The influence of constraints on the efficient allocation of resources for HIV prevention

Adapting Economic Evaluation Methods to Shifting Global Health Priorities: Assessing the Value of Health System Inputs

OBJECTIVES

We highlight the importance of undertaking value assessments for health system inputs if allocative efficiency is to be achieve with health sector resources, with a focus on low- and middle-income countries. However, methodological challenges complicated the application of current economic evaluation techniques to health system input investments.

METHODS

We undertake a review of the literature to examine how assessments of investments in health system inputs have been considered to date, highlighting several studies that have suggested ways to address the methodological issues. Additionally, we surveyed how empirical economic evaluations of health system inputs have approached these issues. Finally, we highlight the steps required to move toward a comprehensive standardized framework for undertaking economic evaluations to make value assessments for investments in health systems.

RESULTS

Although the methodological challenges have been illustrated, a comprehensive framework for value assessments of health system inputs, guiding the evidence required, does not exist. The applied literature of economic evaluations of health system inputs has largely ignored the issues, likely resulting in inaccurate assessments of cost-effectiveness.

CONCLUSIONS

A majority of health sector budgets are spent on health system inputs, facilitating the provision of healthcare interventions. Although economic evaluation methods are a key component in priority setting for healthcare interventions, such methods are less commonly applied to decision making for investments in health system inputs. Given the growing agenda for investments in health systems, a framework will be increasingly required to guide governments and development partners in prioritizing investments in scarce health sector budgets.

Implementation and resource needs for long-acting PrEP in low- and middle-income countries: a scoping review

INTRODUCTION

Several low- and middle-income countries (LMICs) are preparing to introduce long-acting pre-exposure prophylaxis (LAP). Amid multiple pre-exposure prophylaxis (PrEP) options and constrained funding, decision-makers could benefit from systematic implementation planning and aligned costs. We reviewed national costed implementation plans (CIPs) to describe relevant implementation inputs and activities (domains) for informing the costed rollout of LAP. We assessed how primary costing evidence aligned with those domains.

METHODS

We conducted a rapid review of CIPs for oral PrEP and family planning (FP) to develop a consensus of implementation domains, and a scoping review across nine electronic databases for publications on PrEP costing in LMICs between January 2010 and June 2022. We extracted cost data and assessed alignment with the implementation domains and the Global Health Costing Consortium principles.

RESULTS

We identified 15 implementation domains from four national PrEP plans and FP-CIP template; only six were in all sources. We included 66 full-text manuscripts, 10 reported LAP, 13 (20%) were primary cost studies-representing seven countries, and none of the 13 included LAP. The 13 primary cost studies included PrEP commodities (n = 12), human resources (n = 11), indirect costs (n = 11), other commodities (n = 10), demand creation (n = 9) and counselling (n = 9). Few studies costed integration into non-HIV services (n = 5), above site costs (n = 3), supply chains and logistics (n = 3) or policy and planning (n = 2), and none included the costs of target setting, health information system adaptations or implementation research. Cost units and outcomes were variable (e.g. average per person-year).

DISCUSSION

LAP planning will require updating HIV prevention policies, technical assistance for logistical and clinical support, expanding beyond HIV platforms, setting PrEP achievement targets overall and disaggregated by method, extensive supply chain and logistics planning and support, as well as updating health information systems to monitor multiple PrEP methods with different visit schedules. The 15 implementation domains were variable in reviewed studies. PrEP primary cost and budget data are necessary for new product introduction and should match implementation plans with financing.

CONCLUSIONS

As PrEP services expand to include LAP, decision-makers need a framework, tools and a process to support countries in planning the systematic rollout and costing for LAP.

Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review

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Mathematical model capabilities to explore complex systems now enable priority-setting to consider local resource constraints.

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Common objectives of model-based analyses incorporating constraints are to assess real-world feasibility or allocate resources efficiently.

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Constraints may be incorporated via (i) model-based estimation; (ii) linkage of mathematical and health system models; or (iii) optimisation.

