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Background In recent years there has been a growth in economic evaluations that consider indirect health benefits to populations due to advances in mathematical modeling. In addition, economic evaluations guidelines have suggested the inclusion of impact inventories to include non-health direct and indirect consequences. We aim to bring together this literature, together with the broader literature on internalities and externalities to propose a comprehensive approach for analysts to identify and characterize all unintended consequences in economic evaluations. Methods We present a framework to assist analysts identify and characterize additional costs and effects beyond that of direct health impact primarily intended to be influenced by the intervention/technology. We build on previous checklists to provide analysts with a comprehensive framework to justify the inclusion or exclusion of effects, supporting the use of current guidelines, to ensure any unintended effects are considered. We illustrate this framework with examples from immunization. These were identified from a previous systematic review, PhD thesis work, and general search scoping in PubMed databases. Results We present a comprehensive framework to consider additional consequences, exemplified by types and categories. We bring this and other guidance together to assist analysts identify possible unintended consequences whether taking a provider or societal perspective. Conclusions Although there are many challenges ahead to standardize the inclusion of additional consequences in economic evaluation, we hope by moving beyond generic statements to reporting against a comprehensive framework of additional effects we can support further consistency in this aspect of cost-effectiveness analysis going forward.

Background There is a need for easily accessible tuberculosis unit cost data, as well as an understanding of the variability of methods used and reporting standards of that data. Objective The aim of this systematic review was to descriptively review papers reporting tuberculosis unit costs from a healthcare provider perspective looking at methodological variation; to assess quality using a study quality rating system and machine learning to investigate the indicators of reporting quality; and to identify the data gaps to inform standardised tuberculosis unit cost collection and consistent principles for reporting going forward. Methods We searched grey and published literature in five sources and eight databases, respectively, using search terms linked to cost, tuberculosis and tuberculosis health services including tuberculosis treatment and prevention. For inclusion, the papers needed to contain empirical unit cost estimates for tuberculosis interventions from low- and middle-income countries, with reference years between 1990 and 2018. A total of 21,691 papers were found and screened in a phased manner. Data were extracted from the eligible papers into a detailed Microsoft Excel tool, extensively cleaned and analysed with R software (R Project, Vienna, Austria) using the user interface of RStudio. A study quality rating was applied to the reviewed papers based on the inclusion or omission of a selection of variables and their relative importance. Following this, machine learning using a recursive partitioning method was utilised to construct a classification tree to assess the reporting quality. Results This systematic review included 103 provider perspective papers with 627 unit costs (costs not presented here) for tuberculosis interventions among a total of 140 variables. The interventions covered were active, passive and intensified case finding; tuberculosis treatment; above-service costs; and tuberculosis prevention. Passive case finding is the detection of tuberculosis cases where individuals self-identify at health facilities; active case finding is detection of cases of those not in health facilities, such as through outreach; and intensified case finding is detection of cases in high-risk populations. There was heterogeneity in some of the reported methods used such cost allocation, amortisation and the use of top-down, bottom-up or mixed approaches to the costing. Uncertainty checking through sensitivity analysis was only reported on by half of the papers (54%), while purposive and convenience sampling was reported by 72% of papers. Machine learning indicated that reporting on ‘Intervention’ (in particular), ‘Urbanicity’ and ‘Site Sampling’, were the most likely indicators of quality of reporting. The largest data gap identified was for tuberculosis vaccination cost data, the Bacillus Calmette–Guérin (BCG) vaccine in particular. There is a gap in available unit costs for 12 of 30 high tuberculosis burden countries, as well as for the interventions of above-service costs, tuberculosis prevention, and active and intensified case finding. Conclusion Variability in the methods and reporting used makes comparison difficult and makes it hard for decision makers to know which unit costs they can trust. The study quality rating system used in this review as well as the classification tree enable focus on specific reporting aspects that should improve variability and increase confidence in unit costs. Researchers should endeavour to be explicit and transparent in how they cost interventions following the principles as laid out in the Global Health Cost Consortium’s Reference Case for Estimating the Costs of Global Health Services and Interventions, which in turn will lead to repeatability, comparability and enhanced learning from others.

