Sharing the costs of structural interventions: What can models tell us?

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Sharing the costs of structural interventions : What can models tell us? / Stuart, Robyn M.; Wilson, David P.

In: International Journal of Drug Policy, 2021.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Stuart, RM & Wilson, DP 2021, 'Sharing the costs of structural interventions: What can models tell us?', International Journal of Drug Policy. https://doi.org/10.1016/j.drugpo.2020.102702

APA

Stuart, R. M., & Wilson, D. P. (2021). Sharing the costs of structural interventions: What can models tell us? International Journal of Drug Policy, [102702]. https://doi.org/10.1016/j.drugpo.2020.102702

Vancouver

Stuart RM, Wilson DP. Sharing the costs of structural interventions: What can models tell us? International Journal of Drug Policy. 2021. 102702. https://doi.org/10.1016/j.drugpo.2020.102702

Author

Stuart, Robyn M. ; Wilson, David P. / Sharing the costs of structural interventions : What can models tell us?. In: International Journal of Drug Policy. 2021.

Bibtex

@article{e992c95a8ffb4c13b63955323db053aa,
title = "Sharing the costs of structural interventions: What can models tell us?",
abstract = "Background: The global HIV response needs to both integrate with the broader health system and tackle the structural drivers of HIV. Cross-sectoral financing arrangements in which different sectors agree to co-finance structural interventions – have been put forward as promising frameworks to address these concerns. However, co-financing arrangements remain rare for HIV, and there is no consensus on how to distribute costs. Methods: We use case studies to investigate how structural interventions can be incorporated within three quantitative decision-making frameworks. First, we consider cost-benefit analyses (CBA) using an opioid substitution therapy (OST) program in Armenia; second, we construct a theoretical example to illustrate the lessons game theory can shed on the co-financing arrangements implied by CBA; and third we consider allocative efficiency analyses using needle-syringe programs (NSPs) in Belarus. Results: A cross-sectoral cost-benefit analysis of OST in Armenia demonstrates that the share of that should be funded by the HIV sector depends on the willingness to pay (WTP) to avert an HIV-related DALY, the long-term cost-benefit ratio, and the HIV risk reduction from OST. For reasonable parameter values, the HIV sector's share ranges between 0–48%. However, the Shapley value––a game-theoretic solution to cost attribution that ensures each sector gains as much or more as they would from acting independently––implies that the HIV sector's share may be higher. In Belarus, we find that the HIV sector should be willing to co-finance structural interventions that would increase the maximal attainable coverage of NSPs, with the contribution again depending on the WTP to avert an HIV-related DALY. Conclusion: Many interventions known to have cross-sectoral benefits have historically been funded from HIV budgets, but this may change in the future. The question of how to distribute the costs of structural interventions is critical, and frameworks that decision-makers use to inform resource allocations will need to take this into account.",
keywords = "Co-financing, Cost attribution, Structural interventions",
author = "Stuart, {Robyn M.} and Wilson, {David P.}",
year = "2021",
doi = "10.1016/j.drugpo.2020.102702",
language = "English",
journal = "International Journal of Drug Policy",
issn = "0955-3959",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Sharing the costs of structural interventions

T2 - What can models tell us?

AU - Stuart, Robyn M.

AU - Wilson, David P.

PY - 2021

Y1 - 2021

N2 - Background: The global HIV response needs to both integrate with the broader health system and tackle the structural drivers of HIV. Cross-sectoral financing arrangements in which different sectors agree to co-finance structural interventions – have been put forward as promising frameworks to address these concerns. However, co-financing arrangements remain rare for HIV, and there is no consensus on how to distribute costs. Methods: We use case studies to investigate how structural interventions can be incorporated within three quantitative decision-making frameworks. First, we consider cost-benefit analyses (CBA) using an opioid substitution therapy (OST) program in Armenia; second, we construct a theoretical example to illustrate the lessons game theory can shed on the co-financing arrangements implied by CBA; and third we consider allocative efficiency analyses using needle-syringe programs (NSPs) in Belarus. Results: A cross-sectoral cost-benefit analysis of OST in Armenia demonstrates that the share of that should be funded by the HIV sector depends on the willingness to pay (WTP) to avert an HIV-related DALY, the long-term cost-benefit ratio, and the HIV risk reduction from OST. For reasonable parameter values, the HIV sector's share ranges between 0–48%. However, the Shapley value––a game-theoretic solution to cost attribution that ensures each sector gains as much or more as they would from acting independently––implies that the HIV sector's share may be higher. In Belarus, we find that the HIV sector should be willing to co-finance structural interventions that would increase the maximal attainable coverage of NSPs, with the contribution again depending on the WTP to avert an HIV-related DALY. Conclusion: Many interventions known to have cross-sectoral benefits have historically been funded from HIV budgets, but this may change in the future. The question of how to distribute the costs of structural interventions is critical, and frameworks that decision-makers use to inform resource allocations will need to take this into account.

AB - Background: The global HIV response needs to both integrate with the broader health system and tackle the structural drivers of HIV. Cross-sectoral financing arrangements in which different sectors agree to co-finance structural interventions – have been put forward as promising frameworks to address these concerns. However, co-financing arrangements remain rare for HIV, and there is no consensus on how to distribute costs. Methods: We use case studies to investigate how structural interventions can be incorporated within three quantitative decision-making frameworks. First, we consider cost-benefit analyses (CBA) using an opioid substitution therapy (OST) program in Armenia; second, we construct a theoretical example to illustrate the lessons game theory can shed on the co-financing arrangements implied by CBA; and third we consider allocative efficiency analyses using needle-syringe programs (NSPs) in Belarus. Results: A cross-sectoral cost-benefit analysis of OST in Armenia demonstrates that the share of that should be funded by the HIV sector depends on the willingness to pay (WTP) to avert an HIV-related DALY, the long-term cost-benefit ratio, and the HIV risk reduction from OST. For reasonable parameter values, the HIV sector's share ranges between 0–48%. However, the Shapley value––a game-theoretic solution to cost attribution that ensures each sector gains as much or more as they would from acting independently––implies that the HIV sector's share may be higher. In Belarus, we find that the HIV sector should be willing to co-finance structural interventions that would increase the maximal attainable coverage of NSPs, with the contribution again depending on the WTP to avert an HIV-related DALY. Conclusion: Many interventions known to have cross-sectoral benefits have historically been funded from HIV budgets, but this may change in the future. The question of how to distribute the costs of structural interventions is critical, and frameworks that decision-makers use to inform resource allocations will need to take this into account.

KW - Co-financing

KW - Cost attribution

KW - Structural interventions

UR - http://www.scopus.com/inward/record.url?scp=85081655368&partnerID=8YFLogxK

U2 - 10.1016/j.drugpo.2020.102702

DO - 10.1016/j.drugpo.2020.102702

M3 - Journal article

C2 - 32173275

AN - SCOPUS:85081655368

JO - International Journal of Drug Policy

JF - International Journal of Drug Policy

SN - 0955-3959

M1 - 102702

ER -

ID: 243064874