Cost-effectiveness of eye care services in Zambia.

OBJECTIVE: To estimate the cost-effectiveness of cataract surgery and refractive error/presbyopia correction in Zambia. METHODS: Primary data on costs and health related quality of life were collected in a prospective cohort study of 170 cataract and 113 refractive error/presbyopia patients recruited from three health facilities. Six months later, follow-up data were available from 77 and 41 patients who had received cataract surgery and spectacles, respectively. Costs were determined from patient interviews and micro-costing at the three health facilities. Utility values were gathered by administering the EQ-5D quality of life instrument immediately before and six months after cataract surgery or acquiring spectacles. A probabilistic state-transition model was used to generate cost-effectiveness estimates with uncertainty ranges. RESULTS: Utility values significantly improved across the patient sample after cataract surgery and acquiring spectacles. Incremental costs per Quality Adjusted Life Years gained were US$259 for cataract surgery and US$ 375 for refractive error correction. The probabilities of the incremental cost-effectiveness ratios being below the Zambian gross national income per capita were 95% for both cataract surgery and refractive error correction. CONCLUSION: In spite of proven cost-effectiveness, severe health system constraints are likely to hamper scaling up of the interventions

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

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

Informing Balanced Investment in Services and Health Systems: A Case Study of Priority Setting for Tuberculosis Interventions in South Africa.

OBJECTIVES: Health systems face nonfinancial constraints that can influence the opportunity cost of interventions. Empirical methods to explore their impact, however, are underdeveloped. We develop a conceptual framework for defining health system constraints and empirical estimation methods that rely on routine data. We then present an empirical approach for incorporating nonfinancial constraints in cost-effectiveness models of health benefit packages for the health sector. METHODS: We illustrate the application of this approach through a case study of defining a package of services for tuberculosis case-finding in South Africa. An economic model combining transmission model outputs with unit costs was developed to examine the cost-effectiveness of alternative screening and diagnostic algorithms. Constraints were operationalized as restrictions on achievable coverage based on: (1) financial resources; (2) human resources; and (3) policy constraints around diagnostics purchasing. Cost-effectiveness of the interventions was assessed under one "unconstrained" and several "constrained" scenarios. For the unconstrained scenario, incremental cost-effectiveness ratios were estimated with and without the costs of "relaxing" constraints. RESULTS: We find substantial differences in incremental cost-effectiveness ratios across scenarios, leading to variations in the decision rules for prioritizing interventions. In constrained scenarios, the limiting factor for most interventions was not financial, but rather the availability of human resources. CONCLUSIONS: We find that optimal prioritization among different tuberculosis control strategies in South Africa is influenced by whether and how constraints are taken into consideration. We thus demonstrate both the importance and feasibility of considering nonfinancial constraints in health sector resource allocation models

Empirical estimation of resource constraints for use in model-based economic evaluation: an example of TB services in South Africa.

BACKGROUND: Evidence on the relative costs and effects of interventions that do not consider 'real-world' constraints on implementation may be misleading. However, in many low- and middle-income countries, time and data scarcity mean that incorporating health system constraints in priority setting can be challenging. METHODS: We developed a 'proof of concept' method to empirically estimate health system constraints for inclusion in model-based economic evaluations, using intensified case-finding strategies (ICF) for tuberculosis (TB) in South Africa as an example. As part of a strategic planning process, we quantified the resources (fiscal and human) needed to scale up different ICF strategies (cough triage and WHO symptom screening). We identified and characterised three constraints through discussions with local stakeholders: (1) financial constraint: potential maximum increase in public TB financing available for new TB interventions; (2) human resource constraint: maximum current and future capacity among public sector nurses that could be dedicated to TB services; and (3) diagnostic supplies constraint: maximum ratio of Xpert MTB/RIF tests to TB notifications. We assessed the impact of these constraints on the costs of different ICF strategies. RESULTS: It would not be possible to reach the target coverage of ICF (as defined by policy makers) without addressing financial, human resource and diagnostic supplies constraints. The costs of addressing human resource constraints is substantial, increasing total TB programme costs during the period 2016-2035 by between 7% and 37% compared to assuming the expansion of ICF is unconstrained, depending on the ICF strategy chosen. CONCLUSIONS: Failure to include the costs of relaxing constraints may provide misleading estimates of costs, and therefore cost-effectiveness. In turn, these could impact the local relevance and credibility of analyses, thereby increasing the risk of sub-optimal investments

Estimating the Impact of Tuberculosis Case Detection in Constrained Health Systems: An Example of Case-Finding in South Africa.