Background and Objective In context of the End TB goal of zero tuberculosis (TB)-affected households encountering catastrophic costs due to TB by 2020, the estimation of national prevalence of catastrophic costs due to TB is a priority to inform programme design. We explore approaches to estimate the national prevalence of catastrophic costs due to TB from existing datasets as an alternative to nationally representative surveys. Methods We obtained, standardized and merged three patient-level datasets from existing studies on patient-incurred costs due to TB in South Africa. A deterministic cohort model was developed with the aim of estimating the national prevalence of catastrophic costs, using national data on the prevalence of TB and likelihood of loss to follow-up by income quintile and HIV status. Two approaches were tested to parameterize the model with existing cost data. First, a meta-analysis summarized study-level data by HIV status and income quintile. Second, a regression analysis of patient-level data also included employment status, education level and urbanicity. We summarized findings by type of cost and examined uncertainty around resulting estimates. Results Overall, the median prevalence of catastrophic costs for the meta-analysis and regression approaches were 11% (interquartile range [IQR] 9–13%) and 6% (IQR 5–8%), respectively. Both approaches indicated that the main burden of catastrophic costs falls on the poorest households. An individual-level regression analysis produced lower uncertainty around estimates than a study-level meta-analysis. Conclusions This paper presents a novel application of existing data to estimate the national prevalence of catastrophic costs due to TB. This type of model could be useful for researchers and policy makers looking to inform certain policy decisions; however, some uncertainties remain due to limitations in data availability. There is an urgent need for standardized reporting of cost data and improved guidance on methods to collect income data to improve these estimates going forward.

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., Highlights • Health system constraints such as financial, human resources, and diagnostic inputs scarcity can influence the opportunity costs of health interventions and prevent the efficient allocation of resources. Methods for empirical estimation and inclusion of these constraints in priority setting are underdeveloped, particularly for application in low- and middle-income settings. • We propose an approach that can be applied using routine data and that, crucially, presents decision makers with a choice set including constrained and unconstrained scale-up options as well as, crucially, the option of relaxing the health system constraints. The approach is illustrated using a case study of developing an essential tuberculosis control package in South Africa. • We find that taking health system constraints into account changes the cost-effectiveness ranking of intervention options, demonstrating their importance for priority setting. We demonstrate that the approach is feasible within a policy-driven timeline.

Background: Even with good progress on vaccination, SARS-CoV-2 infections in the UK may continue to impose a high burden of disease and therefore pose substantial challenges for health policy decision makers. Stringent government-mandated physical distancing measures (lockdown) have been demonstrated to be epidemiologically effective, but can have both positive and negative economic consequences. The duration and frequency of any intervention policy could, in theory, could be optimized to maximize economic benefits while achieving substantial reductions in disease.Methods: Here, we use a pre-existing SARS-CoV-2 transmission model to assess the health and economic implications of different strengths of control through time in order to identify optimal approaches to non-pharmaceutical intervention stringency in the UK, considering the role of vaccination in reducing the need for future physical distancing measures. The model is calibrated to the COVID-19 epidemic in England and we carry out retrospective analysis of the optimal timing of precautionary breaks in 2020 and the optimal relaxation policy from the January 2021 lockdown, considering the willingness to pay (WTP) for health improvement.Results: We find that the precise timing and intensity of interventions is highly dependent upon the objective of control. As intervention measures are relaxed, we predict a resurgence in cases, but the optimal intervention policy can be established dependent upon the WTP per quality adjusted life year loss avoided. Our results show that establishing an optimal level of control can result in a reduction in net monetary loss of billions of pounds, dependent upon the precise WTP value.Conclusion: It is vital, as the UK emerges from lockdown, but continues to face an on-going pandemic, to accurately establish the overall health and economic costs when making policy decisions. We demonstrate how some of these can be quantified, employing mechanistic infectious disease transmission models to establish optimal levels of control for the ongoing COVID-19 pandemic.

Additional file 1: Top down unit costs in 2013 and 2014 of visit (USD) for any illness, children under 5.

Additional file 1. Annexure.

IntroductionNosocomialMycobacterium tuberculosis(Mtb) transmission substantially impacts health workers, patients and communities. Guidelines for tuberculosis infection prevention and control (TB IPC) exist but implementation in many settings remains suboptimal. Evidence is needed on cost-effective investments to preventMtbtransmission that are feasible in routine clinic environments.MethodsA set of TB IPC interventions was codesigned with local stakeholders using system dynamics modelling techniques that addressed both core activities and enabling actions to support implementation. An economic evaluation of these interventions was conducted at two clinics in KwaZulu-Natal, employing agent-based models ofMtbtransmission within the clinics and in their catchment populations. Intervention costs included the costs of the enablers (eg, strengthened supervision, community sensitisation) identified by stakeholders to ensure uptake and adherence.ResultsAll intervention scenarios modelled, inclusive of the relevant enablers, cost less than US$200 per disability-adjusted life-year (DALY) averted and were very cost-effective in comparison to South Africa’s opportunity cost-based threshold (US$3200 per DALY averted). Two interventions, building modifications to improve ventilation and maximising use of the existing Central Chronic Medicines Dispensing and Distribution system to reduce the number of clinic attendees, were found to be cost saving over the 10-year model time horizon. Incremental cost-effectiveness ratios were sensitive to assumptions on baseline clinic ventilation rates, the prevalence of infectious TB in clinic attendees and future HIV incidence but remained highly cost-effective under all uncertainty analysis scenarios.ConclusionTB IPC interventions in clinics, including the enabling actions to ensure their feasibility, afford very good value for money and should be prioritised for implementation within the South African health system.

