Why organize and present data? To summarize when data set has too many records to look at individually To become familiar with the data before analysis, and to catch errors To look for (and display) Patterns Trends Relationships Exceptions / outliers To communicate findings to others
  • Slide 8
  • 8 Displaying Data Written vs. Oral Presentation Written Time unlimited Details OK White, grey and black Oral Time < 1 min Less detail Colors possible
  • Slide 9
  • 9 Displaying Data How to organize data Identify what data you have Use tables and graphs to summarize; catch errors; identify patterns, relationships Decide how best to summarize the data to communicate the findings Use tables and graphs to communicate the findings effectively
  • Slide 10
  • Tables
  • Slide 11
  • 11 Displaying Data Tables Data are arranged in rows and columns Quantitative information Usually, presents frequency of occurrence of some event or characteristic in different subgroups
  • Slide 12
  • 12 Displaying Data Tables Earthquake -related injury Other injuryTotal Male74259333 Female85151236 Unknown3912 Total162419581 Column Row Cell Clear, concise labels Row totals Column Totals Type of injury by sex, Port-au-Prince field hospital, Haiti, January 13 May 28, 2010 Descriptive Title (What, where, when) CDC. Post-earthquake injuries treated at a field hospital Haiti, 2010. MMWR 59:1673-1677. Footnote, source Unknown, if needed
  • Slide 13
  • 13 Displaying Data Types of Tables 1-variable table (frequency distribution) Range of values of a single variable Number of observations with each value 2-variable table Counts shown according to 2 variables at once 3-variable table Counts shown according to 3 variables at once Composite (combination) tables
  • Slide 14
  • 14 Displaying Data Example of 1-Variable Table Tuberculosis Cases by Sex, U.S., 2009 Sex# Cases Males6,990 Females4,544 Unknown11 Total11,545 Table 1. Number of Reported Cases of Tuberculosis, by Sex, United States, 2009 CDC. Reported Tuberculosis in the U.S., 2009. Atlanta: CDC, October 2010.
  • Slide 15
  • 15 Displaying Data Example of 1-Variable Table Tuberculosis Cases by Age, U.S., 2009 Age Group (years)# Cases 5401 5 14245 15 241,274 25 443,893 45 643,434 652,292 Unknown6 Total11,545 Table 2. Number of Reported Cases of Tuberculosis, by Age, United States, 2009 CDC. Reported Tuberculosis in the U.S., 2009. Atlanta: CDC, October 2010.
  • Slide 16
  • 16 Displaying Data Example of 1-Variable Table, with Percent Column CDC. Reported Tuberculosis in the U.S., 2009. Atlanta: CDC, October 2010. Age Group (years)# CasesPercent 54013.5% 5 142452.1% 15 241,27411.0% 25 443,89333.7% 45 643,43429.7% 652,29219.9% Unknown60.1% Total11,545100.0% Table 2. Number of Reported Cases of Tuberculosis, by Age, United States, 2009
  • Slide 17
  • 17 Displaying Data Age Group # CasesPercentCum Pct 54013.5%3.5% 5 142452.1%5.6% 15 241,27411.0%16.6% 25 443,89333.7%50.4% 45 643,43429.7%80.1% 652,29219.9%99.9% Unknown60.1%100.0% Total11,545100.0% Example of 1-variable Table, with Percent and Cumulative Percent Columns Table 2. Number of Reported Cases of Tuberculosis, by Age, United States, 2009 CDC. Reported Tuberculosis in the U.S., 2009. Atlanta: CDC, October 2010.
