Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review
Born out of a necessity for fiscal sustainability, simulation modeling is playing an increasingly prominent role in setting priorities for combination implementation strategies for HIV treatment and prevention globally. The design of a model and the data inputted into it are central factors in ensuring credible inferences. We executed a narrative review of a set of dynamic HIV transmission models to comprehensively synthesize and compare the structural design and the quality of evidence used to support each model. We included 19 models representing both generalized and concentrated epidemics, classified as compartmental, agent-based, individual-based microsimulation or hybrid in our review. We focused on four structural components (population construction; model entry, exit and HIV care engagement; HIV disease progression; and the force of HIV infection), and two analytical components (model calibration/validation; and health economic evaluation, including uncertainty analysis). While the models we reviewed focused on a variety of individual interventions and their combinations, their structural designs were relatively homogenous across three of the four focal components, with key structural elements influenced by model type and epidemiological context. In contrast, model entry, exit and HIV care engagement tended to differ most across models, with some health system interactions—particularly HIV testing—not modeled explicitly in many contexts. The quality of data used in the models and the transparency with which the data was presented differed substantially across model components. Representative and high-quality data on health service delivery were most commonly not accessed or were unavailable. The structure of an HIV model should ideally fit its epidemiological context and be able to capture all efficacious treatment and prevention services relevant to a robust combination implementation strategy. Developing standardized guidelines on evidence syntheses for health economic evaluation would improve transparency and help prioritize data collection to reduce decision uncertainty.
We acknowledge Lindsay Pearce for assistance with manuscript preparation. The Localized HIV Modeling Study Group comprises Czarina N. Behrends, M.P.H, Ph.D., Department of Healthcare Policy and Research, Weill Cornell Medical College; Carlos Del Rio, MD, Hubert Department of Global Health, Emory Center for AIDS Research, Rollins School of Public Health of Emory University; Julia Dombrowski, MD, Department of Epidemiology, University of Washington; Daniel J. Feaster, Ph.D., Center for Family Studies, Department of Epidemiology and Public Health, Leonard M. Miller School of Medicine, University of Miami; Kelly Gebo, Ph.D., Bloomberg School of Public Health, Johns Hopkins University; Matthew Golden, MD, Division of Allergy and Infectious Diseases, University of Washington; Reuben Granich, MD, Independent Public Health Consultant, Washington, DC; Thomas Kerr, Ph.D., BC Centre for Excellence in HIV/AIDS; Faculty of Medicine, University of British Columbia; Gregory Kirk, Ph.D., Bloomberg School of Public Health, Johns Hopkins University; Brandon DL Marshall, Ph.D., Department of Epidemiology, Brown University School of Public Health, Rhode Island, United States; Shruti H. Mehta, Ph.D., Bloomberg School of Public Health, Johns Hopkins University; Lisa Metsch, Ph.D., Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University; Julio S.G. Montaner, MD, BC Centre for Excellence in HIV/AIDS; Faculty of Medicine, University of British Columbia; Bohdan Nosyk, Ph.D., BC Centre for Excellence in HIV/AIDS; Faculty of Health Sciences, Simon Fraser University; Bruce R. Schackman, Ph.D., Department of Healthcare Policy and Research, Weill Cornell Medical College; Steven Shoptaw, Ph.D., Centre for HIV Identification, Prevention and Treatment Services, School of Medicine, University of California Los Angeles; William Small, Ph.D., BC Centre for Excellence in HIV/AIDS; Faculty of Health Sciences, Simon Fraser University; and Steffanie Strathdee, Ph.D., School of Medicine, University of California.
XZ, BN conceptualized and designed the study; XZ and EK developed the search strategy; XZ, EK and LW conducted the literature search, information extraction and developed tables/figures of the results; XZ wrote the first draft of the manuscript; EK, BN and LW contributed to the manuscript development; BDLM, RG, BRS and JSGM aided in the interpretation of results, and provided critical revisions to the article; all authors approved the final draft.
Compliance with Ethical Standards
This study was funded by the BC Ministry of Health-funded ‘Seek and treat for optimal prevention of HIV & AIDS’ pilot project and a Grant from the National Institutes of Health/National Institute on Drug Abuse (R01-DA-041747). The funders had no direct role in the conduct of the analysis or the decision to submit the manuscript for publication.
Conflict of interest
Xiao Zang, Emanuel Krebs, Linwei Wang, Brandon D.L. Marshall, Reuben Granich, Bruce R. Schackman, Julio S.G. Montaner, and Bohdan Nosyk have no conflicts of interest to report.
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