Introduction for Basic Epidemiological Analysis for Surveillance Data

1. Introduction for Basic Epidemiological Analysis for Surveillance Data National Center for Immunization & Respiratory Diseases Influenza Division

2. Strategic Information

3. 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 • Unusual viruses • Unusual syndromes • Unusually large/severe outbreaks • Understand the impact of influenza to guide policy and resource decisions nationally, regionally, globally

4. What do we mean by strategic information? Increasing emphasis on data use and utility ACTION! KNOWLEDGE Application Assessment INFORMATION Data demand generation Understanding DATA Analysis

5. 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

6. 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

7. 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: • Currently circulating viruses • Geographic spread of activity • Increases & decreases in activity • Who is being affected • 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. Example: US Weekly Cumulative Rate of Hospitalizations • Quick understanding of severity by age group – who is requiring hospitalization?

15. Example: US Weekly Pediatric Deaths • Very simple, easy to update graphic of the number of pediatric deaths compared with past season 2008-09 Number of Deaths Reported =133 2009-10 Number of Deaths Reported=282 2010-11 Number of Deaths Reported=116 2007-08 Number of Deaths Reported = 88 Deaths Reported Current Week Deaths Reported Previous Weeks

16. 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

17. 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: • Age • Gender • Comorbidities • Vaccine coverage • Fatalities • Virologic surveillance: • How many positive flu tests • Type and subtype of circulation viruses • Distribution of viruses by age and severity • Vaccine data: • Understand match between circulating viruses & vaccine strains • Vaccine coverage by age/risk groups • Antiviral resistance

18. 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

19. Conclusions • However, even simple analysis requires upfront preparation • Receipt of data requiring little or no cleaning • Streamline as many tasks as possible • Easy data entry or upload • Predefined queries • Graphic templates • Remember that surveillance systems are built over time • Constantly monitor your data, make improvements as needed, fine tune your analysis

20. Thank you!Questions?