1. Incorporating a Fingerprinting System into the Western Kenya Health and Demographic Surveillance System, 2009 Ezekiel Chiteri, Wilfred Ijaa Frank Odhiambo, Marta Ackers, Allen Hightower, James Kwach, Kayla Laserson INDEPTH CONFERENCE 27 th October 2009 KEMRI/CDC Research and Public Health Collaboration Kisumu, Kenya

3. Background(1) KEMRI/CDC has multiple projects – Health and demographic surveillance System (HDSS), malaria, TB and HIV research Projects assign their participants unique study IDs –Some projects distribute ID cards Projects operate in same study area, same study pop Individuals can enroll in one or more projects –Some projects do not allow cross-study participation Health facility (HF) surveillance conducted as follows –In-patient conducted in 1 hospital –Out-patient conducted in 3 clinics –HIV and TB care and treatment programs conducted in all health facilities The current method of linkage between HDSS and HF/projects is through a search engine tool

4. “SINGLE” POPULATION KEMRI/CDC & OTHER MEDICAL HEALTH ORGANIZATIONS Background (2)

5. Background (3) Challenges to linking individuals from HDSS data to HF/ studies information Misplaced ID cards Name similarities Migrations reconciliation Non uniform identification of participants by different projects/studies

6. Objective To develop an efficient identification system for the whole organization: To be used for linking the HDSS to all HF/projects’ data Scalable and adaptable Acceptable Cost effective

7. Methodology Design a fingerprint system –Database design –Selection of hardware and software development kits (SDKs) –User application design Develop SOPs and procedures for the fingerprint system Ethical clearance -obtained from the KEMRI Ethical Review Committee and the CDC Institutional Review Board Implementation of the fingerprint system Post implementation review

8. Database Design

9. Front-end Design

10. System Specification (HARDWARE) Finger Print Readers –Microsoft Fingerprint Reader –Digital persona Computers –Pentium Processor (i386) (2.0 GHz or later) –1GB RAM or more –5GB of free space in the hard disk.

11. System Specification (SOFTWARE) Database and SDK –Fingerprint SDK 2009 for Windows by GriauleBiometrics –MS SQL SERVER 2005 Operating System –Windows XP Professional

12. System Costs ItemRecommended Brand Average Cost Fingerpt ReaderMicrosoft fingerprint reader$50 SDK Fingerprint SDK 2009 by griaulebiometrics$36 PC Any Brand with the above specifications$1200 Average Cost Per work Station$1286

13. Implementation STEPS: System deployment and user training Health facility and additional study sites’ data collection points HDSS household surveillance data collection points Fingerprint data consolidation

14. Fingerprint Collection Points TOOLSPOINT OF OPERATION Centralized or Replicated Database Fingerprints POPULATION Health facility Mobile Surveillance Other studies Data Point 4 Data Point 5 PC, Laptop, Tablet PC Fingerprint Reader

15. Results 868 fingerprints collected 1352 patient visits recorded in the hospitals Patient visits include multiple visits by the individuals – Fingerprints are enrolled only once – Enrolled fingerprints used to identify individuals in subsequent visits Children<1 were not fingerprinted

16. Limitations Children under 1 year were not finger printed due to a low success rate in enrolling their finger prints during the pilot stage

17. Conclusions High acceptability at current collection points Feasible means of individual identification in health and demographic surveillance research It takes short time to enroll/identify individuals

18. What next? Measuring the success rate of fingerprint identification Build fingerprint database of all residents using HDSS surveillance Measure acceptability in our surveillance area

19. Acknowledgements Colleagues (Programmers) DSS data managers and field workers Study participants KEMRI/CDC PEPFAR