IntroductionBy 2022, high levels of past COVID-19 infections, combined with substantial levels of vaccination and the development of Omicron, have shifted country strategies towards burden reduction policies. SARS-CoV-2 rapid antigen tests (rapid diagnostic tests (RDTs)) could contribute to these policies by helping rapidly detect, isolate and/or treat infections in different settings. However, the evidence to inform RDT policy choices in low and middle-income countries (LMICs) is limited.MethodWe provide an overview of the potential impact of several RDT use cases (surveillance; testing, tracing and isolation without and with surveillance; hospital-based screening to reduce nosocomial COVID-19; and testing to enable earlier/expanded treatment) for a range of country settings. We use conceptual models and literature review to identify which use cases are likely to bring benefits and how these may change with outbreak characteristics. Impacts are measured through multiple outcomes related to gaining time, reducing the burden on the health system and reducing deaths.ResultsIn an optimal scenario in terms of resources and capacity and with baseline parameters, we find marginal time gains of 4 days or more through surveillance and testing tracing and isolation with surveillance, a reduction in peak intensive care unit (ICU) or ICU admissions by 5% or more (hospital-based screening; testing, tracing and isolation) and reductions in COVID-19 deaths by over 6% (hospital-based screening; test and treat). Time gains may be used to strengthen ICU capacity and/or boost vulnerable individuals, though only a small minority of at-risk individuals could be reached in the time available. The impact of RDTs declines with lower country resources and capacity, more transmissible or immune-escaping variants and reduced test sensitivity.ConclusionRDTs alone are unlikely to dramatically reduce the burden of COVID-19 in LMICs, though they may have an important role alongside other interventions such as vaccination, therapeutic drugs, improved healthcare capacity and non-pharmaceutical measures.

To better understand and plan health systems featuring multiple levels and complex causal elements, there have been increasing attempts to incorporate tools arising from complexity science to inform decisions. The utilization of new planning approaches can have important implications for the types of evidence that inform health policymaking and the mechanisms through which they do so. This paper presents an empirical analysis of the application of one such tool—system dynamics modelling (SDM)—within a tuberculosis control programme in South Africa in order to explore how SDM was utilized, and to reflect on the implications for evidence-informed health policymaking. We observed group model building workshops that served to develop the SDM process and undertook 19 qualitative interviews with policymakers and practitioners who partook in these workshops. We analysed the relationship between the SDM process and the use of evidence for policymaking through four conceptual perspectives: (1) a rationalist knowledge-translation view that considers how previously-generated research can be taken up into policy; (2) a programmatic approach that considers existing goals and tasks of decision-makers, and how evidence might address them; (3) a social constructivist lens exploring how the process of using an evidentiary planning tool like SDM can shape the understanding of problems and their solutions; and (4) a normative perspective that recognizes that stakeholders may have different priorities, and thus considers which groups are included and represented in the process. Each perspective can provide useful insights into the SDM process and the political nature of evidence use. In particular, SDM can provide technical information to solve problems, potentially leave out other concerns and influence how problems are conceptualized by formalizing the boundaries of the policy problem and delineating particular solution sets. Undertaking the process further involves choices on stakeholder inclusion affecting whose interests may be served as evidence to inform decisions.

Background Globally, nearly half of all deaths among children under the age of 5 years can be attributed to malaria, diarrhoea, and pneumonia. A significant proportion of these deaths occur in sub-Saharan Africa. Despite several programmes implemented in sub-Saharan Africa, the burden of these illnesses remains persistently high. To mobilise resources for such programmes it is necessary to evaluate their costs, costs-effectiveness, and affordability. This study aimed to estimate the provider costs of treating malaria, diarrhoea, and pneumonia among children under the age of 5 years in routine settings at the health facility level in rural Uganda and Mozambique. Methods Service and cost data was collected from health facilities in midwestern Uganda and Inhambane province, Mozambique from private and public health facilities. Financial and economic costs of providing care for childhood illnesses were investigated from the provider perspective by combining a top-down and bottom-up approach to estimate unit costs and annual total costs for different types of visits for these illnesses. All costs were collected in Ugandan shillings and Mozambican meticais. Costs are presented in 2021 US dollars. Results In Uganda, the highest number of outpatient visits were for children with uncomplicated malaria and of inpatient admissions were for respiratory infections, including pneumonia. The highest unit cost for outpatient visits was for pneumonia (and other respiratory infections) and ranged from $0.5 to 2.3, while the highest unit cost for inpatient admissions was for malaria ($19.6). In Mozambique, the highest numbers of outpatient and inpatient admissions visits were for malaria. The highest unit costs were for malaria too, ranging from $2.5 to 4.2 for outpatient visits and $3.8 for inpatient admissions. The greatest contributors to costs in both countries were drugs and diagnostics, followed by staff. Conclusions The findings highlighted the intensive resource use in the treatment of malaria and pneumonia for outpatient and inpatient cases, particularly at higher level health facilities. Timely treatment to prevent severe complications associated with these illnesses can also avoid high costs to health providers, and households. Trial registration: ClinicalTrials.gov, identifier: NCT01972321.

