The Determinants of HIV Treatment Costs in Resource Limited Settings

Background: Governments and international donors have partnered to provide free HIV treatment to over 6 million individuals in low and middle-income countries. Understanding the determinants of HIV treatment costs will help improve efficiency and provide greater certainty about future resource needs. Methods and Findings: We collected data on HIV treatment costs from 54 clinical sites in Botswana, Ethiopia, Mozambique, Nigeria, Uganda, and Vietnam. Sites provided free HIV treatment funded by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR), national governments, and other partners. Service delivery costs were categorized into successive six-month periods from the date when each site began HIV treatment scale-up. A generalized linear mixed model was used to investigate relationships between site characteristics and per-patient costs, excluding ARV expenses. With predictors at their mean values, average annual per-patient costs were $177 (95$353 (255–468) for adult patients in the first 6 months of ART, and $222 (161–296) for adult patients on ART for >6 months (excludes ARV costs). Patient volume (no. patients receiving treatment) and site maturity (months since clinic began providing treatment services) were both strong independent predictors of per-patient costs. Controlling for other factors, costs declined by 43% (18–63) as patient volume increased from 500 to 5,000 patients, and by 28% (6–47) from 5,000 to 10,000 patients. For site maturity, costs dropped 41% (28–52) between months 0–12 and 25% (15–35) between months 12–24. Price levels (proxied by per-capita GDP) were also influential, with costs increasing by 22% (4–41) for each doubling in per-capita GDP. Additionally, the frequency of clinical follow-up, frequency of laboratory monitoring, and clinician-patient ratio were significant independent predictors of per-patient costs. Conclusions: Substantial reductions in per-patient service delivery costs occur as sites mature and patient cohorts increase in size. Other predictors suggest possible strategies to reduce per-patient costs

Cost-effectiveness of community-based screening and treatment of moderate acute malnutrition in Mali.

IntroductionModerate acute malnutrition (MAM) causes substantial child morbidity and mortality, accounting for 4.4% of deaths and 6.0% of disability-adjusted life years (DALY) lost among children under 5 each year. There is growing consensus on the need to provide appropriate treatment of MAM, both to reduce associated morbidity and mortality and to halt its progression to severe acute malnutrition. We estimated health outcomes, costs and cost-effectiveness of four dietary supplements for MAM treatment in children 6-35 months of age in Mali.MethodsWe conducted a cluster-randomised MAM treatment trial to describe nutritional outcomes of four dietary supplements for the management of MAM: ready-to-use supplementary foods (RUSF; PlumpySup); a specially formulated corn-soy blend (CSB) containing dehulled soybean flour, maize flour, dried skimmed milk, soy oil and a micronutrient pre-mix (CSB++; Super Cereal Plus); Misola, a locally produced, micronutrient-fortified, cereal-legume blend (MI); and locally milled flour (LMF), a mixture of millet, beans, oil and sugar, with a separate micronutrient powder. We used a decision tree model to estimate long-term outcomes and calculated incremental cost-effectiveness ratios (ICERs) comparing the health and economic outcomes of each strategy.ResultsCompared to no MAM treatment, MAM treatment with RUSF, CSB++, MI and LMF reduced the risk of death by 15.4%, 12.7%, 11.9% and 10.3%, respectively. The ICER was US$9821 per death averted (2015 USD) and US$347 per DALY averted for RUSF compared with no MAM treatment.ConclusionMAM treatment with RUSF is cost-effective across a wide range of willingness-to-pay thresholds.Trial registrationNCT01015950

Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies

Investing efficiently in future research to improve policy decisions is an important goal. Expected Value of Sample Information (EVSI) can be used to select the specific design and sample size of a proposed study by assessing the benefit of a range of different studies. Estimating EVSI with the standard nested Monte Carlo algorithm has a notoriously high computational burden, especially when using a complex decision model or when optimizing over study sample sizes and designs. Therefore, a number of more efficient EVSI approximation methods have been developed. However, these approximation methods have not been compared and therefore their relative advantages and disadvantages are not clear. A consortium of EVSI researchers, including the developers of several approximation methods, compared four EVSI methods using three previously published health economic models. The examples were chosen to represent a range of real-world contexts, including situations with multiple study outcomes, missing data, and data from an observational rather than a randomized study. The computational speed and accuracy of each method were compared, and the relative advantages and implementation challenges of the methods were highlighted. In each example, the approximation methods took minutes or hours to achieve reasonably accurate EVSI estimates, whereas the traditional Monte Carlo method took weeks. Specific methods are particularly suited to problems where we wish to compare multiple proposed sample sizes, when the proposed sample size is large, or when the health economic model is computationally expensive. All the evaluated methods gave estimates similar to those given by traditional Monte Carlo, suggesting that EVSI can now be efficiently computed with confidence in realistic examples.Comment: 11 pages, 3 figure