Mathematical models are increasingly being used to compare strategies for tuberculosis (TB) control and inform policy decisions. Models often do not consider financial and other constraints on implementation and may overestimate the impact that can be achieved. We developed a pragmatic approach for incorporating resource constraints into mathematical models of TB. Using a TB transmission model calibrated for South Africa, we estimated the epidemiologic impact and resource requirements (financial, human resource (HR), and diagnostic) of 9 case-finding interventions. We compared the model-estimated resources with scenarios of future resource availability and estimated the impact of interventions under these constraints. Without constraints, symptom screening in public health clinics and among persons receiving care for human immunodeficiency virus infection was predicted to lead to larger reductions in TB incidence (9.5% (2.5th-97.5th percentile range (PR), 8.6-12.2) and 14.5% (2.5th-97.5th PR, 12.2-16.3), respectively) than improved adherence to diagnostic guidelines (2.7%; 2.5th-97.5th PR, 1.6-4.1). However, symptom screening required large increases in resources, exceeding future HR capacity. Even under our most optimistic HR scenario, the reduction in TB incidence from clinic symptom screening was 0.2%-0.9%-less than that of improved adherence to diagnostic guidelines. Ignoring resource constraints may result in incorrect conclusions about an intervention's impact and may lead to suboptimal policy decisions. Models used for decision-making should consider resource constraints

The impact of Coronavirus disease 2019 (COVID-19) on health systems and household resources in Africa and South Asia

AbstractBackgroundCoronavirus disease 2019 (COVID-19) epidemics strain health systems and households. Health systems in Africa and South Asia may be particularly at risk due to potential high prevalence of risk factors for severe disease, large household sizes and limited healthcare capacity.MethodsWe investigated the impact of an unmitigated COVID-19 epidemic on health system resources and costs, and household costs, in Karachi, Delhi, Nairobi, Addis Ababa and Johannesburg. We adapted a dynamic model of SARS-CoV-2 transmission and disease to capture country-specific demography and contact patterns. The epidemiological model was then integrated into an economic framework that captured city-specific health systems and household resource use.FindingsThe cities severely lack intensive care beds, healthcare workers and financial resources to meet demand during an unmitigated COVID-19 epidemic. A highly mitigated COVID-19 epidemic, under optimistic assumptions, may avoid overwhelming hospital bed capacity in some cities, but not critical care capacity.InterpretationViable mitigation strategies encompassing a mix of responses need to be established to expand healthcare capacity, reduce peak demand for healthcare resources, minimise progression to critical care and shield those at greatest risk of severe disease.FundingBill &amp; Melinda Gates Foundation, European Commission, National Institute for Health Research, Department for International Development, Wellcome Trust, Royal Society, Research Councils UK.Research in contextEvidence before this studyWe conducted a PubMed search on May 5, 2020, with no language restrictions, for studies published since inception, combining the terms (“cost” OR “economic”) AND “covid”. Our search yielded 331 articles, only two of which reported estimates of health system costs of COVID-19. The first study estimated resource use and medical costs for COVID-19 in the United States using a static model of COVID 19. The second study estimated the costs of polymerase chain reaction tests in the United States. We found no studies examining the economic implications of COVID-19 in low- or middle-income settings.Added value of this studyThis is the first study to use locally collected data in five cities (Karachi, Delhi, Nairobi, Addis Ababa and Johannesburg) to project the healthcare resource and health economic implications of an unmitigated COVID-19 epidemic. Besides the use of local data, our study moves beyond existing work to (i) consider the capacity of health systems in key cities to cope with this demand, (ii) consider healthcare staff resources needed, since these fall short of demand by greater margins than hospital beds, and (iii) consider economic costs to health services and households.Implications of all the evidenceDemand for ICU beds and healthcare workers will exceed current capacity by orders of magnitude, but the capacity gap for general hospital beds is narrower. With optimistic assumptions about disease severity, the gap between demand and capacity for general hospital beds can be closed in some, but not all the cities. Efforts to bridge the economic burden of disease to households are needed.</jats:sec