ObjectivesPatients with highly resistant tuberculosis have few treatment options. Bedaquiline, pretomanid and linezolid regimen (BPaL) is a new regimen shown to have favourable outcomes after six months. We present an economic evaluation of introducing BPaL against the extensively drug-resistant tuberculosis (XDR-TB) standard of care in three epidemiological settings.DesignCost-effectiveness analysis using Markov cohort model.SettingSouth Africa, Georgia and the Philippines.ParticipantsXDR-TB and multidrug-resistant tuberculosis (MDR-TB) failure and treatment intolerant patients.InterventionsBPaL regimen.Primary and secondary outcome measures(1) Incremental cost per disability-adjusted life years averted by using BPaL against standard of care at the Global Drug Facility list price. (2) The potential maximum price at which the BPaL regimen could become cost neutral.ResultsBPaL for XDR-TB is likely to be cost saving in all study settings when pretomanid is priced at the Global Drug Facility list price. The magnitude of these savings depends on the prevalence of XDR-TB in the country and can amount, over 5 years, to approximately US$ 3 million in South Africa, US$ 200 000 and US$ 60 000 in Georgia and the Philippines, respectively. In South Africa, related future costs of antiretroviral treatment (ART) due to survival of more patients following treatment with BPaL reduced the magnitude of expected savings to approximately US$ 1 million. Overall, when BPaL is introduced to a wider population, including MDR-TB treatment failure and treatment intolerant, we observe increased savings and clinical benefits. The potential threshold price at which the probability of the introduction of BPaL becoming cost neutral begins to increase is higher in Georgia and the Philippines (US$ 3650 and US$ 3800, respectively) compared with South Africa (US$ 500) including ART costs.ConclusionsOur results estimate that BPaL can be a cost-saving addition to the local TB programmes in varied programmatic settings.

BACKGROUND: Patient-centred care along with optimal financing of inpatient and outpatient services are the main priorities of the Georgia National TB Programme (NTP). This paper presents TB diagnostics and treatment unit cost, their comparison with NTP tariffs and how the study findings informed TB financing policy.METHODS: Top-down (TD) and bottom-up (BU) mean unit costs for TB interventions by episode of care were calculated. TD costs were compared with NTP tariffs, and variations in these and the unit costs cost composition between public and private facilities was assessed.RESULTS: Outpatient interventions costs exceeded NTP tariffs. Unit costs in private facilities were higher compared with public providers. There was very little difference between per-day costs for drug-susceptible treatment and NTP tariffs in case of inpatient services. Treatment day financing exceeded actual costs in the capital (public facility) for drug-resistant TB, and this was lower in the regions.CONCLUSION: Use of reliable unit costs for TB services at policy discussions led to a shift from per-day payment to a diagnosis-related group model in TB inpatient financing in 2020. A next step will be informing policy decisions on outpatient TB care financing to reduce the existing gap between funding and costs.

BACKGROUND: There is a dearth of economic analysis required to support increased investment in TB in India. This study estimates the costs of TB services from a health systems´ perspective to facilitate the efficient allocation of resources by India´s National Tuberculosis Elimination Programme.METHODS: Data were collected from a multi-stage, stratified random sample of 20 facilities delivering TB services in two purposively selected states in India as per Global Health Cost Consortium standards and using Value TB Data Collection Tool. Unit costs were estimated using the top-down (TD) and bottom-up (BU) methodology and are reported in 2018 US dollars.RESULTS: Cost of delivering 50 types of TB services and four interventions varied according to costing method. Key services included sputum smear microscopy, Xpert® MTB/RIF and X-ray with an average BU costs of respectively US$2.45, US$17.36 and US$2.85. Average BU cost for bacille Calmette-Guérin vaccination, passive case-finding, TB prevention in children under 5 years using isoniazid and first-line drug treatment in new pulmonary and extrapulmonary TB cases was respectively US$0.76, US$1.62, US$2.41, US$103 and US$98.CONCLUSION: The unit cost of TB services and outputs are now available to support investment decisions, as diagnosis algorithms are reviewed and prevention or treatment for TB are expanded or updated in India.

