Optimal investment in a portfolio of HIV prevention programs

Quantifying optimal resource allocation strategies for controlling epidemics

Frequent emergence of communicable diseases is a major concern worldwide. Lack of sufficient resources to mitigate the disease burden makes the situation even more challenging for lower-income countries. Hence, strategy development for disease eradication and optimal management of the social and economic burden has garnered a lot of attention in recent years. In this context, we quantify the optimal fraction of resources that can be allocated to two major intervention measures, namely reduction of disease transmission and improvement of healthcare infrastructure. Our results demonstrate that the effectiveness of each of the interventions has a significant impact on the optimal resource allocation in both long-term disease dynamics and outbreak scenarios. The optimal allocation strategy for long-term dynamics exhibits non-monotonic behaviour with respect to the effectiveness of interventions, which differs from the more intuitive strategy recommended in the case of outbreaks. Further, our results indicate that the relationship between investment in interventions and the corresponding increase in patient recovery rate or decrease in disease transmission rate plays a decisive role in determining optimal strategies. Intervention programmes with decreasing returns promote the necessity for resource sharing. Our study provides fundamental insights into determining the best response strategy when controlling epidemics in resource-constrained situations.

Optimal spatial evaluation of a pro rata vaccine distribution rule for COVID-19

The COVID-19 Vaccines Global Access (COVAX) is a World Health Organization (WHO) initiative that aims for an equitable access of COVID-19 vaccines. Despite potential heterogeneous infection levels across a country, countries receiving allotments of vaccines may follow WHO's allocation guidelines and distribute vaccines based on a jurisdictions' relative population size. Utilizing economic-epidemiological modeling, we benchmark the performance of this pro rata allocation rule by comparing it to an optimal one that minimizes the economic damages and expenditures over time, including a penalty representing the social costs of deviating from the pro rata strategy. The pro rata rule performs better when the duration of naturally- and vaccine-acquired immunity is short, when there is population mixing, when the supply of vaccine is high, and when there is minimal heterogeneity in demographics. Despite behavioral and epidemiological uncertainty diminishing the performance of the optimal allocation, it generally outperforms the pro rata vaccine distribution rule.

Optimal resource allocation in HIV self-testing secondary distribution among Chinese MSM: data-driven integer programming models

Human immunodeficiency virus self-testing (HIVST) is an innovative and effective strategy important to the expansion of HIV testing coverage. Several innovative implementations of HIVST have been developed and piloted among some HIV high-risk populations like men who have sex with men (MSM) to meet the global testing target. One innovative strategy is the secondary distribution of HIVST, in which individuals (defined as indexes) were given multiple testing kits for both self-use (i.e.self-testing) and distribution to other people in their MSM social network (defined as alters). Studies about secondary HIVST distribution have mainly concentrated on developing new intervention approaches to further increase the effectiveness of this relatively new strategy from the perspective of traditional public health discipline. There are many points of HIVST secondary distribution in which mathematical modelling can play an important role. In this study, we considered secondary HIVST kits distribution in a resource-constrained situation and proposed two data-driven integer linear programming models to maximize the overall economic benefits of secondary HIVST kits distribution based on our present implementation data from Chinese MSM. The objective function took expansion of normal alters and detection of positive and newly-tested 'alters' into account. Based on solutions from solvers, we developed greedy algorithms to find final solutions for our linear programming models. Results showed that our proposed data-driven approach could improve the total health economic benefit of HIVST secondary distribution. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

HIV supply chains in low- and middle-income countries: overview and research opportunities

Purpose

Despite HIV being reported as one of the major global health issues, availability and accessibility of HIV services and supplies remain limited, especially in low- and middle-income countries. The effective and efficient operation of HIV supply chains is critical to tackle this problem. The purpose of this paper is to give an introduction to HIV supply chains in low- and middle-income countries and identify research opportunities for the operations research/operations management (OR/OM) community.

Design/methodology/approach

First, the authors review a combination of the scientific and grey literature, including both qualitative and quantitative papers, to give an overview of HIV supply chain operations in low- and middle-income countries and the challenges that are faced by organizing such supply chains. The authors then classify and discuss the relevant OR/OM literature based on seven classification criteria: decision level, methodology, type of HIV service modeled, challenges, performance measures, real-life applicability and countries covered. Because research on HIV supply chains in low- and middle-income countries is limited in the OR/OM field, this part also includes papers focusing on HIV supply chain modeling in high-income countries.

Findings

The authors conclude this study by identifying several tendencies and gaps and by proposing future research directions for OR/OM research.

Originality/value

To the best of the authors’ knowledge, this paper is the first literature review addressing this specific topic from an OR/OM perspective.

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

OBJECTIVE

This study reviews optimization models for human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) resource allocation.

METHODS

We searched 2 databases for peer-reviewed articles published from January 1985 through August 2019 that describe optimization models for resource allocation in HIV/AIDS. We included models that consider 2 or more competing HIV/AIDS interventions. We extracted data on selected characteristics and identified similarities and differences across models. We also assessed the quality of mathematical disease transmission models based on the best practices identified by a 2010 task force.

RESULTS

The final qualitative synthesis included 23 articles that used 14 unique optimization models. The articles shared several characteristics, including the use of dynamic transmission modeling to estimate health benefits and the inclusion of specific high-risk groups in the study population. The models explored similar HIV/AIDS interventions that span primary and secondary prevention and antiretroviral treatment. Most articles were focused on sub-Saharan African countries (57%) and the United States (39%). There was notable variation in the types of optimization objectives across the articles; the most common was minimizing HIV incidence or maximizing infections averted (87%). Articles that utilized mathematical modeling of HIV disease and transmission displayed variable quality.

