Introduction for Basic Epidemiological Analysis for

Surveillance Data

National Center for Immunization & Respiratory Diseases Influenza Division

Strategic Information

What Does Strategic Information Mean?

Generating information and knowledge to influence policy making, programmatic action and research

• Which viruses are circulating, where, when, who is affected?

• Contribute to vaccine selection• Determine intensity and impact of activity• Detect unusual events

oUnusual virusesoUnusual syndromesoUnusually large/severe outbreaks

Understand the impact of influenza to guide policy and resource decisions nationally, regionally, globally

What do we mean by strategic

information?

DATA

INFORMATION

KNOWLEDGE

ACTION!

Data demand generation

Analysis

Understanding

Application

Increasing emphasis on data use and utility

Assessment

Considerations: Data Collection & Analysis

Data for action must be timely

Analysis does not need to be complex to be useful

Know your data!

Feedback to data providers is critical

Considerations: Timeliness Timely analysis can mean:

• Use of preliminary results in order to convey data quickly

• Rapid response to unusual events• Implementation of prevention and control

efforts• Situational awareness

Considerations for Analysis Surveillance data analysis does not have to be complex

to be useful – analyses that can be updated frequently & quickly are often sufficient

• Often the simple messages are the most important and effective during an influenza season:o Currently circulating viruseso Geographic spread of activityo Increases & decreases in activityo Who is being affectedo Detection of unusual events – large outbreaks, unusual

severity; unusual viruses Responsibility to use all data collected

• Does not all need to be used in routine reports• Full analysis may be done at less frequent intervals• Responsibility to follow up on signals

Know Your Data All datasets are different – let your analysis & decision

making plans guide your collection of a dataset

• Consider how much data is needed for a stable output

• Which sites have the biggest impact

There is no one way to do analysis BUT some basic principles of surveillance analysis are key to a global understanding

Analytic methods can be developed and enhanced over time

Examples of Analysis & Reporting

Weekly reports:

• Percent SARI/ILI flu positive, by population, hospitalizations, consultations, region

• Comparison to previous seasons

• Number of SARI/ILI patients tested & proportion positive

• Number of sentinel sites reporting

• By age group

• Observation of circulating types & subtypes

Weekly Analysis

Allows detection of signals & rapid response to follow up of signals

• Where is the increase occurring? Single site? Multiple site?

Are there increases in other surveillance data – laboratory positives?

• Are you receiving specimens?• Is the signal due to another pathogen?

Contact site submitting data for more information Make sure you understand & can explain the data

you are reporting Again, a glance at a picture gives a good

understanding of current activity, problems, monitoring of reporting

Example: US Weekly Outpatient ILI Report

Monitor Influenza-like Illness

• >3000 healthcare providers in 50 US states

• Mix of practice types

• >25 million patient visits each year

• Subset provides clinical specimens

Regularly Reporting Sites: 2009-2010

Example: US Weekly Outpatient ILI Report

Quick graphical presentation of ILI activity provides a picture of what is happening now, how it compares to baseline and to previous seasons

Example: US Weekly Outpatient ILI Report

Same data, by state, allows us to see regional trends

Again, a glance at a picture gives a good understanding of current activity

Example: US Weekly Cumulative Rate of Hospitalizations

Quick understanding of severity by age group – who is requiring hospitalization?

Example: US Weekly Pediatric Deaths

Very simple, easy to update graphic of the number of pediatric deaths compared with past season

0

5

10

15

20

25

30

35

40

2007

-40

2007

-46

2007

-52

2008

-06

2008

-12

2008

-18

2008

-24

2008

-30

2008

-36

2008

-42

2008

-48

2009

-01

2009

-07

2009

-13

2009

-19

2009

-25

2009

-31

2009

-37

2009

-43

2009

-49

2010

-03

2010

-09

2010

-15

2010

-21

2010

-27

2010

-33

2010

-39

2010

-45

2010

-51

2011

-05

2011

-11

2011

-17

2011

-23

2011

-29

2011

-35

Week of Death

Num

ber

of d

eath

s

2007-08Number of Deaths

Reported = 88

2008-09Number of Deaths

Reported =133

2009-10Number of

Deaths Reported=282

2010-11Number of Deaths

Reported=116

Deaths Reported Current Week Deaths Reported Previous Weeks

Date Influenza A (2009 H1N1)

Influenza A (H3N2)

Influenza A (Subtype Unknown) Influenza B Total

# Deaths CurrentWeek – 39 0 0 0 0 0

# Deaths SinceOctober 1, 2010 30 21 20 45 116

Example: WHO Weekly Report for the Eastern Mediterranean Region

Data source: FluNet (www.who.int/flunet). Global Influenza Surveillance and Response System (GISRS) Data generated on 27/03/2013

Annual Reporting Epidemiologic surveillance: SARI & ILI:

• In-depth description and summary of annual trends in SARI data collected by week unable to be analyzed and updated on a weekly basis:o Ageo Gendero Comorbiditieso Vaccine coverageo Fatalities

Virologic surveillance:o How many positive flu testso Type and subtype of circulation viruseso Distribution of viruses by age and severity

Vaccine data:• Understand match between circulating viruses & vaccine

strains• Vaccine coverage by age/risk groups• Antiviral resistance

Conclusions These are simply examples:

• Your analysis plan depends on your data & the message you want to convey; these are critical considerations when you develop your database: develop a plan first

None of the examples shown include complex analysis• Counts, %, cumulative rate• These simple analyses allow for effective presentation of

data, whether in one week or for the whole year

Conclusions However, even simple analysis requires

upfront preparation• Receipt of data requiring little or no cleaning• Streamline as many tasks as possible

o Easy data entry or uploado Predefined querieso Graphic templates

Remember that surveillance systems are built over time

• Constantly monitor your data, make improvements as needed, fine tune your analysis

Thank you!Questions?