ObjectivesCOVID-19 has altered health sector capacity in low-income and middle-income countries (LMICs). Cost data to inform evidence-based priority setting are urgently needed. Consequently, in this paper, we calculate the full economic health sector costs of COVID-19 clinical management in 79 LMICs under different epidemiological scenarios.MethodsWe used country-specific epidemiological projections from a dynamic transmission model to determine number of cases, hospitalisations and deaths over 1 year under four mitigation scenarios. We defined the health sector response for three base LMICs through guidelines and expert opinion. We calculated costs through local resource use and price data and extrapolated costs across 79 LMICs. Lastly, we compared cost estimates against gross domestic product (GDP) and total annual health expenditure in 76 LMICs.ResultsCOVID-19 clinical management costs vary greatly by country, ranging between ConclusionsWe present the first dataset of COVID-19 clinical management costs across LMICs. These costs can be used to inform decision-making on priority setting. Our results show that COVID-19 clinical management costs in LMICs are substantial, even in scenarios of moderate social distancing. Low-income countries are particularly vulnerable and some will struggle to cope with almost any epidemiological scenario. The choices facing LMICs are likely to remain stark and emergency financial support will be needed.

Background The nationwide lockdown (March 25 to June 8, 2020) to curb the spread of coronavirus infection had significant health and economic impacts on the Indian economy. There is limited empirical evidence on how COVID-19 restrictive measures may impact the economic welfare of specific groups of patients, e.g., tuberculosis patients. We provide the first such evidence for India. Methods A total of 291 tuberculosis patients from the general population and from a high-risk group, patients from tea garden areas, were interviewed at different time points to understand household income loss during the complete lockdown, three and eight months after the complete lockdown was lifted. Income loss was estimated by comparing net monthly household income during and after lockdown with prelockdown income. Tuberculosis service utilization patterns before and during the lockdown period also were examined. Household income loss, travel and other expenses related to tuberculosis drug pickup were presented in 2020 US dollars (1 US$ = INR 74.132). Results 26% of households with tuberculosis patients in tea garden areas and 51% of households in the general population had zero monthly income during the complete lockdown months (April–May 2020). Overall income loss slowly recovered during July–August compared to April–May 2020. Approximately 7% of patients in the general population and 4% in tea garden areas discontinued their tuberculosis medicines because of the complete lockdown. Conclusion Discontinuation of medicine will have an additional burden on the tuberculosis elimination program in terms of additional cases, including multidrug resistant tuberculosis cases. Income loss for households and poor restoration of income after the lockdown will likely have an impact on the nutrition of tuberculosis patients and families. Tuberculosis patients working in the informal sector were the worst affected group during the nationwide lockdown. This emphasizes that a policy priority must continue to protect those working in informal sectors from the economic consequences of such restrictive measures, including paid sick leave, additional food support, and direct benefit transfers. Alongside ensuring widespread access to COVID-19 vaccines, these policy actions remain pivotal in ensuring the well-being of those who are unfortunate enough to be living with tuberculosis.

Background Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million). Methods and findings We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5-year duration of protection is likely to avert around 0.9 (95% credible interval (CrI): 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths, and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question. Conclusions COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries., In a modelling study, Carl A B Pearson and coauthors investigate the health impact and cost-effectiveness of various COVID-19 vaccination scenarios in Sindh Province, Pakistan, Author summary Why was this study done? The evidence base for health and economic impact of Coronavirus Disease 2019 (COVID-19) vaccination in low- and middle-income settings is limited. Searching PubMed, medRxiv, and econLit using the search term (“coronavirus” OR “covid” OR “ncov”) AND (“vaccination” OR “immunisation”) AND (“model” OR “cost” OR “economic”) for full text articles published in any language between 1 January 2020 and 20 January 2021, returned 29 (PubMed), 1,167 (medRxiv), and 0 (econLit) studies: 20 overall were relevant, with only 4 exclusively focused on low- or middle-income countries (India, China, Mexico), while 3 multicountry analyses also included low- or middle-income settings. However, only 3 of these studies are considered economic outcomes, all of them comparing the costs of vaccination to the costs of nonpharmaceutical interventions (NPIs) and concluding that both are necessary to reduce infections and maximise economic benefit. The majority of studies focus on high-income settings and conclude that prioritizing COVID-19 vaccination to older age groups is the preferred strategy to minimise mortality, particularly when vaccine supplies are constrained, while other age- or occupational risk groups should be prioritised when vaccine availability increases or when other policy objectives are pursued. What did the researchers do and find? We combined epidemiological and economic analysis of COVID-19 vaccination based on real-world disease and programmatic information in the Sindh Province of Pakistan. We found that vaccination in this setting is likely to be highly cost-effective, and even cost saving, as long as the vaccine is reasonably priced and efficacy is high. Unlike studies in high-income settings, we also found that vaccination programmes targeting all adults may have almost as much benefit as those initially targeted at older populations, likely reflecting the higher previous infection rates and different demography in these settings. What do these findings mean? The results suggest that low- and middle-income countries (LMICs) see less benefit to initially prioritising vaccination of older (65+) populations compared to unprioritised distribution. Factors outside this analysis, like cost differences between prioritised and unprioritised programmes, will further influence the preferred approach. As such, LMICs and international bodies providing guidance for LMICs need to consider evidence specific to these settings when making recommendations about COVID-19 vaccination. Further data and model-based analyses in such settings are urgently needed in order to ensure that vaccination decisions are appropriate to these contexts.