CONCLUSIONS

This systematic review of the literature identified examples of optimization models that have been applied in different settings, many of which displayed similar features. There were similarities in objective functions across optimization models, but they did not align with global HIV/AIDS goals or targets. Future work should be applied in countries facing the largest declines in HIV/AIDS funding.

Public Health Interventions with Harms and Benefits: A Graphical Framework for Evaluating Tradeoffs

BACKGROUND

Evaluations of public health interventions typically report benefits and harms aggregated over the population. However, benefits and harms are not always evenly distributed. Examining disaggregated outcomes enables decision makers to consider health benefits and harms accruing to both intended intervention recipients and others in the population.

METHODS

We provide a graphical framework for categorizing and comparing public health interventions that examines the distribution of benefit and harm between and within population subgroups for a single intervention and compares distributions of harm and benefit for multiple interventions. We demonstrate the framework through a case study of a hypothetical increase in the price of meat (5%, 10%, 25%, or 50%) that, via elasticity of demand, reduces consumption and consequently reduces body mass index. We examine how inequalities in benefits and harms (measured by quality-adjusted life-years) are distributed across a population of white and black males and females.

RESULTS

A 50% meat price increase would yield the greatest net benefit to the population. However, because of reduced consumption among low-weight individuals, black males would bear disproportionate harm relative to the benefit they receive. With increasing meat price, the distribution of harm relative to benefit becomes less "internal" to those receiving benefit and more "distributed" to those not receiving commensurate benefit. When we segment the population by sex only, this result does not hold.

CONCLUSIONS

Disaggregating harms and benefits to understand their differential impact on subgroups can strongly affect which decision alternative is deemed optimal, as can the approach to segmenting the population. Our framework provides a useful tool for illuminating key tradeoffs relevant to harm-averse decision makers and those concerned with both equity and efficiency.

Resource Allocation for Epidemic Control Across Multiple Sub-populations

The number of pathogenic threats to plant, animal and human health is increasing. Controlling the spread of such threats is costly and often resources are limited. A key challenge facing decision makers is how to allocate resources to control the different threats in order to achieve the least amount of damage from the collective impact. In this paper we consider the allocation of limited resources across n independent target populations to treat pathogens whose spread is modelled using the susceptible–infected–susceptible model. Using mathematical analysis of the systems dynamics, we show that for effective disease control, with a limited budget, treatment should be focused on a subset of populations, rather than attempting to treat all populations less intensively. The choice of populations to treat can be approximated by a knapsack-type problem. We show that the knapsack closely approximates the exact optimum and greatly outperforms a number of simpler strategies. A key advantage of the knapsack approximation is that it provides insight into the way in which the economic and epidemiological dynamics affect the optimal allocation of resources. In particular using the knapsack approximation to apportion control takes into account two important aspects of the dynamics: the indirect interaction between the populations due to the shared pool of limited resources and the dependence on the initial conditions.

A Little Planning Goes a Long Way: Multilevel Allocation of HIV Prevention Resources

Background. HIV prevention funds are often allocated by decision makers at multiple levels. High-level decision makers may allocate funds to regions, and regional decision makers then allocate those funds to specific programs. Often, funds are allocated proportionally (e.g., in proportion to HIV incidence) rather than efficiently (i.e., to maximize HIV infections averted). The authors investigate the impact of efficient and proportional allocation methods at 2 different decision levels.

Methods. The authors developed an optimization model of resource allocation at 2 levels—an aggregate upper level and multiple local levels—and considered efficient allocation and allocation proportional to HIV incidence. Using data from 40 U.S. states, they compared 4 strategies for allocating HIV prevention funds.

Results. The greatest health benefit (HIV infections averted) occurred when efficient allocations were made at both levels. When funds were allocated proportionally at the higher level and efficiently at the lower level, the health benefit was about 5% less than when efficient allocations were made at both levels. When funds were allocated efficiently at the higher level and proportionally at the lower level, the health benefit was 15% less than when efficient allocations were made at both levels. The least health benefit (23% less than when efficient allocations were made at both levels) occurred with proportional allocation at both levels.

Conclusions. Efficient allocation only at the higher level cannot overcome poor allocations at lower levels. Moreover, efficient allocation at the lower level is likely to yield greater gains than efficient allocation at the higher level. Thus, upper-level decision makers, such as donor organizations, should develop incentives to promote efficient allocation by lower-level decision makers.

