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