OBJECTIVE: To undertake a cost-effectiveness analysis of a Community-based Hypertension Improvement Project (ComHIP) compared with standard hypertension care in Ghana. DESIGN: Cost-effectiveness analysis using a Markov model. SETTING: Lower Manya Krobo, Eastern Region, Ghana. INTERVENTION: We evaluated ComHIP, an intervention with multiple components, including: community-based education on cardiovascular disease (CVD) risk factors and healthy lifestyles; community-based screening and monitoring of blood pressure by licensed chemical sellers and CVD nurses; community-based diagnosis, treatment, counselling, follow-up and referral of hypertension patients by CVD nurses; telemedicine consultation by CVD nurses and referral of patients with severe hypertension and/or organ damage to a physician; information and communication technologies messages for healthy lifestyles, treatment adherence support and treatment refill reminders for hypertension patients; Commcare, a cloud-based health records system linked to short-message service (SMS)/voice messaging for treatment adherence, reminders and health messaging. ComHIP was evaluated under two scale-up scenarios: (1) ComHIP as currently implemented with support from international partners and (2) ComHIP under full local implementation. MAIN OUTCOME MEASURES: Incremental cost per disability-adjusted life-year (DALY) averted from a societal perspective over a time horizon of 10 years. RESULTS: ComHIP is unlikely to be a cost-effective intervention, with current ComHIP implementation and ComHIP under full local implementation costing on average US$12 189 and US$6530 per DALY averted, respectively. Results were robust to uncertainty analyses around model parameters. CONCLUSIONS: High overhead costs and high patient costs in ComHIP suggest that the societal costs of ensuring appropriate hypertension care are high and may not produce sufficient impact to achieve cost-effective implementation. However, these results are limited by the evidence quality of the effectiveness estimates, which comes from observational data rather than from randomised controlled study design.

ObjectiveTo undertake a cost-effectiveness analysis of a Community-based Hypertension Improvement Project (ComHIP) compared with standard hypertension care in Ghana.DesignCost-effectiveness analysis using a Markov model.SettingLower Manya Krobo, Eastern Region, Ghana.InterventionWe evaluated ComHIP, an intervention with multiple components, including: community-based education on cardiovascular disease (CVD) risk factors and healthy lifestyles; community-based screening and monitoring of blood pressure by licensed chemical sellers and CVD nurses; community-based diagnosis, treatment, counselling, follow-up and referral of hypertension patients by CVD nurses; telemedicine consultation by CVD nurses and referral of patients with severe hypertension and/or organ damage to a physician; information and communication technologies messages for healthy lifestyles, treatment adherence support and treatment refill reminders for hypertension patients; Commcare, a cloud-based health records system linked to short-message service (SMS)/voice messaging for treatment adherence, reminders and health messaging. ComHIP was evaluated under two scale-up scenarios: (1) ComHIP as currently implemented with support from international partners and (2) ComHIP under full local implementation.Main outcome measuresIncremental cost per disability-adjusted life-year (DALY) averted from a societal perspective over a time horizon of 10 years.ResultsComHIP is unlikely to be a cost-effective intervention, with current ComHIP implementation and ComHIP under full local implementation costing on average US$12 189 and US$6530 per DALY averted, respectively. Results were robust to uncertainty analyses around model parameters.ConclusionsHigh overhead costs and high patient costs in ComHIP suggest that the societal costs of ensuring appropriate hypertension care are high and may not produce sufficient impact to achieve cost-effective implementation. However, these results are limited by the evidence quality of the effectiveness estimates, which comes from observational data rather than from randomised controlled study design.

Background How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes. Methods We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed. Results The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage. Conclusion The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.

BackgroundTransmission of respiratory pathogens, such as Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2, is more likely during close, prolonged contact and when sharing a poorly ventilated space. In clinics in KwaZulu-Natal (KZN) and Western Cape (WC), South Africa, we estimated clinic visit duration, time spent indoors and outdoors, and occupancy density of waiting rooms.MethodsWe used unique barcodes to track attendees’ movements in 11 clinics in two provinces, multiple imputation to estimate missing arrival and departure times, and mixed-effects linear regression to examine associations with visit duration.Results2,903 attendees were included. Median visit duration was 2 hours 36 minutes (interquartile range [IQR] 01:36–3:43). Longer mean visit times were associated with being female (13.5 minutes longer than males; pOverall, attendees spent more of their time indoors (median 95.6% [IQR 46–100]) than outdoors (2.5% [IQR 0–35]). Attendees at clinics with outdoor waiting areas spent a greater proportion (median 13.7% [IQR 1– 75]) of their time outdoors.In two clinics in KZN (no appointment system), occupancy densities of ∼2.0 persons/m2 were observed in smaller waiting rooms during busy periods. In one clinic in WC (appointment system), occupancy density did not exceed 1.0 persons/m2 despite higher overall attendance.ConclusionsLonger waiting times were associated with early arrival, being female, and attending with a young child. Attendees generally waited where they were asked to. Regular estimation of occupancy density (as patient flow proxy) may help staff assess for risk of infection transmission and guide intervention to reduce time spent in risky spaces.