Efficiency, Equity, and Budgetary Policies

The standard decision rules of cost-effectiveness analysis either require the decision maker to set a threshold willingness to pay for additional health care or to set an overall fixed budget. In practice, neither are generally taken, but instead an arbitrary decision rule is followed that may not be consistent with the overall budget, lead to an allocation of resources that is less than optimal, and is unable to identify the program that should be displaced at the margin. Recent work has shown how mathematical programming can be used as a generalization of the standard decision rules. The authors extend the use of mathematical programming, first to incorporate more complex budgetary rules about when expenditure can be incurred, and show the opportunity loss, in terms of health benefit forgone, of each budgetary policy. Second, the authors demonstrate that indivisibility in a patient population can be regarded as essentially a concern for horizontal equity and represent this and other equity concerns as constraints in the program. Third, the authors estimate the different opportunity costs of a range of equity concerns applied to particular patient populations, and when imposed on all patient populations. They apply this framework of analysis to a realistic and policy-relevant problem. Key words: cost-effectiveness analysis; cost-benefit analysis; mathematical programming; resource allocation. (Med Decis Making 2007;27:128—137)

The Impact of Ignoring Population Heterogeneity when Markov Models are Used in Cost-Effectiveness Analysis

Many factors related to the spread and progression of diseases vary throughout a population. This heterogeneity is frequently ignored in cost-effectiveness analyses by using aver-age or representative values or by considering multiple risk groups. The author explores the impact that such simplifying assumptions may have on the results and interpretation of cost-effectiveness analyses when Markov models are used to calculate the costs and health impact of interventions. A discrete-time Markov model for a disease is defined, and 5 potential interventions are considered. Health benefits, costs, and incremental cost-effectiveness ratios are calculated for each intervention. It is assumed that the population is heterogeneous with respect to the probability of becoming sick. Ignoring this heterogeneity may lead to optimistic or pessimistic estimates of cost-effectiveness ratios, depending on the intervention and, in some cases, the parameter values. Implications are discussed of this finding on the use of league tables and on comparisons of cost-effectiveness ratios versus commonly accepted threshold values.

A systematic review of modelling approaches in economic evaluations of health interventions for drug and alcohol problems

Background

The overarching goal of health policies is to maximize health and societal benefits. Economic evaluations can play a vital role in assessing whether or not such benefits occur. This paper reviews the application of modelling techniques in economic evaluations of drug and alcohol interventions with regard to (i) modelling paradigms themselves; (ii) perspectives of costs and benefits and (iii) time frame.

Methods

Papers that use modelling approaches for economic evaluations of drug and alcohol interventions were identified by carrying out searches of major databases.

Results

Thirty eight papers met the inclusion criteria. Overall, the cohort Markov models remain the most popular approach, followed by decision trees, Individual based model and System dynamics model (SD). Most of the papers adopted a long term time frame to reflect the long term costs and benefits of health interventions. However, it was fairly common among the reviewed papers to adopt a narrow perspective that only takes into account costs and benefits borne by the health care sector.

Conclusions

This review paper informs policy makers about the availability of modelling techniques that can be used to enhance the quality of economic evaluations for drug and alcohol treatment interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1368-8) contains supplementary material, which is available to authorized users.

Toward cost-effective staffing mixes for Veterans Affairs substance use disorder treatment programs

Background

In fiscal year (FY) 2008, 133,658 patients were provided services within substance use disorders treatment programs (SUDTPs) in the U.S. Department of Veterans Affairs (VA) health care system. To improve the effectiveness and cost-effectiveness of SUDTPs, we analyze the impacts of staffing mix on the benefits and costs of specialty SUD services. This study demonstrates how cost-effective staffing mixes for each type of VA SUDTPs can be defined empirically.

Methods

We used a stepwise method to derive prediction functions for benefits and costs based on patients’ treatment outcomes at VA SUDTPs nationally from 2001 to 2003, and used them to formulate optimization problems to determine recommended staffing mixes that maximize net benefits per patient for four types of SUDTPs by using the solver function with the Generalized Reduced Gradient algorithm in Microsoft Excel 2010 while conforming to limits of current practice. We conducted sensitivity analyses by varying the baseline severity of addiction problems between lower (2.5 %) and higher (97.5 %) values derived from bootstrapping.

Results and conclusions

Compared to the actual staffing mixes in FY01-FY03, the recommended staffing mixes would lower treatment costs while improving patients’ outcomes, and improved net benefits are estimated from $1472 to $17,743 per patient.

Creating impact with operations research in health: making room for practice in academia

Operations research (OR)-based analyses have the potential to improve decision making for many important, real-world health care problems. However, junior scholars often avoid working on practical applications in health because promotion and tenure processes tend to value theoretical studies more highly than applied studies. This paper discusses the author's experiences in using OR to inform and influence decisions in health and provides a blueprint for junior researchers who wish to find success by taking a similar path. This involves selecting good problems to study, forming productive collaborations with domain experts, developing appropriate models, identifying the most salient results from an analysis, and effectively disseminating findings to decision makers. The paper then suggests how journals, funding agencies, and senior academics can encourage such work by taking a broader and more informed view of the potential role and contributions of OR to solving health care problems. Making room in academia for the application of OR in health follows in the tradition begun by the founders of operations research: to work on important real-world problems where operations research can contribute to better decision making.

HIV epidemic control-a model for optimal allocation of prevention and treatment resources

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.

Approximating optimal controls for networks when there are combinations of population-level and targeted measures available: chlamydia infection as a case-study

Using a modified one-dimensional model for the spread of an SIS disease on a network, we show that the behaviour of complex network simulations can be replicated with a simpler model. This model is then used to design optimal controls for use on the network, which would otherwise be unfeasible to obtain, resulting in information about how best to combine a population-level random intervention with one that is more targeted. This technique is used to minimise intervention costs over a short time interval with a target prevalence, and also to minimise prevalence with a specified budget. When applied to chlamydia, we find results consistent with previous work; that is maximising targeted control (contact tracing) is important to using resources effectively, while high-intensity bursts of population control (screening) are more effective than maintaining a high level of coverage.