Costs and Cost-Effectiveness of Biomedical, Non-Surgical HIV Prevention Interventions: A Systematic Literature Review.

BACKGROUND: Considerable evidence on the costs and cost-effectiveness of biomedical, non-surgical interventions to prevent human immunodeficiency virus (HIV) transmission has been generated over the last decade. This study aims to synthesize findings and identify remaining knowledge gaps to suggest future research priorities. METHODS: A systematic literature review was carried out in August 2020 using the MEDLINE, Embase, Global Health and EconLit databases to retrieve economic evaluations and costing studies of oral pre-exposure prophylaxis (PrEP), injectable long-acting PrEP, vaginal microbicide rings and gels, HIV vaccines and broadly neutralizing antibodies. Studies reporting costs from the provider or societal perspective were included in the analysis. Those reporting on behavioural methods of prevention, condoms and surgical approaches (voluntary medical male circumcision) were excluded. The quality of reporting of the included studies was assessed using published checklists. RESULTS: We identified 3007 citations, of which 87 studies were retained. Most were set in low- and middle-income countries (LMICs; n = 53) and focused on the costs and/or cost-effectiveness of oral PrEP regimens (n = 70). Model-based economic evaluations were the most frequent study design; only two trial-based cost-effectiveness analyses and nine costing studies were found. Less than half of the studies provided practical details on how the intervention would be delivered by the health system, and only three of these, all in LMICs, explicitly focused on service integration and its implication for delivery costs. 'Real-world' programme delivery mechanisms and costs of intervention delivery were rarely considered. PrEP technologies were generally found to be cost-effective only when targeting high-risk subpopulations. Single-dose HIV vaccines are expected to be cost-effective for all groups despite substantial uncertainty around pricing. CONCLUSIONS: A lack of primary, detailed and updated cost data, including above-service level costs, from a variety of settings makes it difficult to evaluate the cost-effectiveness of specific delivery modes at scale, or to evaluate strategies for services integration. Closing this evidence gap around real-world implementation is vital, not least because the strategies targeting high-risk groups that are recommended by PrEP models may incur substantially higher costs and be of limited practical feasibility in some settings

Correction to: The epidemiologic impact and cost-effectiveness of new tuberculosis vaccines on multidrug-resistant tuberculosis in India and China.

The original article contained errors in the Abstract which have all since been corrected

The epidemiologic impact and cost-effectiveness of new tuberculosis vaccines on multidrug-resistant tuberculosis in India and China.

BACKGROUND: Despite recent advances through the development pipeline, how novel tuberculosis (TB) vaccines might affect rifampicin-resistant and multidrug-resistant tuberculosis (RR/MDR-TB) is unknown. We investigated the epidemiologic impact, cost-effectiveness, and budget impact of hypothetical novel prophylactic prevention of disease TB vaccines on RR/MDR-TB in China and India. METHODS: We constructed a deterministic, compartmental, age-, drug-resistance- and treatment history-stratified dynamic transmission model of tuberculosis. We introduced novel vaccines from 2027, with post- (PSI) or both pre- and post-infection (P&PI) efficacy, conferring 10 years of protection, with 50% efficacy. We measured vaccine cost-effectiveness over 2027-2050 as USD/DALY averted-against 1-times GDP/capita, and two healthcare opportunity cost-based (HCOC), thresholds. We carried out scenario analyses. RESULTS: By 2050, the P&PI vaccine reduced RR/MDR-TB incidence rate by 71% (UI: 69-72) and 72% (UI: 70-74), and the PSI vaccine by 31% (UI: 30-32) and 44% (UI: 42-47) in China and India, respectively. In India, we found both USD 10 P&PI and PSI vaccines cost-effective at the 1-times GDP and upper HCOC thresholds and P&PI vaccines cost-effective at the lower HCOC threshold. In China, both vaccines were cost-effective at the 1-times GDP threshold. P&PI vaccine remained cost-effective at the lower HCOC threshold with 49% probability and PSI vaccines at the upper HCOC threshold with 21% probability. The P&PI vaccine was predicted to avert 0.9 million (UI: 0.8-1.1) and 1.1 million (UI: 0.9-1.4) second-line therapy regimens in China and India between 2027 and 2050, respectively. CONCLUSIONS: Novel TB vaccination is likely to substantially reduce the future burden of RR/MDR-TB, while averting the need for second-line therapy. Vaccination may be cost-effective depending on vaccine characteristics and setting

