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Development and Calibration of a Dynamic HIV Transmission Model for 6 US Cities

Author

Listed:
  • Xiao Zang

    (BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
    Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada)

  • Emanuel Krebs

    (BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada)

  • Jeong E. Min

    (BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada)

  • Ankur Pandya

    (Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA)

  • Brandon D. L. Marshall

    (Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA)

  • Bruce R. Schackman

    (Department of Healthcare Policy and Research, Weill Cornell Medical College, New York City, NY, USA)

  • Czarina N. Behrends

    (Department of Healthcare Policy and Research, Weill Cornell Medical College, New York City, NY, USA)

  • Daniel J. Feaster

    (Department of Epidemiology and Public Health, Leonard M. Miller School of Medicine, University of Miami, Miami, FL, USA)

  • Bohdan Nosyk

    (BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
    Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada)

Abstract

Background. Heterogeneity in HIV microepidemics across US cities necessitates locally oriented, combination implementation strategies to prioritize resources. We calibrated and validated a dynamic, compartmental HIV transmission model to establish a status quo treatment scenario, holding constant current levels of care for 6 US cities. Methods. Built off a comprehensive evidence synthesis, we adapted and extended a previously published model to replicate the transmission, progression, and clinical care for each microepidemic. We identified a common set of 17 calibration targets between 2012 and 2015 and used the Morris method to select the most influential parameters for calibration. We then applied the Nelder-Mead algorithm to iteratively calibrate the model to generate 2000 best-fitting parameter sets. Finally, model projections were internally validated with a series of robustness checks and externally validated against published estimates of HIV incidence, while the face validity of 25-year projections was assessed by a Scientific Advisory Committee (SAC). Results. We documented our process for model development, calibration, and validation to maximize its transparency and reproducibility. The projected outcomes demonstrated a good fit to calibration targets, with a mean goodness-of-fit ranging from 0.0174 (New York City [NYC]) to 0.0861 (Atlanta). Most of the incidence predictions were within the uncertainty range for 5 of the 6 cities (ranging from 21% [Miami] to 100% [NYC]), demonstrating good external validity. The face validity of the long-term projections was confirmed by our SAC, showing that the incidence would decrease or remain stable in Atlanta, Los Angeles, NYC, and Seattle while increasing in Baltimore and Miami. Discussion. This exercise provides a basis for assessing the incremental value of further investments in HIV combination implementation strategies tailored to urban HIV microepidemics.

Suggested Citation

  • Xiao Zang & Emanuel Krebs & Jeong E. Min & Ankur Pandya & Brandon D. L. Marshall & Bruce R. Schackman & Czarina N. Behrends & Daniel J. Feaster & Bohdan Nosyk, 2020. "Development and Calibration of a Dynamic HIV Transmission Model for 6 US Cities," Medical Decision Making, , vol. 40(1), pages 3-16, January.
  • Handle: RePEc:sae:medema:v:40:y:2020:i:1:p:3-16
    DOI: 10.1177/0272989X19889356
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    References listed on IDEAS

    as
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    3. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
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