Role of Routine HIV Testing in Concentrated Epidemics Operations Research for

Optimizing the HIV Testing Program in an Urban Canadian Setting

K Vasarhelyi, S Kok, JSG Montaner, AR Rutherford, R Barrios, K McPherson, M Thumath, L Tran,

A Nathoo, R Gustafson

Collaboration of Academic and Public Health Partners• BC Centre for Excellence in HIV/AIDS• Vancouver Coastal Health • Providence Health Care • The IRMACS Centre

A poster for the Vancouver Coastal Health / Providence Health Care social marketing campaign promoting routine HIV testing

The IRMACS Centre

The BC Centre for Excellence in HIV/AIDS & Providence Health Care

BACKGROUND

Stakeholder’s Questions

1. Should we do it? Can routine voluntary HIV testing make a useful contribution to controlling the HIV epidemic in Vancouver?2. How can we do it? What is the best way to integrate routine voluntary HIV testing into the current testing program?

The HIV Epidemic in Vancouver• Concentrated epidemic• MSM, IDU, sex workers1 • HIV prevalence ~12 / 10002

• >200 new diagnoses / year in past 10 years3

• <150 new diagnoses in 20123

• HIV testing traditionally risk-based• No routine testing guidelines in Canada

(1) MSM – men who have sex with men; IDU – injection drug user(2) McInnes et al., 2009, Harm Reduction Journal(3) BC Centre for Disease Control (Vancouver’s population 600,000) / Vancouver Coastal Health

Routine TestingGeneralized epidemics

Lower yield Lower cost/test

Risk-based TestingConcentrated

epidemicsHigher yield

Higher cost/test

What is the optimal mix of testing methods for Vancouver?

Routine TestingGeneralized epidemics

Lower yield Lower cost/test

Risk-based TestingConcentrated

epidemicsHigher yield

Higher cost/test

YIELD COST

What is the optimal mix of testing methods for Vancouver?

What is the optimal mix of testing methods for Vancouver?

Objectives

• Minimize morbidity• Minimize mortality• Minimize HIV incidence

What is the optimal mix of testing methods for Vancouver?

Objective

• Minimize morbidity• Minimize mortality• Minimize HIV incidence

Operations Research and Optimization

• Find best intervention to meet objective• Intervention is resource allocation• Optimal distribution of new resources• Optimal realignment of existing resources

MODEL

Model DevelopmentStep 1

Qualitative Model for Cascade of Care

Step 2 Qualitative Model for

HIV Testing Program

Step 4System Dynamics / HIV Transmission Simulation Model of Cascade of Care

with Detailed HIV Testing Program

Step 3Combine

Model DevelopmentStep 1

Qualitative Model for Cascade of Care

Step 2 Qualitative Model for

HIV Testing Program

Step 4System Dynamics / HIV Transmission Simulation Model of Cascade of Care

with Detailed HIV Testing Program

Step 3Combine

General Population

MSM

Other Key Populations (IDU, Sex workers)

Qualitative Model of the Cascade of Care

Decisions and activities in the HIV care continuum defined through consultations with system experts

Qualitative Model of the Cascade of Care

Decisions and activities in the HIV care continuum defined through consultations with system experts

DIAGNOSISLINKAGE

TOCARE

RETENTIONIN

CARE

Qualitative Model of the HIV Testing Program

Vancouver Coastal Health for STOP HIV/AIDS Project, Vancouver, Canada (2013)

Qualitative Model of the HIV Testing Program

Vancouver Coastal Health for STOP HIV/AIDS Project, Vancouver, Canada (2013)

Routine Testing inHOSPITALS

HIV Testing Resources • No $ estimate available• Cost of 1 Risk-Based Test > Cost of 1 Routine Test• Considered 1:1 to 9:1 cost ratios

Number of Tests / Month

Total HIV Testing Resources

+Cost Ratio

RESULTS

Question 1Is routine testing effective in reducing

HIV incidence in Vancouver?

SIMULATON SCENARIO1. Increase total testing budget by 50%.2. Invest all new resources in one program:• Risk-based testing or• Routine testing in high-prevalence settings or• Routine testing in hospitals

3. Compare 5-year cumulative incidence.

Relative effectiveness of testing programsin reducing 5-year cumulative HIV incidence

Risk-based TestingUp to 83 infections averted in 5 years

Routine Testing in HospitalsUp to 104 infections averted in 5 years

Routine Testing inHigh-Prevalence SettingsUp to 274 infections averted in 5 years

Question 2How many infections would be averted by increasing routine testing in hospitals and

improving engagement in treatment?SIMULATION SCENARIO

1. Increase total testing budget by 50%.2. Invest all new resources in routine testing in

hospitals.3. Increase immediate treatment initiation after linkage

to care from 38% to 75% and reduce loss to follow-up from 26% to 10%.

4. Compare 5-year cumulative incidence.

Test Cost RatioRisk-based :Routine

Infections AvertedOver 5 Years Change in

Infections AvertedBaseline

EngagementImproved

Engagement

1:1 41 81 + 98 %

5:1 79 121 + 53 %

9:1 104 147 + 41%

Increasing routine testing in hospitals and improving engagement in treatment

Question 3How many infections would be averted by realigning existing resources between risk-

based and routine testing in hospitals?

SIMULATION SCENARIO1. Keep total testing budget the same.2. Realign existing resources between risk-based

testing and routine testing in hospitals in 5% increments.

3. Compare 5-year cumulative incidence.

Optimal resource allocation to risk-based testing and routine testing in hospitals to

minimize HIV incidence

Cost Ratio

% Resources in Routine Testing

in Hospitals

Optimal % Hospital

Admissions to Test

(Current=12%)Current Optimal

1:1 38% 0% 0%

3:1 17% 15% 10%

5:1 11% 30% 32%

7:1 8% 40% 59%

9:1 6% 45% 83%

Optimal resource allocation to risk-based testing and routine testing in hospitals to

minimize HIV incidence

Cost Ratio

% Resources in Routine Testing

in Hospitals

Optimal % Hospital

Admissions to Test

(Current=12%)Current Optimal

1:1 38% 0% 0%

3:1 17% 15% 10%

5:1 11% 30% 32%

7:1 8% 40% 59%

9:1 6% 45% 83%

CONCLUSIONS

Conclusions

• Routine HIV testing in Vancouver is likely to be averting infections, especially in high-prevalence settings. In general routine testing may play an important role in controlling concentrated HIV epidemics.

• Optimizing across the cascade of care could avert additional infections.

• Realigning existing resources may improve efficiency of the testing program.

Conclusions

• Next steps include – Morbidity and mortality as optimization objectives – Developing other parts of the model of cascade

• Operations research and optimization provide powerful methods to inform implementation of WHO guidelines on early treatment initiation.

Collaborators & SponsorsBC Centre for

Excellence in HIV/AIDSSilvia Guillemi

Guillaume ColleySusan Shurgold

Benita Yip

Vancouver Coastal Health &Providence Health Care

Kendra McPhersonMeaghan Thumath

Lynn TranReka GustafsonAfshan Nathoo

Allison MacbethChris Buchner

Val MunroeJat Sandhu

Ellen DemlowTim Chu

Scott Harrison

BC Centre for Disease Control

Mark GilbertTravis Salway Hottes

Gina Ogilvie

University of Zurich

Lukas Ahrenberg

IRMACSPam BorghardtPeter Borwein

Brian CorrieFelix Breden

Kelly GardnerAlexa van der Waall

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