Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review

Xiao Zang, Emanuel Krebs, Linwei Wang, Brandon D. L. Marshall, Reuben Granich, Bruce R. Schackman, Julio S. G. Montaner and Bohdan Nosyk ()
Additional contact information
Xiao Zang: British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital
Emanuel Krebs: British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital
Linwei Wang: British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital
Brandon D. L. Marshall: Brown University
Reuben Granich: Independent Public Health Consultant
Bruce R. Schackman: Weill Cornell Medical College
Julio S. G. Montaner: British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital
Bohdan Nosyk: British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital

PharmacoEconomics, 2019, vol. 37, issue 10, No 3, 1219-1239

Abstract: Abstract 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.

Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s40273-019-00817-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:pharme:v:37:y:2019:i:10:d:10.1007_s40273-019-00817-1

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40273

DOI: 10.1007/s40273-019-00817-1

Access Statistics for this article

PharmacoEconomics is currently edited by Timothy Wrightson and Christopher I. Carswell

More articles in PharmacoEconomics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().