Modelling the effect of infection prevention and control measures on rate of Mycobacterium tuberculosis transmission to clinic attendees in primary health clinics in South Africa

Aaron S Karat - ORCID: 0000-0001-9643-664X https://orcid.org/0000-0001-9643-664XKarin Diaconu - ORCID: 0000-0002-5810-9725 https://orcid.org/0000-0002-5810-9725Karina Kielmann - ORCID: 0000-0001-5519-1658 https://orcid.org/0000-0001-5519-1658Background Elevated rates of tuberculosis in health care workers demonstrate the high rate of Mycobacterium tuberculosis (Mtb) transmission in health facilities in high burden settings. In the context of a project taking a whole systems approach to tuberculosis infection prevention and control (IPC), we aimed to evaluate the potential impact of conventional and novel IPC measures on Mtb transmission to patients and other clinic attendees.Methods An individual-based model of patient movements through clinics, ventilation in waiting areas, and Mtb transmission was developed, and parameterised using empirical data from eight clinics in two provinces in South Africa. Seven interventions – co-developed with health professionals and policymakers - were simulated: 1. queue management systems with outdoor waiting areas, 2. ultraviolet germicidal irradiation systems (UVGI), 3. appointment systems, 4. opening windows and doors, 5. surgical mask wearing by clinic attendees, 6. simple clinic retrofits, and 7. increased coverage of long antiretroviral therapy prescriptions and community medicine collection points through the CCMDD service.Results In the model, 1. outdoor waiting areas reduced the transmission to clinic attendees by 83% (interquartile range [IQR] 76-88%), 2. UVGI by 77% (IQR 64-85%), 3. appointment systems by 62% (IQR 45-75%), 4. opening windows and doors by 55% (IQR 25-72%), 5. masks by 47% (IQR 42-50%), 6. clinic retrofits by 45% (IQR 16-64%), and 7. increasing the coverage of CCMDD by 22% (IQR 12-32%).Conclusions The majority of the interventions achieved median reductions in the rate of transmission to clinic attendees of at least 45%, meaning that a range of highly effective intervention options are available, that can be tailored to the local context. Measures that are not traditionally considered to be IPC interventions, such as appointment systems, may be as effective as more traditional IPC measures, such as mask wearing.The support of the Economic and Social Research Council (IK) is gratefully acknowledged. The project is partly funded by the Antimicrobial Resistance Cross Council Initiative supported by the seven research councils in partnership with other funders including support from the GCRF. Grant reference: ES/P008011/1. NM is additionally funded the Wellcome Trust (218261/Z/19/Z). RGW is funded by the Wellcome Trust (218261/Z/19/Z), NIH (1R01AI147321-01), EDTCP (RIA208D-2505B), UK MRC (CCF17-7779 via SET Bloomsbury), ESRC (ES/P008011/1), BMGF (OPP1084276, OPP1135288 & INV-001754), and the WHO (2020/985800-0). TAY is funded via an NIHR Academic Clinical Fellowship. RMGHJ is funded by ERC (action number 757699)https://doi.org/10.1136/bmjgh-2021-0071246pubpub1