IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v38y2018i2p262-272.html
   My bibliography  Save this article

An Adaptive Approach to Locating Mobile HIV Testing Services

Author

Listed:
  • Gregg S. Gonsalves
  • Forrest W. Crawford
  • Paul D. Cleary
  • Edward H. Kaplan
  • A. David Paltiel

Abstract

Background . Public health agencies suggest targeting “hotspots†to identify individuals with undetected HIV infection. However, definitions of hotspots vary. Little is known about how best to target mobile HIV testing resources. Methods . We conducted a computer-based tournament to compare the yield of 4 algorithms for mobile HIV testing. Over 180 rounds of play, the algorithms selected 1 of 3 hypothetical zones, each with unknown prevalence of undiagnosed HIV, in which to conduct a fixed number of HIV tests. The algorithms were: 1) Thompson Sampling, an adaptive Bayesian search strategy; 2) Explore-then-Exploit, a strategy that initially draws comparable samples from all zones and then devotes all remaining rounds of play to HIV testing in whichever zone produced the highest observed yield; 3) Retrospection, a strategy using only base prevalence information; and; 4) Clairvoyance, a benchmarking strategy that employs perfect information about HIV prevalence in each zone. Results . Over 250 tournament runs, Thompson Sampling outperformed Explore-then-Exploit 66% of the time, identifying 15% more cases. Thompson Sampling’s superiority persisted in a variety of circumstances examined in the sensitivity analysis. Case detection rates using Thompson Sampling were, on average, within 90% of the benchmark established by Clairvoyance. Retrospection was consistently the poorest performer. Limitations . We did not consider either selection bias (i.e., the correlation between infection status and the decision to obtain an HIV test) or the costs of relocation to another zone from one round of play to the next. Conclusions . Adaptive methods like Thompson Sampling for mobile HIV testing are practical and effective, and may have advantages over other commonly used strategies.

Suggested Citation

  • Gregg S. Gonsalves & Forrest W. Crawford & Paul D. Cleary & Edward H. Kaplan & A. David Paltiel, 2018. "An Adaptive Approach to Locating Mobile HIV Testing Services," Medical Decision Making, , vol. 38(2), pages 262-272, February.
    • Handle: RePEc:sae:medema:v:38:y:2018:i:2:p:262-272
    DOI: 10.1177/0272989X17716431
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X17716431
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X17716431?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ingrid V Bassett & Darshini Govindasamy & Alison S Erlwanger & Emily P Hyle & Katharina Kranzer & Nienke van Schaik & Farzad Noubary & A David Paltiel & Robin Wood & Rochelle P Walensky & Elena Losina, 2014. "Mobile HIV Screening in Cape Town, South Africa: Clinical Impact, Cost and Cost-Effectiveness," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    2. Nedialko B Dimitrov & Sebastian Goll & Nathaniel Hupert & Babak Pourbohloul & Lauren Ancel Meyers, 2011. "Optimizing Tactics for Use of the U.S. Antiviral Strategic National Stockpile for Pandemic Influenza," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-10, January.
    3. Stanley J. Benkoski & Michael G. Monticino & James R. Weisinger, 1991. "A survey of the search theory literature," Naval Research Logistics (NRL), John Wiley & Sons, vol. 38(4), pages 469-494, August.
    4. David B. Brown & James E. Smith, 2013. "Optimal Sequential Exploration: Bandits, Clairvoyants, and Wildcats," Operations Research, INFORMS, vol. 61(3), pages 644-665, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gillis, Melissa & Urban, Ryley & Saif, Ahmed & Kamal, Noreen & Murphy, Matthew, 2021. "A simulation–optimization framework for optimizing response strategies to epidemics," Operations Research Perspectives, Elsevier, vol. 8(C).
    2. Alberto Vera & Siddhartha Banerjee, 2021. "The Bayesian Prophet: A Low-Regret Framework for Online Decision Making," Management Science, INFORMS, vol. 67(3), pages 1368-1391, March.
    3. Steven M. Shechter & Farhad Ghassemi & Yasin Gocgun & Martin L. Puterman, 2015. "Technical Note—Trading Off Quick versus Slow Actions in Optimal Search," Operations Research, INFORMS, vol. 63(2), pages 353-362, April.
    4. T. C. E. Cheng & B. Kriheli & E. Levner & C. T. Ng, 2021. "Scheduling an autonomous robot searching for hidden targets," Annals of Operations Research, Springer, vol. 298(1), pages 95-109, March.
    5. Reiter, Johannes & Mauch, Franz & Jäckle, Josef, 1992. "Blocking transitions in lattice spin models with directed kinetic constraints," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 184(3), pages 493-498.
    6. Hoam Chung & Elijah Polak & Johannes O. Royset & Shankar Sastry, 2011. "On the optimal detection of an underwater intruder in a channel using unmanned underwater vehicles," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(8), pages 804-820, December.
    7. Bell, Peter N, 2015. "Mineral exploration as a game of chance," MPRA Paper 62159, University Library of Munich, Germany.
    8. Frédéric Dambreville & Jean‐Pierre Le Cadre, 2002. "Detection of a Markovian target with optimization of the search efforts under generalized linear constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(2), pages 117-142, March.
    9. Benoit Duvocelle & János Flesch & Hui Min Shi & Dries Vermeulen, 2021. "Search for a moving target in a competitive environment," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(2), pages 547-557, June.
    10. Keskin, Burcu B. & Griffin, Emily C. & Prell, Jonathan O. & Dilkina, Bistra & Ferber, Aaron & MacDonald, John & Hilend, Rowan & Griffis, Stanley & Gore, Meredith L., 2023. "Quantitative Investigation of Wildlife Trafficking Supply Chains: A Review," Omega, Elsevier, vol. 115(C).
    11. Reiter, J. & Jäckle, J., 1995. "Dynamics of the symmetrically constrained Ising chain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 215(3), pages 311-330.
    12. Abd-Elmoneim Anwar Mohamed & Mohamed Abd Allah El-Hadidy, 2013. "Optimal Multiplicative Generalized Linear Search Plan for a Discrete Random Walker," Journal of Optimization, Hindawi, vol. 2013, pages 1-13, July.
    13. Thul, Lawrence & Powell, Warren, 2023. "Stochastic optimization for vaccine and testing kit allocation for the COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 325-338.
    14. Steve Alpern, 2002. "Rendezvous Search: A Personal Perspective," Operations Research, INFORMS, vol. 50(5), pages 772-795, October.
    15. Ziv Scully & Laura Doval, 2024. "Local hedging approximately solves Pandora's box problems with nonobligatory inspection," Papers 2410.19011, arXiv.org.
    16. Joseph B. Kadane, 2015. "Optimal discrete search with technological choice," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(3), pages 317-336, June.
    17. Nadarajah, Selvaprabu & Secomandi, Nicola, 2023. "A review of the operations literature on real options in energy," European Journal of Operational Research, Elsevier, vol. 309(2), pages 469-487.
    18. Mark Broadie & Weiwei Shen, 2016. "High-Dimensional Portfolio Optimization With Transaction Costs," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-49, June.
    19. Tonderai Mabuto & Mary H Latka & Bulelani Kuwane & Gavin J Churchyard & Salome Charalambous & Christopher J Hoffmann, 2014. "Four Models of HIV Counseling and Testing: Utilization and Test Results in South Africa," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-7, July.
    20. Timothy H. Chung & Rachel T. Silvestrini, 2014. "Modeling and analysis of exhaustive probabilistic search," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(2), pages 164-178, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:38:y:2018:i:2:p:262-272. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.