Population Health Impact and Cost-Effectiveness of Tuberculosis Diagnosis with Xpert MTB/RIF: A Dynamic Simulation and Economic Evaluation

Background: The Xpert MTB/RIF test enables rapid detection of tuberculosis (TB) and rifampicin resistance. The World Health Organization recommends Xpert for initial diagnosis in individuals suspected of having multidrug-resistant TB (MDR-TB) or HIV-associated TB, and many countries are moving quickly toward adopting Xpert. As roll-out proceeds, it is essential to understand the potential health impact and cost-effectiveness of diagnostic strategies based on Xpert. Methods and findings: We evaluated potential health and economic consequences of implementing Xpert in five southern African countries—Botswana, Lesotho, Namibia, South Africa, and Swaziland—where drug resistance and TB-HIV coinfection are prevalent. Using a calibrated, dynamic mathematical model, we compared the status quo diagnostic algorithm, emphasizing sputum smear, against an algorithm incorporating Xpert for initial diagnosis. Results were projected over 10- and 20-y time periods starting from 2012. Compared to status quo, implementation of Xpert would avert 132,000 (95% CI: 55,000–284,000) TB cases and 182,000 (97,000–302,000) TB deaths in southern Africa over the 10 y following introduction, and would reduce prevalence by 28% (14%–40%) by 2022, with more modest reductions in incidence. Health system costs are projected to increase substantially with Xpert, by US$460 million (294–699 million) over 10 y. Antiretroviral therapy for HIV represents a substantial fraction of these additional costs, because of improved survival in TB/HIV-infected populations through better TB case-finding and treatment. Costs for treating MDR-TB are also expected to rise significantly with Xpert scale-up. Relative to status quo, Xpert has an estimated cost-effectiveness of US$959 (633–1,485) per disability-adjusted life-year averted over 10 y. Across countries, cost-effectiveness ratios ranged from US$792 (482–1,785) in Swaziland to US$1,257 (767–2,276) in Botswana. Assessing outcomes over a 10-y period focuses on the near-term consequences of Xpert adoption, but the cost-effectiveness results are conservative, with cost-effectiveness ratios assessed over a 20-y time horizon approximately 20% lower than the 10-y values. Conclusions: Introduction of Xpert could substantially change TB morbidity and mortality through improved case-finding and treatment, with more limited impact on long-term transmission dynamics. Despite extant uncertainty about TB natural history and intervention impact in southern Africa, adoption of Xpert evidently offers reasonable value for its cost, based on conventional benchmarks for cost-effectiveness. However, the additional financial burden would be substantial, including significant increases in costs for treating HIV and MDR-TB. Given the fundamental influence of HIV on TB dynamics and intervention costs, care should be taken when interpreting the results of this analysis outside of settings with high HIV prevalence. Please see later in the article for the Editors' Summar

Predictive power of wastewater for nowcasting infectious disease transmission: A retrospective case study of five sewershed areas in Louisville, Kentucky

Background: Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. Methods: We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. Findings: Adding wastewater data minimally improved the predictive performance of nowcasts compared to a model fitted to case and death data (Weighted Interval Score (WIS) 0.208 versus 0.223), and reduced the predictive performance compared to a model fitted to deaths data (WIS 0.517 versus 0.500). Adding wastewater data to deaths data improved the nowcasts agreement to estimates from models using cases and deaths data. These findings were consistent across individual sewersheds as well as for models fit to the aggregated total data of 5 sewersheds. Retrospective reconstructions of epidemiological dynamics created using different combinations of data were in general agreement (coverage \u3e75%). Interpretation: These findings show wastewater data may be valuable for infectious disease nowcasting when clinical surveillance data are absent, such as early in a pandemic or in low-resource settings where systematic collection of epidemiologic data is difficult

Estimators Used in Multisite Healthcare Costing Studies in Low- and Middle-Income Countries: A Systematic Review and Simulation Study.

BACKGROUND: In low- and middle-income countries, multisite costing studies are increasingly used to estimate healthcare program costs. These studies have employed a variety of estimators to summarize sample data and make inferences about overall program costs. OBJECTIVE: We conducted a systematic review and simulation study to describe these estimation methods and quantify their performance in terms of expected bias and variance. METHODS: We reviewed the published literature through January 2017 to identify multisite costing studies conducted in low- and middle-income countries and extracted data on analytic approaches. To assess estimator performance under realistic conditions, we conducted a simulation study based on 20 empirical cost data sets. RESULTS: The most commonly used estimators were the volume-weighted mean and the simple mean, despite theoretical reasons to expect bias in the simple mean. When we tested various estimators in realistic study scenarios, the simple mean exhibited an upward bias ranging from 12% to 113% of the true cost across a range of study sample sizes and data sets. The volume-weighted mean exhibited minimal bias and substantially lower root mean squared error. Further gains were possible using estimators that incorporated auxiliary information on delivery volumes. CONCLUSIONS: The choice of summary estimator in multisite costing studies can significantly influence study findings and, therefore, the economic analyses they inform. Use of the simple mean to summarize the results of multisite costing studies should be considered inappropriate. Our study demonstrates that several alternative better-performing methods are available