  • Slide 18
  • 18 Displaying Data Creating Categories Mutually exclusive, all inclusive Choices Standard categories for the disease Equal intervals Equal numbers within each group Include category for unknown values When analyzing data, begin with more categories, then collapse into a smaller number of categories for presentation
  • Slide 19
  • 19 Displaying Data Some Standard Categories in U.S. Notifiable DiseasesP&I mortality NCHS mortalityHIV/AIDS < 1 year 1-4 5-9 10-14 15-19 20-24 25-29 30-39 40-49 50-59 60 Not stated Total < 28 days 28 d 1 yr 1-14 15-24 25-44 45-64 65-74 75-84 85 Unknown Total < 1 year 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85 Not stated Total < 5 years 512 1314 1519 2024 2529 3034 3539 4044 4549 5054 5559 6064 65 Total
  • Slide 20
  • 20 Displaying Data Two-Variable Tables Shows counts according to two variables simultaneously Also called cross-tab or contingency tables
  • Slide 21
  • 21 Displaying Data Age Group FemalesMalesUnkTotal Example of Two-variable Table 51872140401 5 141191260245 15 2455971321,274 25 441,6412,24753,893 45 641,1532,27833,434 658821,40912,292 Unknown3306 Total4,5546,9901111,545 Table 3. Number of Reported Cases of Tuberculosis, by Age and Sex, United States, 2009 CDC. Reported Tuberculosis in the U.S., 2009. Atlanta: CDC, October 2010.
  • Slide 22
  • 22 Displaying Data Example of Two-by-Two Table Drank from stream near Campsite 6? IllWell Yes18422 No53944 234366
  • Slide 23
  • 23 Displaying Data Example of Two-by-Two Table Drank from stream near Campsite 6? IllWell Attack Rate (%) Yes1842281.8% No5394411.4% 234366
  • Slide 24
  • 24 Displaying Data Example of Three-variable Table FemalesMales Age groupU.S.OtherU.S.OtherTotal 51672018331401 51482377254245* 15241783772074991,274* 25444111,2156351,5913,893* 45644636691,1721,0803,434* 65+3655096317612,292* Total1,667*2,829*2,900*4,019*11,545* * Totals includes cases with missing age, sex, or birth country Table 3. Number of Reported Cases of Tuberculosis, by Age, Sex, and Birth Country, United States, 2009 CDC. Reported Tuberculosis in the U.S., 2009. Atlanta: CDC, October 2010.
  • Slide 25
  • 25 Displaying Data Composite (Combination) Tables Combines two or more 1-way or 2-way tables Uses limited space efficiently Well suited for written and oral presentations, but simple tables must be prepared first
  • Slide 26
  • 26 Displaying Data Composite Table Example Ortiz, Katz, Mahmoud, et al. J Infect Dis 2007;196:1685-1691
  • Slide 27
  • 27 Displaying Data Why Tables? When too many records, summarize in table (or graph) Allow you to identify, explore, understand, and present distributions, trends, relationships, variations, and exceptions in the data Tables serve as basis for graphs always create a table first!
  • Slide 28
  • 28 Displaying Data Some Tips for Creating Printed Tables Keep it simple Should be self-explanatory Title (what, where, when) with table number Label each row and column clearly and concisely Include units of measurement (years, mg/dl, etc.) Show totals for rows and columns Explain codes, abbreviations, symbols Note any exclusions in a footnote Note source in a footnote
  • Slide 29
  • Graphs
  • Slide 30
  • 30 Displaying Data Graphs Display quantitative data using a set of coordinates Rectangular graphs (x, y coordinates) most common x axis along bottom = method of classification, often time y axis along side = frequency, usually number, percent or rate
  • Slide 31
  • 31 Displaying Data Graphs: Advantages and Disadvantages Advantages Easy to understand and interpret Reveal patterns in data Useful for generating hypotheses Useful before formal data analysis Disadvantage Loss of detail
  • Slide 32
  • 32 Displaying Data Graph Types Arithmetic-scale line graph Histogram Many other types, not covered in this lecture Semilogarithmic-scale line graph Frequency polygon Cumulative frequency curve Survival curve Scatter diagram
  • Slide 33
  • 33 Displaying Data Arithmetic Scale Line Graph # Cases Intervals on x-axis are equal Intervals on y-axis are equal Start y-axis at 0; use scale breaks only if you must Useful to portray data collected over time
  • Slide 34
  • 34 Displaying Data Creating a Line Graph Make x-axis longer than y-axis (best ratio 5:3) X-axis: Match x-axis scale to intervals used during data collection Y-axis: Always