Anatoli Kamali
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Transcript of Anatoli Kamali
Overview of IAVI Fingerprint projects, and use of fingerprinting in fishing communities in Uganda
International AIDS Vaccine Initiative
&
MRC/UVRI Uganda Research Unit on AIDS
IAVI –Africa partners Fingerprints projects
IAVI and African CRC have conducted a series of fingerprint projects in East and Southern countries to:
• determine whether FPT could prevent co-enrolment across sites
• assess acceptability of FPT
• assess the use of FPT as a tool to track hard-to-reach mobile populations as a ‘virtual cohort’.
• FPT is being used in a study of HIV prevalence, incidence, retention and migration in fishing communities in Uganda.
Risks for co-enrolment: Validity of trial results and potential serious adverse effects from multiple vaccinations
Background 1: IAVI’s Initial Interest was in Participant
"Collisions" Between Research, Surveillance and
Treatment
• Data from a few studies in Africa reported Co-Enrollment in HIV Prevention clinical trials
• HIV research organizations including IAVI (Protocol B) have recognized co-enrollments within observational protocols e.g. participant was able to co-enrol in two IAVI-sponsored studies in Kenya
• IAVI made initial investments in fingerprint (<$25,000) in an attempt to see whether fingerprint technology could prevent co-enrollment
across sites, and asses its acceptability
• The resulting product was called Detection of Clinical Co-Enrollment or “Linux Beta,” consisting of an inexpensive netbook and fingerprint scanner
Background 2: IAVI’s Secondary Interest was In
Fingerprint as a Tool to Track Hard-To-Reach
Populations and Lower the Cost of Cohort Surveillance
• IAVI and Africa partners have been participating in studies with Key population cohorts, including fishing and sex worker communities.
• HIV incidence remains very high (4.7/100 PYAR [3.5-6.2]); higher in females (8.0 [5.5-11.7]) than men (3.1 [2.0-4.7]), with no evidence of decline
• Thus suitable for HIV prevention trials BUT high mobility may impact the suitability
• >80% who do not attend visits are reported as “out-migrated” or “not contactable”
Tracking individuals – house-to-house surveys
• “Traditional” strategies: locator maps and mobile phones may not be appropriate
• Potential of misidentification!
Field survey
Tracking Hard-To-Reach Populations and Lower the
Cost of Cohort Surveillance
• Alternative strategies such as a mobile FPT system offers the promise of being able to have health workers inexpensively follow participants outside the clinic, including at their homes and specially designated kiosks
• IAVI made an additional investment (<$20,000) in a mobile fingerprint system in an attempt attempt to see whether fingerprint technology could be used in surveillance studies
• The resulting product was called Android Biometric data Collection (ABC) (and formally virtual cohort). It consisted of a either an Android tablet or phone, with a multi-spectral fingerprint scanner
Potential Fingerprint failures
• Participant refusal to provide a fingerprint
• Inability to present the required finger/s to physical constraints (amputations or injuries)
• Fingerprint reader or computer system malfunctions –
Ø software failures
Ø reader unable to capture an image of sufficient quality for successful fingerprint template extraction
Phase I – Linux Beta Shows Us Acceptability of
Fingerprint But Inadequate Performance
• IAVI’s partnered with Vaxtrac/Biometrac, a Gates Challenge grant awardee, to build a low-cost (USD$1000 per year per site) fingerprint-based detection of co-enrollment system. It was the first system designed explicitly to detect co-enrollment across trial networks.
• The system utilizes netbook tablets and 3G connections and can rapidly take a participant’s fingerprint, transmit it to a cloud matching
engine and determine if someone has been co-enrolled previously.
• The system was deployed at KAVI-KNH and KAVI-Kangemi, and CGMRC within Protocol C.
Phase I – Linux Beta Shows Us Acceptability of
Fingerprint But Inadequate Performance:
Lessons Learned and Conclusion
• Lesson 1: Fingerprint is generally acceptable to the populations, with very few refusals to consent across both KAVI and CGMRC.
• Lesson 2: The Linux Beta’s reliance on Internet connectivity
frustrated the site staff, and made them uncertain whether the netbook was going to work when called upon.