Methods in public health services and systems research: a systematic review

CONTEXT

Public Health Services and Systems Research (PHSSR) is concerned with evaluating the organization, financing, and delivery of public health services and their impact on public health. The strength of the current PHSSR evidence is somewhat dependent on the methods used to examine the field. Methods used in PHSSR articles, reports, and other documents were reviewed to assess their methodologic strengths and challenges in light of PHSSR goals.

EVIDENCE ACQUISITION

A total of 364 documents from the PHSSR library met the inclusion criteria as empirical and based in the U.S. After additional exclusions, 327 of these were analyzed.

EVIDENCE SYNTHESIS

A detailed codebook was used to classify articles in terms of (1) study design; (2) sampling; (3) instrumentation; (4) data collection; (5) data analysis; and (6) study validity. Inter-coder reliability was assessed for the codebook; once it was found reliable, the available empirical documents were coded.

CONCLUSIONS

Although there has been a dramatic increase in the amount of published PHSSR recently, methods used remain primarily cross-sectional and descriptive. Moreover, although appropriate for exploratory and foundational work in a new field, these approaches are limiting progress toward some PHSSR goals. Recommendations are given to advance and strengthen the methods used in PHSSR to better meet the goals and challenges facing the field.

Aligning resources to fight HIV/AIDS in the United States: funding to states through the US Department of Health and Human Services

BACKGROUND

In response to the first U.S. National HIV/AIDS Strategy released in July 2010, we assessed how HIV/AIDS funding is spent by the Department of Health and Human Services (HHS) and how these resources align geographically with the HIV/AIDS epidemic according to various measures.

METHODS

Estimated FY2010 spending information was gathered from HHS agencies, including state/territory-level spending by prevention, care, and treatment services of the Centers for Disease Control and Prevention (CDC), Health Resources and Services Administration (HRSA), and Substance Abuse and Mental Health Services Administration (SAMHSA) - as well as Centers for Medicare and Medicaid Services (CMS). HHS funding is presented descriptively by state in the context of living HIV and AIDS case numbers and rates.

RESULTS

Nearly US$16 billion went to discretionary and entitlement spending, 77% of which supported or provided care and treatment by CMS (Medicare, Medicaid) and HRSA; the remainder to research, prevention, and other activities. For states and territories overall, funding was highly correlated with living AIDS case numbers (R(2) = .88) as well as living HIV case numbers (R(2) = .84); funding was far less correlated with case rates (per 100,000 population) for AIDS (R(2) = .35) or HIV (R(2) = .42).

CONCLUSIONS

HHS HIV/AIDS funding, overall, is well correlated with the number of HIV/AIDS cases in each state/territory. Future assessments should capture information on who is being served, where, and how.

Can cost-effectiveness analysis integrate concerns for equity? Systematic review

OBJECTIVES

The aim of this study was to promote approaches to health technology assessment (HTA) that are both evidence-based and values-based. We conducted a systematic review of published studies describing formal methods to consider equity in the context of cost-effectiveness analysis (CEA).

METHODS

Candidate studies were identified through an unrestricted search of the Pub Med and EMBASE databases. The search closed on January 20, 2011. We identified additional studies by consulting experts and checking article bibliographies. Two authors independently reviewed each candidate study to determine inclusion and extracted data from studies retained for review. In addition to documenting methods, data extraction identified implicit and explicit notions of fairness. Data were synthesized in narrative form. Study quality was not assessed.

RESULTS

Of the 695 candidate articles, 51 were retained for review. We identified three broad methods to facilitate quantitative consideration of equity concerns in economic evaluation: integration of distributional concerns through equity weights and social welfare functions, exploration of the opportunity costs of alternative policy options through mathematical programming, and multi-criteria decision analysis.

CONCLUSIONS

Several viable techniques to integrate equity concerns within CEA now exist, ranging from descriptive approaches to the quantitative methods studied in this review. Two obstacles at the normative level have impeded their use in decision making to date: the multiplicity of concepts and values discussed under the rubric of equity, and the lack of a widely accepted normative source on which to ground controversial value choices. Clarification of equity concepts and attention to procedural fairness may strengthen use of these techniques in HTA decision making.

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

HIV/AIDS prevention funds are often allocated at multiple levels of decision-making. Optimal allocation of HIV prevention funds maximizes the number of HIV infections averted. However, decision makers often allocate using simple heuristics such as proportional allocation. We evaluate the impact of using incentives to encourage optimal allocation in a two-level decision-making process. We model an incentive based decision-making process consisting of an upper-level decision maker allocating funds to a single lower-level decision maker who then distributes funds to local programs. We assume that the lower-level utility function is linear in the amount of the budget received from the upper-level, the fraction of funds reserved for proportional allocation, and the number of infections averted. We assume that the upper level objective is to maximize the number of infections averted. We illustrate with an example using data from California, U.S.

