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Using Epidemiology for Data-Driven Decision-Making in Tuberculosis Programs February 24, 2016

Visualization to Enhance Data Impact 1

Visualization to Enhance

Data Impact

Cynthia Driver, DrPH

Deputy Director

Public Health Programs

• 20 countries and cities

• 3 components

– Civil registration and vital statistics

– Mobile phone survey of NCD risk factors

– Data Impact Program

Data for Health Initiative

Goal: Data-driven Policymaking

Management

Collection

Data-driven

Policymaking

Demand

for data

Analysis

Communication



• Difficult to turn data into clear, succinct

communications products that advance

policy

• Challenges in both directions:

– Technical experts—articulating importance of

data to lay audiences

– Decision-makers—incorporating data into

communications products

Challenge

Scenario

• Advocate for additional funds to expand

TB program services in a neighborhood

with high TB rate

• Stakeholders

– Health department decision-makers

– Community partners

Data from: NYC DOHMH Bureau of Tuberculosis Control, Annual Summary 2014

You have data…now what? Tuberculosis Rates by Neighborhood, Brooklyn, NYC, 2014

Neighborhood Rate per 100,000

Bedford Stuyvesant-Crown Heights 6.5

Williamsburg-Bushwick 4.7

East Flatbush-Flatbush 9.6

Downtown-Brooklyn Heights-Park 2.6

Sunset Park 23.1

Coney Island 6.9

East New York 4.8

Borough Park 10.3

Bensonhurst- Bay Ridge 7.7

Greenpoint 1.5

Canarsie-Flatland 5.0

Brooklyn 7.4

City-Wide 7.2



Why Visualize?

• Data findings more readily apparent in visual

images

• Easier to grasp meaning of data points in

graphical or pictorial format

• Visualize to:

- understand what the data are saying

- communicate efficiently to others

- support good decision-making

A Data Visualization…

… conveys meaningful and memorable

insights through graphical representation

of data

0

5

10

15

20

25

Rat

e p

er

10

0,0

00

TB Rates by Neighborhood, Brooklyn, NYC, 2014

Data from: NYC DOHMH Bureau of Tuberculosis Control Annual Summary, 2014



Source: NYC DOHMH Bureau of Tuberculosis Control Annual Summary, 2014

TB Rates by Neighborhood, Brooklyn, NYC, 2014

1.5

2.6

4.7

4.8

5.0

6.5

6.9

7.7

9.6

10.3

23.1

0 5 10 15 20 25

Greenpoint

Downtown-Brooklyn Heights-Park

Williamsburg-Bushwick

East New York

Canarsie-Flatland

Bedford Stuyvesant-Crown Heights

Coney Island

Bensonhurst- Bay Ridge

East Flatbush-Flatbush

Borough Park

Sunset Park

Rate per 100,000

Citywide rate

(7.2 per 100,000)

Effective Visualization

• Visual perception

• Design principles

• Visualization type

• Data stories

Visual Perception

• Humans ‘see’ differences in color, form,

space, sequencing

• Data presentation impacts what we see

and how we interpret it



10 Design Principles

Orient audience

1. Label sufficiently

2. Visually link related elements

3. Create a visual hierarchy

4. Simplify data comparisons

5. Display reference points

10 Design Principles

Eliminate distractions

6. Present text horizontally

7. Limit non-data elements

8. Use color purposively

9. Be cautious with images

10. Avoid distortions.

Data Visualization Types

Figures

• Bar

• Line

Maps

• Choropleth

• Dot density

• Proportional symbol



TB Case Rates by Age Group and Sex, US, 2014

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

Under 5 5 - 14 15 - 24 25 - 44 45 - 64 ≥65

Male Female

Cas

es p

er 1

00,0

00

Source: CDC. Reported Tuberculosis in the United States, 2014. Surveillance Slide set.

20 Leading Causes of DALYs, NYC, 2005

Reported TB Cases, US, 1982–2014*

*Updated as of June 5, 2015.

0

5,000

10,000

15,000

20,000

25,000

30,000

No

. of

Cas

es

Year




TB Case Rates in U.S.-born vs. Foreign-born Persons, United States,* 1993 – 2014**

*Includes the same data as slide 17, but rates presented on a logarithmic scale.

**Updated as of June 5, 2015.

Cas

es

pe

r 1

00

,00

0

1

10

100

1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

U.S. Overall

U.S. -born

Foreign-born


Importance of geography – why map?

• Clustering of disease cases in specific location

• Visualizing health outcomes by geography

• Identifying geographic trends

More focused

interventions

Improved resource

allocation

Better understanding of disease patterns

When to Map?

• Location key to message

– When not key, map not useful for conveying message

• Tables, charts, graphs more useful



Types of Maps

• Choropleth

• Dot density

• Proportional symbol

TB Rates by Neighborhood, Brooklyn, 2014

Sunset Park

2004 2014

DC

Percentage of TB Cases Among Foreign-born Persons, United States*

*Updated as of June 5, 2015.

DC

>50%

25%–49% <25% No cases




Dental Hygienists in South Carolina by Primary Practice Location, 2010

Source: Office for Healthcare Workforce Analysis and Planning, 2011

US Homeless Population by State, 2009

Source: StateHealthFacts.org

Strategic Communications

Using Data • Communicate priorities,

justify policy decisions

• Establish systems to

regularly share visually

compelling data

o Reports highlight specific

health issues or health status of

populations

o Press releases, speeches,

testimonies regularly

incorporate data



A Policy Brief

A concise document that presents findings of policy-relevant data analysis and evaluates policy options for non-technical audiences

Includes:

• Context, scope, impact of problem

• Viable solutions

• Rationale for changing policies

Design Considerations

• Thoughtful design and length (2-4 pages)

• “Hook” that entices audiences to read

beyond the Key Messages

• Clearly worded

• Use graphs, maps, or figures

Resources

Excel

QGIS

ArcGIS

EpiInfo Map



Thank you!

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