Optimization Models for HIV/AIDS Resource Allocation: A Systematic Review

Avanceña, Anton L. V.; Hutton, David

doi:10.1016/j.jval.2020.08.001

Cited by 9 publications

(5 citation statements)

References 71 publications

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“…Both national and international stakeholders conveyed a need for modelling to support integrated disease and programme delivery, structural interventions and decisions around human resources and programme administration. By not accounting for these, disease-specific models may not fully capture operational feasibility and decision-making processes, thus undermining perceived validity 40. Multi-disease, ‘whole system’ approaches which consider interactions between diseases, interventions and the health system, such as for the Thanzi La Onse model in Malawi, may enhance the relevance of modelling for local decision-making and resource allocation 41 42.…”

Section: Discussionmentioning

confidence: 99%

“…By not accounting for these, disease-specific models may not fully capture operational feasibility and decision-making processes, thus undermining perceived validity. 40 Multi-disease, 'whole system' approaches which consider interactions between diseases, interventions and the health system, such as for the Thanzi La Onse model in Malawi, may enhance the relevance of modelling for local decisionmaking and resource allocation. 41 42 Further modelling which considers the workforce capacity and subsequent costs will facilitate transparent and feasible estimates of providing cost-effective interventions.…”

Section: Bmj Global Healthmentioning

confidence: 99%

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Evaluation of the use of modelling in resource allocation decisions for HIV and TB

Bowring,

ten Brink,

Martin-Hughes

et al. 2024

BMJ Glob Health

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IntroductionGlobally, resources for health spending, including HIV and tuberculosis (TB), are constrained, and a substantial gap exists between spending and estimated needs. Optima is an allocative efficiency modelling tool that has been used since 2010 in over 50 settings to generate evidence for country-level HIV and TB resource allocation decisions. This evaluation assessed the utilisation of modelling to inform financing priorities from the perspective of country stakeholders and their international partners.MethodsIn October to December 2021, the World Bank and Burnet Institute led 16 semi-structured small-group virtual interviews with 54 representatives from national governments and international health and funding organisations. Interviews probed participants’ roles and satisfaction with Optima analyses and how model findings have had been used and impacted resource allocation. Interviewed stakeholders represented nine countries and 11 different disease programme-country contexts with prior Optima modelling analyses. Interview notes were thematically analysed to assess factors influencing the utilisation of modelling evidence in health policy and outcomes.ResultsCommon influences on utilisation of Optima findings encompassed the perceived validity of findings, health system financing mechanisms, the extent of stakeholder participation in the modelling process–including engagement of funding organisations, sociopolitical context and timeliness of the analysis. Using workshops can facilitate effective stakeholder engagement and collaboration. Model findings were often used conceptually to localise global evidence and facilitate discussion. Secondary outputs included informing strategic and financial planning, funding advocacy, grant proposals and influencing investment shifts.ConclusionAllocative efficiency modelling has supported evidence-informed decision-making in numerous contexts and enhanced the conceptual and practical understanding of allocative efficiency. Most immediately, greater involvement of country stakeholders in modelling studies and timing studies to key strategic and financial planning decisions may increase the impact on decision-making. Better consideration for integrated disease modelling, equity goals and financing constraints may improve relevance and utilisation of modelling findings.

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Section: Discussionmentioning

confidence: 99%

Section: Bmj Global Healthmentioning

confidence: 99%

Evaluation of the use of modelling in resource allocation decisions for HIV and TB

Bowring,

ten Brink,

Martin-Hughes

et al. 2024

BMJ Glob Health

View full text Add to dashboard Cite

show abstract

“…By not accounting for these, disease-specific models may not fully capture operational feasibility and decision-making processes, thus undermining perceived validity. 24 Multi-disease, "whole system" approaches which consider interactions between diseases, interventions and the health system, such as for the Thanzi La Onse model in Malawi, may enhance the relevance of modelling for local decision-making and resource allocation. 25,26 Further modelling which considers the workforce capacity and subsequent costs will facilitate transparent and feasible estimates of providing cost-effective interventions.…”

Section: Discussionmentioning

confidence: 99%

Qualitative evaluation of the use of modelling in resource allocation decisions for HIV and TB

Bowring

Brink

Martin-Hughes

et al. 2023

Preprint

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Introduction: Globally, resources for health spending, including HIV and tuberculosis (TB), are constrained, and a substantial gap exists between spending and estimated needs. Optima is an allocative efficiency modelling tool that has been used since 2010 in over 50 settings to generate evidence for country-level HIV and TB resource allocation decisions. This evaluation sought to assess the determinants and outcomes of using modelling to inform financing priorities from the perspective of country stakeholders and their international partners. Methods: In October-December 2021, the World Bank and Burnet Institute led 16 small-group virtual interviews with representatives from national governments and international health and funding organizations. Interviewed stakeholders represented nine countries and 11 different disease program country contexts where Optima modelling work had been undertaken. Interview notes were thematically analyzed to evaluate determinants of research translation into policy and practice. Results: Common factors that facilitated or inhibited the application of Optima findings broadly encompassed the perceived validity of findings, health system financing mechanisms, the extent of stakeholder participation, engagement of funding organization, socio-political context, and whether the analysis was timed to suit data and stakeholder needs. Key reported outcomes of Optima analyses related to improved understanding of data and allocative efficiency, support for strategic planning, financial planning, funding advocacy and grant proposals, and influencing investment shifts between interventions or their delivery modalities. Conclusion: Allocative efficiency modeling has supported evidence-informed decision making in numerous contexts and enhanced the conceptual and practical understanding of allocative efficiency. Most immediately, greater involvement of country stakeholders in modelling studies and tying the timing of such studies to key strategic and financial planning decisions may increase the impact on decision making. To further improve relevance and acceptance of modelling findings, there needs to be greater consideration given to integrated disease modelling, equity goals, and financing constraints.

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“…10 Mathematical modeling has been used to evaluate the potential impact of diverse HIV interventions on HIV transmission, morbidity, mortality, and other outcomes [11][12][13][14][15] and to prioritize resource allocation. 16 The objective of this study was to model the potential impact of the HIV-1 nucleic acid testing, linkage, treatment, and PNS interventions, as delivered in the Tambua Mapema Plus (TMP) trial, on the Kenyan HIV epidemic. Specifically, our aim was to evaluate the TMP intervention's impact on the first 2 UNAIDS 95-95-95 targets by modeling the proportion of PLWH who would know their status and the proportion of those diagnosed who would be on treatment.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Impact of HIV-1 Nucleic Acid Testing Among Symptomatic Adult Outpatients in Kenya

Hamilton

Agutu

Babigumira

et al. 2022

JAIDS Journal of Acquired Immune Deficiency Syndromes

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Optimization Models for HIV/AIDS Resource Allocation: A Systematic Review

Cited by 9 publications

References 71 publications

Evaluation of the use of modelling in resource allocation decisions for HIV and TB

Evaluation of the use of modelling in resource allocation decisions for HIV and TB

Qualitative evaluation of the use of modelling in resource allocation decisions for HIV and TB

Modeling the Impact of HIV-1 Nucleic Acid Testing Among Symptomatic Adult Outpatients in Kenya

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