HIV prevention through sport: the case of the Mathare Youth Sport Association in Kenya

Sport has become a popular tool for HIV prevention, based on claims that it can foster life skills that are necessary to translate knowledge, attitudes and behavioural intentions into actual behaviour. Empirical evidence of the effectiveness of sport-based HIV prevention programmes is, however, sorely lacking. We therefore conducted a cross-sectional survey assessing sexual behaviour and the determinants thereof among 454 youth of the Mathare Youth Sport Association (MYSA) in Kenya and a control group of 318 non-MYSA members. Multiple (ordinal) logistic regression models were applied to measure the association between MYSA membership and attitudes, subjective norms and self-efficacy related to condom use as well as sexual experience, age at sexual debut, condom use, history of concurrent relationships and number of partners in the last year. MYSA members were more likely to use condoms during the first sex act (odds ratio (OR)=2.10; 95% CI: 1.10-3.99). Consistent condom use with the current/last partner was 23.2% (36/155) among MYSA members vs. 17.2% (17/99) among the control group. Even after adjusting for media exposure - a factor associated with both MYSA membership and higher frequency of condom use - MYSA members were still found to use condoms more frequently with their current/last partner (adjusted OR=1.64; 95% CI: 1.01-2.68). Nevertheless, levels of condom use remain disturbingly low. More rigorous evaluations of sport programmes for HIV prevention are needed. When possible, programmes should be preceded by baseline assessments, trends in risk behaviour of the intervention group should be compared with those of a control group, and protocols for data collection and analysis should include measuring of and adjusting for potentially confounding factors.

Decision making for HIV prevention and treatment scale up: bridging the gap between theory and practice

BACKGROUND

Effectively controlling the HIV epidemic will require efficient use of limited resources. Despite ambitious global goals for HIV prevention and treatment scale up, few comprehensive practical tools exist to inform such decisions.

METHODS

We briefly summarize modeling approaches for resource allocation for epidemic control, and discuss the practical limitations of these models. We describe typical challenges of HIV resource allocation in practice and some of the tools used by decision makers. We identify the characteristics needed in a model that can effectively support planners in decision making about HIV prevention and treatment scale up.

RESULTS

An effective model to support HIV scale-up decisions will be flexible, with capability for parameter customization and incorporation of uncertainty. Such a model needs certain key technical features: it must capture epidemic effects; account for how intervention effectiveness depends on the target population and the level of scale up; capture benefit and cost differentials for packages of interventions versus single interventions, including both treatment and prevention interventions; incorporate key constraints on potential funding allocations; identify optimal or near-optimal solutions; and estimate the impact of HIV interventions on the health care system and the resulting resource needs. Additionally, an effective model needs a user-friendly design and structure, ease of calibration and validation, and accessibility to decision makers in all settings.

CONCLUSIONS

Resource allocation theory can make a significant contribution to decision making about HIV prevention and treatment scale up. What remains now is to develop models that can bridge the gap between theory and practice.

Allocating funds for HIV/AIDS: a descriptive study of KwaDukuza, South Africa

OBJECTIVE

through a descriptive study, we determined the factors that influence the decision-making process for allocating funds to HIV/AIDS prevention and treatment programmes, and the extent to which formal decision tools are used in the municipality of KwaDukuza, South Africa.

METHODS

we conducted 35 key informant interviews in KwaDukuza. The interview questions addressed specific resource allocation issues while allowing respondents to speak openly about the complexities of the HIV/AIDS resource allocation process.

RESULTS

donors have a large influence on the decision-making process for HIV/AIDS resource allocation. However, advocacy groups, governmental bodies and local communities also play an important role. Political power, culture and ethics are among a set of intangible factors that have a strong influence on HIV/AIDS resource allocation. Formal methods, including needs assessment, best practice approaches, epidemiologic modelling and cost-effectiveness analysis are sometimes used to support the HIV/AIDS resource allocation process. Historical spending patterns are an important consideration in future HIV/AIDS allocation strategies.

CONCLUSIONS

several factors and groups influence resource allocation in KwaDukuza. Although formal economic and epidemiologic information is sometimes used, in most cases other factors are more important for resource allocation decision-making. These other factors should be considered in any attempts to improve the resource allocation processes.

Budgetary policies and available actions: a generalisation of decision rules for allocation and research decisions

The allocation problem in health care can be characterised as a mathematical programming problem but attempts to incorporate uncertainty in costs and effect have suffered from important limitations. A two-stage stochastic mathematical programming formulation is developed and applied to a numerical example to explore and demonstrate the implications of this more general and comprehensive approach. The solution to the allocation problem for different budgets, budgetary policies, and available actions are then demonstrated. This analysis is used to evaluate different budgetary policies and examine the adequacy of standard decision rules in cost-effectiveness analysis. The research decision is then considered alongside the allocation problem. This more general formulation demonstrates that the value of further research depends on: (i) the budgetary policy in place; (ii) the realisations revealed during the budget period; (iii) remedial actions that may be available; and (iv) variability in parameters values.

Recommendations for increasing the use of HIV/AIDS resource allocation models

BACKGROUND

Resource allocation models have not had a substantial impact on HIV/AIDS resource allocation decisions in spite of the important, additional insights they may provide. In this paper, we highlight six difficulties often encountered in attempts to implement such models in policy settings; these are: model complexity, data requirements, multiple stakeholders, funding issues, and political and ethical considerations. We then make recommendations as to how each of these difficulties may be overcome.

RESULTS

To ensure that models can inform the actual decision, modellers should understand the environment in which decision-makers operate, including full knowledge of the stakeholders' key issues and requirements. HIV/AIDS resource allocation model formulations should be contextualized and sensitive to societal concerns and decision-makers' realities. Modellers should provide the required education and training materials in order for decision-makers to be reasonably well versed in understanding the capabilities, power and limitations of the model.

CONCLUSION

This paper addresses the issue of knowledge translation from the established resource allocation modelling expertise in the academic realm to that of policymaking.