BackgroundTransmission of respiratory pathogens, such as Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2, is more likely during close, prolonged contact and when sharing a poorly ventilated space. In clinics in KwaZulu-Natal (KZN) and Western Cape (WC), South Africa, we estimated clinic visit duration, time spent indoors and outdoors, and occupancy density of waiting rooms.MethodsWe used unique barcodes to track attendees’ movements in 11 clinics in two provinces, multiple imputation to estimate missing arrival and departure times, and mixed-effects linear regression to examine associations with visit duration.Results2,903 attendees were included. Median visit duration was 2 hours 36 minutes (interquartile range [IQR] 01:36–3:43). Longer mean visit times were associated with being female (13.5 minutes longer than males; pOverall, attendees spent more of their time indoors (median 95.6% [IQR 46–100]) than outdoors (2.5% [IQR 0–35]). Attendees at clinics with outdoor waiting areas spent a greater proportion (median 13.7% [IQR 1– 75]) of their time outdoors.In two clinics in KZN (no appointment system), occupancy densities of ∼2.0 persons/m2 were observed in smaller waiting rooms during busy periods. In one clinic in WC (appointment system), occupancy density did not exceed 1.0 persons/m2 despite higher overall attendance.ConclusionsLonger waiting times were associated with early arrival, being female, and attending with a young child. Attendees generally waited where they were asked to. Regular estimation of occupancy density (as patient flow proxy) may help staff assess for risk of infection transmission and guide intervention to reduce time spent in risky spaces.

Objective: Explore facility-level average costs per client of HIV testing and counselling (HTC) and voluntary medical male circumcision (VMMC) services in 13 countries.Methods: Through a literature search we identified studies that reported facility-level costs of HTC or VMMC programmes. We requested the primary data from authors and standardised the disparate data sources to make them comparable. We then conducted descriptive statistics and a meta-analysis to assess the cost variation among facilities. All costs were converted to 2017 US dollars ($).Results: We gathered data from 14 studies across 13 countries and 772 facilities (552 HTC, 220 VMMC). The weighted average unit cost per client served was $15 (95% CI 12, 18) for HTC and $59 (95% CI 45, 74) for VMMC. On average, 38% of the mean unit cost for HTC corresponded to recurrent costs, 56% to personnel costs, and 6% to capital costs. For VMMC, 41% of the average unit cost corresponded to recurrent costs, 55% to personnel costs, and 4% to capital costs. We observed unit cost variation within and between countries, and lower costs in higher scale categories in all interventions.Keywords: efficiency, unit cost, prevention, cost variation

Consistently defined, accurate, and easily accessible cost data are a valuable resource to inform efficiency analyses, budget preparation, and sustainability planning in global health. The Global Health Cost Consortium (GHCC) designed the Unit Cost Study Repository (UCSR) to be a resource for standardised HIV and TB intervention cost data displayed by key characteristics such as intervention type, country, and target population. To develop the UCSR, the GHCC defined a typology of interventions for each disease; aligned interventions according to the standardised principles, methods, and cost and activity categories from the GHCC Reference Case for Estimating the Costs of Global Health Services and Interventions; completed a systematic literature review; conducted extensive data extraction; performed quality assurance; grappled with complex methodological issues such as the proper approach to the inflation and conversion of costs; developed and implemented a study quality rating system; and designed a web-based user interface that flexibly displays large amounts of data in a user-friendly way. Key lessons learned from the extraction process include the importance of assessing the multiple uses of extracted data; the critical role of standardising definitions (particularly units of measurement); using appropriate classifications of interventions and components of costs; the efficiency derived from programming data checks; and the necessity of extraction quality monitoring by senior analysts. For the web interface, lessons were: understanding the target audiences, including consulting them regarding critical characteristics; designing the display of data in “levels”; and incorporating alert and unique trait descriptions to further clarify differences in the data.Keywords: tuberculosis, database, reference case, systematic review

