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Promoting HIV Testing by Men: A Discrete Choice Experiment to Elicit Preferences and Predict Uptake of Community-based Testing in Uganda

Author

Listed:
  • Elisabeth M. Schaffer

    () (University of Colorado School of Medicine, Anschutz Medical Campus
    University of North Carolina at Chapel Hill)

  • Juan Marcos Gonzalez

    (Duke Clinical Research Institute)

  • Stephanie B. Wheeler

    (University of North Carolina at Chapel Hill)

  • Dalsone Kwarisiima

    (Makerere University Joint AIDS Program)

  • Gabriel Chamie

    (University of California San Francisco)

  • Harsha Thirumurthy

    (University of Pennsylvania)

Abstract

Background and Objectives HIV testing is essential to access HIV treatment and care and plays a critical role in preventing transmission. Despite this, testing coverage is low among men in sub-Saharan Africa. Community-based testing has demonstrated potential to expand male testing coverage, yet scant evidence reveals how community-based services can be designed to optimize testing uptake. We conducted a discrete choice experiment (DCE) to elicit preferences and predict uptake of community-based testing by men in Uganda. Methods Hypothetical choices between alternative community-based testing services and the option to opt-out of testing were presented to a random, population-based sample of 203 adult male residents. The testing alternatives varied by service delivery model (community health campaign, counselor-administered home-based testing, distribution of HIV self-test kits at local pharmacies), availability of multi-disease testing, access to antiretroviral therapy (ART), and provision of a US$0.85 incentive. We estimated preferences using a random parameters logit model and explored whether preferences varied by participant characteristics through subgroup analyses. We simulated uptake when a single and when two community-based testing services are made available, using reference values of observed uptake to calibrate predictions. Results The share of the adult male population predicted to test for HIV ranged from 0.15 to 0.91 when a single community-based testing service is made available and from 0.50 to 0.96 when two community-based services are provided concurrently. ART access was the strongest driver of choices (relative importance [RI] = 3.01, 95% confidence interval [CI]: 1.74–4.29), followed by the service delivery model (RI = 1.27, 95% CI 0.72–1.82) and availability of multi-disease testing (RI = 1.27, 95% CI 0.09–2.45). A US$0.85 incentive had the least yet still significant influence on choices (RI = 0.77, 95% CI 0.06–1.49). Men who perceived their risk of having HIV to be relatively elevated had higher predicted uptake of HIV self-test kits at local pharmacies, as did young adult men compared to men aged ≥ 30 years. Men who earned ≤ the daily median income had higher predicted uptake of all community-based testing services versus men who earned above the daily median income. Conclusion Substantial opportunity exists to optimize the delivery of HIV testing to expand uptake by men; using an innovative DCE, we deliver timely, actionable guidance for promoting community-based testing by men in Uganda. We advance the stated preference literature methodologically by describing how we constructed and evaluated a pragmatic experimental design, used interaction terms to conduct subgroup analyses, and harnessed participant-specific preference estimates to predict and calibrate testing uptake.

Suggested Citation

  • Elisabeth M. Schaffer & Juan Marcos Gonzalez & Stephanie B. Wheeler & Dalsone Kwarisiima & Gabriel Chamie & Harsha Thirumurthy, 2020. "Promoting HIV Testing by Men: A Discrete Choice Experiment to Elicit Preferences and Predict Uptake of Community-based Testing in Uganda," Applied Health Economics and Health Policy, Springer, vol. 18(3), pages 413-432, June.
  • Handle: RePEc:spr:aphecp:v:18:y:2020:i:3:d:10.1007_s40258-019-00549-5
    DOI: 10.1007/s40258-019-00549-5
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    References listed on IDEAS

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    1. Mickael Bech & Dorte Gyrd‐Hansen, 2005. "Effects coding in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 14(10), pages 1079-1083, October.
    2. Jan Ostermann & Bernard Njau & Derek S Brown & Axel Mühlbacher & Nathan Thielman, 2014. "Heterogeneous HIV Testing Preferences in an Urban Setting in Tanzania: Results from a Discrete Choice Experiment," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    3. Bhat, Chandra R., 1998. "Accommodating flexible substitution patterns in multi-dimensional choice modeling: formulation and application to travel mode and departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 455-466, September.
    4. Jan Ostermann & Derek Brown & Axel Mühlbacher & Bernard Njau & Nathan Thielman, 2015. "Would you test for 5000 Shillings? HIV risk and willingness to accept HIV testing in Tanzania," Health Economics Review, Springer, vol. 5(1), pages 1-11, December.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, December.
    6. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    7. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    8. Manuela De Allegri & Isabelle Agier & Justin Tiendrebeogo & Valerie Renée Louis & Maurice Yé & Olaf Mueller & Malabika Sarker, 2015. "Factors Affecting the Uptake of HIV Testing among Men: A Mixed-Methods Study in Rural Burkina Faso," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    9. Jane Hall & Patricia Kenny & Madeleine King & Jordan Louviere & Rosalie Viney & Angela Yeoh, 2002. "Using stated preference discrete choice modelling to evaluate the introduction of varicella vaccination," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 457-465, July.
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    1. Chris Sampson’s journal round-up for 1st June 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-06-01 11:00:00

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