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Models can then project constrained intervention effects and costs and resource requirement s for delivering interventions at full scale.

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'Health system constraints' should be systematically defined for routine operationalisation in model-based priority-setting.

Priority setting for infectious disease control is increasingly concerned with physical input constraints and other real-world restrictions on implementation and on the decision process. These health system constraints determine the ‘feasibility’ of interventions and hence impact. However, considering them within mathematical models places additional demands on model structure and relies on data availability. This review aims to provide an overview of published methods for considering constraints in mathematical models of infectious disease.

We systematically searched the literature to identify studies employing dynamic transmission models to assess interventions in any infectious disease and geographical area that included non-financial constraints to implementation. Information was extracted on the types of constraints considered and how these were identified and characterised, as well as on the model structures and techniques for incorporating the constraints.

A total of 36 studies were retained for analysis. While most dynamic transmission models identified were deterministic compartmental models, stochastic models and agent-based simulations were also successfully used for assessing the effects of non-financial constraints on priority setting. Studies aimed to assess reductions in intervention coverage (and programme costs) as a result of constraints preventing successful roll-out and scale-up, and/or to calculate costs and resources needed to relax these constraints and achieve desired coverage levels. We identified three approaches for incorporating constraints within the analyses: (i) estimation within the disease transmission model; (ii) linking disease transmission and health system models; (iii) optimising under constraints (other than the budget).

The review highlighted the viability of expanding model-based priority setting to consider health system constraints. We show strengths and limitations in current approaches to identify and quantify locally-relevant constraints, ranging from simple assumptions to structured elicitation and operational models. Overall, there is a clear need for transparency in the way feasibility is defined as a decision criteria for its systematic operationalisation within models.

Effect of Universal Testing and Treatment on HIV Incidence - HPTN 071 (PopART)

BACKGROUND

A universal testing and treatment strategy is a potential approach to reduce the incidence of human immunodeficiency virus (HIV) infection, yet previous trial results are inconsistent.

METHODS

In the HPTN 071 (PopART) community-randomized trial conducted from 2013 through 2018, we randomly assigned 21 communities in Zambia and South Africa (total population, approximately 1 million) to group A (combination prevention intervention with universal antiretroviral therapy [ART]), group B (the prevention intervention with ART provided according to local guidelines [universal since 2016]), or group C (standard care). The prevention intervention included home-based HIV testing delivered by community workers, who also supported linkage to HIV care and ART adherence. The primary outcome, HIV incidence between months 12 and 36, was measured in a population cohort of approximately 2000 randomly sampled adults (18 to 44 years of age) per community. Viral suppression (<400 copies of HIV RNA per milliliter) was assessed in all HIV-positive participants at 24 months.

RESULTS

The population cohort included 48,301 participants. Baseline HIV prevalence was 21% or 22% in each group. Between months 12 and 36, a total of 553 new HIV infections were observed during 39,702 person-years (1.4 per 100 person-years; women, 1.7; men, 0.8). The adjusted rate ratio for group A as compared with group C was 0.93 (95% confidence interval [CI], 0.74 to 1.18; P = 0.51) and for group B as compared with group C was 0.70 (95% CI, 0.55 to 0.88; P = 0.006). The percentage of HIV-positive participants with viral suppression at 24 months was 71.9% in group A, 67.5% in group B, and 60.2% in group C. The estimated percentage of HIV-positive adults in the community who were receiving ART at 36 months was 81% in group A and 80% in group B.

CONCLUSIONS

A combination prevention intervention with ART provided according to local guidelines resulted in a 30% lower incidence of HIV infection than standard care. The lack of effect with universal ART was unanticipated and not consistent with the data on viral suppression. In this trial setting, universal testing and treatment reduced the population-level incidence of HIV infection. (Funded by the National Institute of Allergy and Infectious Diseases and others; HPTN 071 [PopArt] ClinicalTrials.gov number, NCT01900977.).