Optimal investment in HIV prevention programs: more is not always better

This paper develops a mathematical/economic framework to address the following question: Given a particular population, a specific HIV prevention program, and a fixed amount of funds that could be invested in the program, how much money should be invested? We consider the impact of investment in a prevention program on the HIV sufficient contact rate (defined via production functions that describe the change in the sufficient contact rate as a function of expenditure on a prevention program), and the impact of changes in the sufficient contact rate on the spread of HIV (via an epidemic model). In general, the cost per HIV infection averted is not constant as the level of investment changes, so the fact that some investment in a program is cost effective does not mean that more investment in the program is cost effective. Our framework provides a formal means for determining how the cost per infection averted changes with the level of expenditure. We can use this information as follows: When the program has decreasing marginal cost per infection averted (which occurs, for example, with a growing epidemic and a prevention program with increasing returns to scale), it is optimal either to spend nothing on the program or to spend the entire budget. When the program has increasing marginal cost per infection averted (which occurs, for example, with a shrinking epidemic and a prevention program with decreasing returns to scale), it may be optimal to spend some but not all of the budget. The amount that should be spent depends on both the rate of disease spread and the production function for the prevention program. We illustrate our ideas with two examples: that of a needle exchange program, and that of a methadone maintenance program.

Public health delivery systems: evidence, uncertainty, and emerging research needs

The authors review empirical studies published between 1990 and 2007 on the topics of public health organization, financing, staffing, and service delivery. A summary is provided of what is currently known about the attributes of public health delivery systems that influence their performance and outcomes. This review also identifies unanswered questions, highlighting areas where new research is needed. Existing studies suggest that economies of scale and scope exist in the delivery of public health services, and that key organizational and governance characteristics of public health agencies may explain differences in service delivery across communities. Financial resources and staffing characteristics vary widely across public health systems and have expected associations with service delivery and outcomes. Numerous gaps and uncertainties are identified regarding the mechanisms through which organizational, financial, and workforce characteristics influence the effectiveness and efficiency of public health service delivery. This review suggests that new research is needed to evaluate the effects of ongoing changes in delivery system structure, financing, and staffing.

Universal access to HIV treatment in developing countries: going beyond the misinterpretations of the 'cost-effectiveness' algorithm

BACKGROUND

Economic cost-effectiveness analysis (CEA) has been proposed as the appropriate tool to set priorities for resource allocation among available health interventions. Controversy remains about the way CEA should be used in the field of HIV/AIDS.

METHODS AND OBJECTIVES

This paper reviews the general literature in health economics and public economics about the use of CEA for priority setting in public health, in order better to inform current debates about resource allocation in the fight against HIV/AIDS.

RESULTS

Theoretical and practical limitations of CEA do not raise major problems when it is applied to compare alternatives for treating the same medical condition or public health problem. Using CEA to set priorities among different health interventions by ranking them from the lowest to the highest values of their cost per life-year saved is appropriate only under the very restrictive and unrealistic assumptions that all interventions compared are discrete and finite alternatives that cannot vary in terms of size and scale. In order for CEA to inform resource allocation compared across programmes to fight the AIDS epidemic, a pragmatic interpretation of this economic approach, like that proposed by the Commission on Macroeconomics and Health, is better suited. Interventions, like a number of preventive strategies and first-line antiretroviral treatments for HIV, whose marginal costs per additional life-year saved are less than three times the gross domestic product per capita, should be considered cost-effective.

CONCLUSION

Because of their empirical and theoretical limitations, results of CEA should only be one element in priority setting among interventions for HIV/AIDS, which should also be informed by explicit debates about societal and ethical preferences.

S4HARA: System for HIV/AIDS resource allocation

Background

HIV/AIDS resource allocation decisions are influenced by political, social, ethical and other factors that are difficult to quantify. Consequently, quantitative models of HIV/AIDS resource allocation have had limited impact on actual spending decisions. We propose a decision-support System for HIV/AIDS Resource Allocation (S4HARA) that takes into consideration both principles of efficient resource allocation and the role of non-quantifiable influences on the decision-making process for resource allocation.

Methods

S4HARA is a four-step spreadsheet-based model. The first step serves to identify the factors currently influencing HIV/AIDS allocation decisions. The second step consists of prioritizing HIV/AIDS interventions. The third step involves allocating the budget to the HIV/AIDS interventions using a rational approach. Decision-makers can select from several rational models of resource allocation depending on availability of data and level of complexity. The last step combines the results of the first and third steps to highlight the influencing factors that act as barriers or facilitators to the results suggested by the rational resource allocation approach. Actionable recommendations are then made to improve the allocation. We illustrate S4HARA in the context of a primary healthcare clinic in South Africa.

Results

The clinic offers six types of HIV/AIDS interventions and spends US$750,000 annually on these programs. Current allocation decisions are influenced by donors, NGOs and the government as well as by ethical and religious factors. Without additional funding, an optimal allocation of the total budget suggests that the portion allotted to condom distribution be increased from 1% to 15% and the portion allotted to prevention and treatment of opportunistic infections be increased from 43% to 71%, while allocation to other interventions should decrease.

Conclusion

Condom uptake at the clinic should be increased by changing the condom distribution policy from a pull system to a push system. NGOs and donors promoting antiretroviral programs at the clinic should be sensitized to the results of the model and urged to invest in wellness programs aimed at the prevention and treatment of opportunistic infections. S4HARA differentiates itself from other decision support tools by providing rational HIV/AIDS resource allocation capabilities as well as consideration of the realities facing authorities in their decision-making process.