• Lesson 3: Revealed a high (7.8%) failure rate
• Conclusion: The Linux Beta’s high error rate and inability to
work offline, made the system frustrating to use and only
minimally viable as a clinical tool.
Phase II – Android Biometric data Collection (ABC/
Virtual Cohort) Expands Capabilities But Has
Limitations
• Building on the lessons learned from the Linux Beta, IAVI set out to build ABC in a way that would be flexible than the Linux beta.
• The system comprised of an Android smart phone or tablet and a multi-spectral fingerprint scanner (<$1000). The system was configured so it could work with no Internet connection for seven days.
• The first deployment was for the AHI/Fever Study with 5 clinics and pharmacies on the coast of Kenya near CGMRC-Mtwapa.
• The second deployment was at ZEHRP Ndola for population surveillance including FSW, and ANC. And the most recent deployment has been for the CHESS study at UVRI-Uganda.
Phase II – Android Biometric data Collection (ABC/ Virtual Cohort)
Expands Capabilities But Has Limitations
Lessons Learned and Conclusion
• Lesson 1: Deployment of ABC at Pharmacies was a failure. Mtwapaarea pharmacies are high volume operations, and pharmacy staff were reluctant to assist the study even for cash incentives.
• Lesson 2: The fingerprint operators were very inconsistent in taking good fingerprints
• Lesson 3: Even with four finger authentication experienced false positives at a higher then expected rate (~4%)
• Conclusion: Due to disappointing performance, IAVI demanded a complete overall the fingerprint algorithm, so as to put it inline with real world use and provide greater tolerance for operator error.
Phase III – Android Biometric data Collection improvement
• With lots of assistance from ZEHRP (over 1000 scans), IAVI and Biometrac set out to improve the operation of ABC and reduce error rates
• The fingerprint matching algorithm was adjusted, tested, and retested. After adjustment, a final ZEHRP stress test showed:
– That accuracy of approximately 1 false negative (a person not being identified upon return to any clinic) out of 1000 scans was attained by scanning four fingers (2 thumbs and 2 index).
– The same algorithm effectively eliminates potential for false positive (a person being misidentified as the wrong person).
– Two finger (thumb) scanning reduces accuracy to about 1 false negative in 100.
1
23
45 6
78
9
MASAKA
KALUNGU
MPIGI
WAKISO
KAMPALA
MUKONO
JINJA
KALANGALA
Kyamuliibwa:
MRC Office and Study
Sites
Entebbe:
Head office and
Study Sites
Kampala (Mengo):
Clinic and
Study Site
Trans African highway
Masaka:
MRC Office and Study
Sites
Lake Victoria Study
Sites:
1 Mitondo
2 Kisuku
3 Makonzi
4 Kassa
5 Kabasese
6 Bukakata
7 Lambu
8 Kaziru
9 Koome/ Damba
ISO
PALA
MUKONO
JINJA
1
23
444 6
UNGU
MPIGI
1
UGANDA
LAKE VICTORIA
Location of study sites and offices
Jinja:
Study Site
50km
N
FPT: HIV prevalence, incidence, retention and migration study
Mobility - absence from home…
14
Busy schedules and “un identifiable” residences
All Residents moved to another island!
Can we be innovative?
IAVI –Uganda team atop their field boat
Fingerprint project: Gershim Asiki
Fingerprinting scanner (TFT 500P VX 10.0, Grinding technology co., LTD, China) usable without internet connectivity, supplied by Endeavour Africa
Fingerprint in fishing communities- Uganda
• Aug 2015 - Feb 2016, enrolled adults ≥18years a house to house HCT survey in 18 communities
• Repeated every six months up one year to assess HIV incidence
• A subgroup 18-30 years (most mobile) followed quarterly to assess migrations
• The scanners automatically register volunteer’s fingerprint signature by converting the fingerprint into an alphanumeric number using unique algorithm, as well as recording the date and time against the respective ID
• The fingerprint signature data with no volunteer names or other identifiable data are subsequently downloaded and managed on a centralized database
Acknowledgement
• International AIDS Vaccine Initiative (IAVI) – Fran Priddy, Pat Fast, David Mark and colleagues
• MRC/UVRI Uganda Research Unit on AIDS – Gershim Asiki, Andrew Abaasa
• KAVI, Centre for Geographic Medicine Research – Coast, Kilifi