Objective: To estimate facility-level average cost for ART services and explore unit cost variations using pooled facility-level cost estimates from four HIV empirical cost studies conducted in five African countries .Methods: Through a literature search we identified studies reporting facility-level costs for ART programmes. We requested the underlying data and standardised the disparate data sources to make them comparable. Subsequently, we estimated the annual cost per patient served and assessed the cost variation among facilities and other service delivery characteristics using descriptive statistics and meta-analysis. All costs were converted to 2017 US dollars ($).Results: We obtained and standardised data from four studies across five African countries and 139 facilities. The weighted average cost per patient on ART was $251 (95% CI: 193–308). On average, 46% of the mean unit cost correspond to antiretroviral (ARVs) costs, 31% to personnel costs, 20% other recurrent costs, and 2% to capital costs. We observed a lot of variation in unit cost and scale levels between countries. We also observed a negative relationship between ART unit cost and the number of patients served in a year.Conclusion: Our approach allowed us to explore unit cost variation across contexts by pooling ART costs from multiple sources. Our research provides an example of how to estimate costs based on heterogeneous sources reconciling methodological differences across studies and contributes by giving an example on how to estimate costs based on heterogeneous sources of data. Also, our study provides additional information on costs for funders, policy-makers, and decision-makers in the process of designing or scaling-up HIV interventions.Keywords: HIV, treatment, efficiency, cost variatio

Drug-resistant tuberculosis (DR-TB) is challenging to diagnose, treat, and prevent, but this situation is slowly changing. If the world is to drastically reduce the incidence of DR-TB, we must stop creating new DR-TB as an essential first step. The DR-TB epidemic that is ongoing should also be directly addressed. First-line drug resistance must be rapidly detected using universal molecular testing for resistance to at least rifampin and, preferably, other key drugs at initial TB diagnosis. DR-TB treatment outcomes must also improve dramatically. Effective use of currently available, new, and repurposed drugs, combined with patient-centered treatment that aids adherence and reduces catastrophic costs, are essential. Innovations within sight, such as short, highly effective, broadly indicated regimens, paired with point-of-care drug susceptibility testing, could accelerate progress in treatment outcomes. Preventing or containing resistance to second-line and novel drugs is also critical and will require high-quality systems for diagnosis, regimen selection, and treatment monitoring. Finally, earlier detection and/or prevention of DR-TB is necessary, with particular attention to airborne infection control, case finding, and preventive therapy for contacts of patients with DR-TB. Implementing these strategies can overcome the barrier that DR-TB represents for global TB elimination efforts, and could ultimately make global elimination of DR-TB (fewer than one annual case per million population worldwide) attainable. There is a strong cost-effectiveness case to support pursuing DR-TB elimination; however, achieving this goal will require substantial global investment plus political and societal commitment at national and local levels.

___Key messages___ The Commission recommends five priority investments to achieve a tuberculosis-free world within a generation. These investments are designed to fulfil the mandate of the UN High Level Meeting on tuberculosis. In addition, they answer the question of how countries with high-burden tuberculosis and their development partners should target their future investments to ensure that ending tuberculosis is achievable. __Invest first to ensure that high quality rapid diagnostics and treatment are provided to all individuals receiving care for tuberculosis, wherever they seek care__ This priority includes rapid drug susceptibility testing and second-line treatment for resistant forms of tuberculosis. Achieving universal, high-quality person-centred and family-centred care—including sustained improvement in the performance of private sector providers—usually should be the top policy and budget priority. __Reach people and populations at high risk for tuberculosis (such as household and other close contacts of people with tuberculosis, and people with HIV) and bring them into care__ Active case-finding and treatment in high-risk populations demands adequate resources to reach and care for these populations. At the same time, reaching certain high-risk populations, such as people co-infected with tuberculosis and HIV, for tuberculosis preventive therapy is essential to achieve epidemiologic control. Once high-risk populations have access to affordable, high-quality diagnostic, treatment and preventive services, invest in identifying tuberculosis cases in the general population, primarily by strengthening the capacity to deliver health services and move toward universal health coverage. __Increase investment to accelerate tuberculosis research and development and bring new diagnostics, therapeutic strategies, and vaccines to clinical practice to quickly end the pandemic__ Strong advocacy with science ministries and research-oriented pharmaceutical companies is crucial, including ministries and companies in middle-income countries, to highlight the importance of investing in new tools. Financing the early uptake of new products will provide important confidence signals to product developers. __Make investment in tuberculosis programmes a shared responsibility, increasing development assistance for tuberculosis according to the financial needs of individual low-income and middle-income countries__ As countries successfully mobilise more domestic resources towards tuberculosis programmes, external assistance to middle-income countries should address the following priorities: reduce the spread of drug-resistant tuberculosis in all affected low-income and middle-income countries; facilitate market-shaping activities to enable access to high quality drugs and diagnostics for high-burden countries; and finance tuberculosis research and development, including product development as well as population, policy, and implementation research that will provide lessons and international sharing of best practices. __Hold countries and key stakeholders accountable for progress made towards ending tuberculosis__ Accountability entails establishing independent, multisectoral processes, such as national tuberculosis report cards, to ensure that all stakeholders carry out their responsibilities to contribute to ending the pandemic. Accountability mechanisms should not only assess progress, but also guarantee that Heads of Governments, national tuberculosis programmes, and even regional and site-level clinics, as well as key non-governmental organisations, take the necessary corrective actions to remove obstacles to ending tuberculosis.

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.