A linear programming model for allocating HIV prevention funds with state agencies: a pilot study

Given the initiatives to improve resource allocation decisions for HIV prevention activities, a linear programming model was designed specifically for use by state and local decision-makers. A pilot study using information from the state of Florida was conducted and studied under a series of scenarios depicting the impact of common resource allocation constraints. Improvements over the past allocation strategy in the number of potential infections averted were observed in all scenarios with a maximal improvement of 73%. When allocating limited resources, policymakers must balance efficiency and equity. In this pilot study, the optimal allocation (i.e., most-efficient strategy) would not distribute resources in an equitable manner. Instead, only 12% of at-risk people would receive prevention funds. We find that less efficient strategies, where 58% fewer infections are averted, result in significantly more equitable allocations. This tool serves as a guide for allocating funds for prevention activities.

Efficient allocation of resources to prevent HIV infection among injection drug users: the Prevention Point Philadelphia (PPP) needle exchange program

The objective of this study is to determine the allocation of resources within a multi-site needle exchange program (NEP) that achieves the largest possible reduction in new HIV infections at minimum cost. We present a model that relates the number of injection drug user (IDU) clients and the number of syringes exchanged per client to both the costs of the NEP and the expected reduction in HIV infections per unit time. We show that cost-effective allocation within a multi-site NEP requires that sites be located where the density of IDUs is highest, and that the number of syringes exchanged per client be equal across sites. We apply these optimal allocation rules to a specific multi-site needle exchange program, Prevention Point Philadelphia (PPP). This NEP, we find, needs to add 2 or 3 new sites in neighborhoods with the highest density of IDU AIDS cases, and to increase its total IDU client base by about 28%, from approximately 6400 to 8200 IDU clients. The case-study NEP also needs to increase its hours of operation at two existing sites, where the number of needles distributed per client is currently sub-optimal, by 50%. At the optimal allocation, the estimated cost per case of HIV averted would be dollar 2800 (range dollar 2300-dollar 4200). Such a favorable cost-effectiveness ratio derives primarily from PPP's low marginal costs per distributed needle.

Improved allocation of HIV prevention resources: using information about prevention program production functions

To allocate HIV prevention resources effectively, it is important to have information about the effectiveness of alternative prevention programs as a function of expenditure. We refer to this relationship as the "production function" for a prevention program. Few studies of HIV prevention programs have reported this relationship. This paper demonstrates the value of such information. We present a simple model for allocating HIV prevention resources, and apply the model to an illustrative HIV prevention resource allocation problem. We show that, without sufficient information about prevention program production functions, suboptimal decisions may be made. We show that epidemiologic data, such as estimates of HIV prevalence or incidence, may not provide enough information to support optimal allocation of HIV prevention resources. Our results suggest that good allocations can be obtained based on fairly basic information about prevention program production functions: an estimate of fixed cost plus a single estimate of cost and resulting risk reduction. We find that knowledge of production functions is most important when fixed cost is high and/or when the budget is a significantly constraining factor. We suggest that, at the minimum, future data collection on prevention program effectiveness should include fixed and variable cost estimates for the intervention when implemented at a "typical" level, along with a detailed description of the intervention and detailed description of costs by category.

Decreasing international HIV transmission: the role of expanding access to opioid agonist therapies for injection drug users

AIMS

To examine the role of expanded access to opioid agonist treatment as a means to decrease international HIV transmission.

DESIGN

Review of the English language literature via Medline.

MEASUREMENTS

Estimates of prevalence rates for injection drug use, HIV infection and treatment effect sizes for changes in opioid use, opioid injection, needle-sharing, injection-related HIV risk behavior and cost.

FINDINGS

An estimated 12.6 million injection drug users internationally accounted for 10% of the 4.2 million new HIV infections in 2003. Ninety-three of the 136 countries (68%) that report injection drug use identify HIV infection related to this behavior. Observational studies of methadone treatment demonstrate decreases in opioid use, opioid injection, needle-sharing and lower rates of HIV prevalence and incidence. The effectiveness of buprenorphine in demonstrating similar findings is expected, although implementations and research are still emerging. The cost-effectiveness of opioid agonist treatment has been established. The barriers to international adoption of opioid agonist treatment, despite the research evidence and international guidelines, are discussed.

CONCLUSIONS

Untreated opioid dependence leads to HIV transmission, on an international level. Opioid agonist treatments are associated with reductions in the frequency of opioid use, fewer injections and injection-related HIV risk behaviors and lower rates of HIV prevalence and incidence. Despite international recommendations, treatment for opioid-dependent injection drug users with methadone and buprenorphine is limited. Research, implementation efforts and political strategies to expand access to opioid agonist treatment are needed in order to combat the spread of HIV, especially in the developing world.

Aligning Budget With U.S. National HIV Prevention Priorities

Reducing new HIV infections in the United States requires allocating public resources to interventions that will have the greatest impact on reducing the number of new infections. We report on the organizational experience of a federal agency's efforts to align its HIV prevention resources to reflect the specific priorities of a five-year strategic plan that has as its goal a fifty percent reduction in the number of annual HIV infections nationwide. Structural and other impediments encountered during the alignment process, and the steps taken to minimize their impact are described, adding to the empirical data base of strategic planning experiences in the public sector.