Who's afraid of the big bad wolf: a prospective paradigm to test Rachman's indirect pathways in children

Rachman's theory [The conditioning theory of fear insition: a critical examination. Behav. Res. Ther. 15 (1977) 375–387] of fear acquisition suggests that fears and phobias can be acquired through three pathways: direct conditioning, vicarious learning and information/instruction. Although retrospective studies have provided some evidence for these pathways in the development of phobias during childhood [see King, Gullone, & Ollendick, Etiology of childhood phobias: current status of Rachman's three pathway's theory. Behav. Res. Ther. 36 (1998) 297–309 for a review], these studies have relied on long-term past memories of adult phobics or their parents. The current study was aimed towards developing a paradigm in which the plausibility of Rachman's indirect pathways could be investigated prospectively. In Experiment 1, children aged between 7 and 9 were presented with two types of information about novel stimuli (two monsters): video information and verbal information in the form of a story. Fear-related beliefs about the monsters changed significantly as a result of verbal information but not video information. Having established an operational paradigm, Experiment 2 looked at whether the source of verbal information had an effect on changes in fear-beliefs. Using the same paradigm, information about the monsters was provided by either a teacher, an adult stranger or a peer, or no information was given. Again, verbal information significantly changed fear-beliefs, but only when the information came from an adult. The role of information in the acquisition of fear and maintenance of avoidant behaviour is discussed with reference to modern conditioning theories of fear acquisition

Determinants of cost of routine immunization programme in India

The costs of delivering routine immunization services in India vary widely across facilities, districts and states. Understanding the factors influencing this cost variation could help predict future immunization costs and suggest approaches for improving the efficiency of service provision. We examined determinants of facility cost for immunization services based on a nationally representative sample of sub-centres and primary health centres (99 and 89 facilities, respectively) by regressing logged total facility costs, both including and excluding vaccine cost, against several explanatory variables. We used a multi-level regression model to account for the multi-stage sampling design, including state- and district-level random effects. We found that facility costs were significantly associated with total doses administered, type of facility, salary of the main vaccinator, number of immunization sessions, and the distance of the facility from the nearest cold chain point. Use of pentavalent vaccine by the state was an important determinant of total facility cost including vaccine cost. India is introducing several new vaccines including some supported by Gavi. Therefore, the government will have to ensure that additional resources will be made available after the support from Gavi ceases

Uncertainty in tuberculosis clinical decision-making: An umbrella review with systematic methods and thematic analysis

Tuberculosis is a major infectious disease worldwide, but currently available diagnostics have suboptimal accuracy, particularly in patients unable to expectorate, and are often unavailable at the point-of-care in resource-limited settings. Test/treatment decision are, therefore, often made on clinical grounds. We hypothesized that contextual factors beyond disease probability may influence clinical decisions about when to test and when to treat for tuberculosis. This umbrella review aimed to identify such factors, and to develop a framework for uncertainty in tuberculosis clinical decision-making. Systematic reviews were searched in seven databases (MEDLINE, CINAHL Complete, Embase, Scopus, Cochrane, PROSPERO, Epistemonikos) using predetermined search criteria. Findings were classified as barriers and facilitators for testing or treatment decisions, and thematically analysed based on a multi-level model of uncertainty in health care. We included 27 reviews. Study designs and primary aims were heterogeneous, with seven meta-analyses and three qualitative evidence syntheses. Facilitators for decisions to test included providers’ advanced professional qualification and confidence in tests results, availability of automated diagnostics with quick turnaround times. Common barriers for requesting a diagnostic test included: poor provider tuberculosis knowledge, fear of acquiring tuberculosis through respiratory sampling, scarcity of healthcare resources, and complexity of specimen collection. Facilitators for empiric treatment included patients’ young age, severe sickness, and test inaccessibility. Main barriers to treatment included communication obstacles, providers’ high confidence in negative test results (irrespective of negative predictive value). Multiple sources of uncertainty were identified at the patient, provider, diagnostic test, and healthcare system levels. Complex determinants of uncertainty influenced decision-making. This could result in delayed or missed diagnosis and treatment opportunities. It is important to understand the variability associated with patient-provider clinical encounters and healthcare settings, clinicians’ attitudes, and experiences, as well as diagnostic test characteristics, to improve clinical practices, and allow an impactful introduction of novel diagnostics