Preventing HIV in injection drug users: choosing the best mix of interventions for the population

Injection drug users (IDUs) transmit the human immunodeficiency virus (HIV) via both needle sharing and sex. This analysis explores the effects of population risk behaviors, intervention effectiveness, intervention costs, and budget and capacity constraints when allocating funds between two prevention programs to maximize effectiveness. The two interventions, methadone maintenance and street outreach, address different types of risk behavior. We developed a model of the spread of HIV and divided IDUs into susceptible (uninfected) persons and infective persons and separately portrayed sex and injection risk. We simulated the epidemic in San Francisco, California, and New York City for periods from the mid-1980s to the mid-1990s and incorporated the behavioral effects of the two interventions. We used the simulation to find the allocation of a fixed budget to the two interventions that averted the greatest number of infections in the IDUs and their noninjecting sex partners. We assumed that interventions have increasing marginal costs. In the epidemic scenarios, our analysis found that the best allocation nearly always involves spending as much as possible on street outreach. This result is largely insensitive to variations in epidemic scenario, intervention efficacy, and cost. However, the absolute and relative benefits of the best allocation varied. In mid-1990s San Francisco, maximizing spending on outreach averted 3.5% of total HIV infections expected and 10 times the 0.3% from maximizing spending on treatment. In late 1980s New York City, the difference is five-fold (2.6% vs. 0.44%, respectively). Our analyses suggest that, even though prevention works better in higher risk scenarios, the choice of intervention mix is more important in the lower risk scenarios. Models and analyses such as those presented here may help decision makers adapt individual prevention programs to their own communities and to reallocate resources among programs to reflect the evolution of their own epidemics.

Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis

Traditional cost-effectiveness analysis (CEA) assumes that program costs and benefits scale linearly with investment-an unrealistic assumption for epidemic control programs. This paper combines epidemic modeling with optimization techniques to determine the optimal allocation of a limited resource for epidemic control among multiple noninteracting populations. We show that the optimal resource allocation depends on many factors including the size of each population, the state of the epidemic in each population before resources are allocated (e.g. infection prevalence and incidence), the length of the time horizon, and prevention program characteristics. We establish conditions that characterize the optimal solution in certain cases.

Integer/linear mathematical programming models: a tool for allocating healthcare resources

In today's environment, the demand for efficient healthcare resource allocation is increasing. As new technologies become available, allocation decisions become more complex and tools to assist decision makers in determining efficient allocations of healthcare resources are encouraged. Mathematical programs have multiple properties that are desirable for healthcare decision makers such as the simultaneous consideration of multiple constraints and a built-in sensitivity analysis. These models have been well researched and are considered invaluable in other industries. Mathematical programming has also become increasingly visible in facilitating the allocation of healthcare resources in the health services research sector. However, the use of mathematical programming tools has been limited in economic evaluations of new technologies. Budget allocations, such as formulary, drug development, and pricing decisions may benefit greatly from the use of mathematical programs. As an increasing number of expensive new technologies become available and pressure grows to contain healthcare costs, these tools may help guide a more efficient allocation of resources for technologies under budgetary and other constraints.

Optimal allocation of resources across four interventions for type 2 diabetes

BACKGROUND

Several interventions can be applied to prevent complications of type 2 diabetes. This article examines the optimal allocation of resources across 4 interventions to treat patients newly diagnosed with type 2 diabetes. The interventions are intensive glycemic control, intensified hypertension control, cholesterol reduction, and smoking cessation.

METHODS

A linear programming model was designed to select sets of interventions to maximize quality-adjusted life years (QALYs), subject to varied budget and equity constraints.

RESULTS

For no additional cost, approximately 211,000 QALYs can be gained over the lifetimes of all persons newly diagnosed with diabetes by implementing interventions rather than standard care. With increased availability of funds, additional health benefits can be gained but with diminishing marginal returns. The impact of equity constraints is extensive compared to the solution with the same intervention costs and no equity constraint. Under the conditions modeled, intensified hypertension control and smoking cessation interventions were provided most often, and intensive glycemic control and cholesterol reduction interventions were provided less often.

CONCLUSIONS

A resource allocation model identifies trade-offs involved when imposing budget and equity constraints on care for individuals with newly diagnosed diabetes.

The equivalence of numbers: the social value of avoiding health decline: an experimental Web-based study

BACKGROUND

Health economic analysis aimed at informing policy makers and supporting resource allocation decisions has to evaluate not only improvements in health but also avoided decline. Little is known however, whether the "direction" in which changes in health are experienced is important for the public in prioritizing among patients. This experimental study investigates the social value people place on avoiding (further) health decline when directly compared to curative treatments in resource allocation decisions.

METHODS

127 individuals completed an interactive survey that was published in the World Wide Web. They were confronted with a standard gamble (SG) and three person trade-off tasks, either comparing improvements in health (PTO-Up), avoided decline (PTO-Down), or both, contrasting health changes of equal magnitude differing in the direction in which they are experienced (PTO-WAD). Finally, a direct priority ranking of various interventions was obtained.

RESULTS

Participants strongly prioritized improving patients' health rather than avoiding decline. The mean substitution rate between health improvements and avoided decline (WAD) ranged between 0.47 and 0.64 dependent on the intervention. Weighting PTO values according to the direction in which changes in health are experienced improved their accuracy in predicting a direct prioritization ranking. Health state utilities obtained by the standard gamble method seem not to reflect social values in resource allocation contexts.

CONCLUSION

Results suggest that the utility of being cured of a given health state might not be a good approximation for the societal value of avoiding this health state, especially in cases of competition between preventive and curative interventions.