A cost-effectiveness analysis of hypertrophic cardiomyopathy sudden cardiac death risk algorithms for implantable cardioverter defibrillator decision-making.

AIMS: To conduct a contemporary cost-effectiveness analysis examining the use of implantable cardioverter defibrillators (ICD) for primary prevention in patients with hypertrophic cardiomyopathy (HCM). METHODS: A discrete-time Markov model was used to determine the cost-effectiveness of different ICD decision-making rules for implantation. Several scenarios were investigated including the reference scenario of implantation rates according to observed real world practice. A 12-year time horizon with an annual cycle length was used. Transition probabilities used in the model were obtained using Bayesian analysis. The study has been reported according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. RESULTS: Using a 5-year SCD risk threshold of 6% was cheaper than current practice and has marginally better total quality adjusted life years (QALYs). This is the most cost-effective of the options considered, with an incremental cost effectiveness ratio of £834 per QALY. Sensitivity analyses highlighted that this decision is largely driven by what health related quality of life (HRQL) is attributed to ICD patients and time horizon. CONCLUSION: We present a timely new perspective on HCM ICD cost-effectiveness, using methods reflecting real-world practice. While we have shown that a 6% 5-year SCD risk cut-off provides the best cohort stratification to aid ICD decision-making, this will also be influenced by the particular values of costs and HRQL for subgroups or at a local level. The process of explicitly demonstrating the main factors which drive conclusions from such an analysis will help to inform shared decision-making in this complex area for all stakeholders concerned.

Blended Survival Curves: A New Approach to Extrapolation for Time-to-Event Outcomes from Clinical Trials in Health Technology Assessment.

BACKGROUND: Survival extrapolation is essential in cost-effectiveness analysis to quantify the lifetime survival benefit associated with a new intervention, due to the restricted duration of randomized controlled trials (RCTs). Current approaches of extrapolation often assume that the treatment effect observed in the trial can continue indefinitely, which is unrealistic and may have a huge impact on decisions for resource allocation. OBJECTIVE: We introduce a novel methodology as a possible solution to alleviate the problem of survival extrapolation with heavily censored data from clinical trials. METHOD: The main idea is to mix a flexible model (e.g., Cox semiparametric) to fit as well as possible the observed data and a parametric model encoding assumptions on the expected behavior of underlying long-term survival. The two are "blended" into a single survival curve that is identical with the Cox model over the range of observed times and gradually approaching the parametric model over the extrapolation period based on a weight function. The weight function regulates the way two survival curves are blended, determining how the internal and external sources contribute to the estimated survival over time. RESULTS: A 4-y follow-up RCT of rituximab in combination with fludarabine and cyclophosphamide versus fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia is used to illustrate the method. CONCLUSION: Long-term extrapolation from immature trial data may lead to significantly different estimates with various modelling assumptions. The blending approach provides sufficient flexibility, allowing a wide range of plausible scenarios to be considered as well as the inclusion of external information, based, for example, on hard data or expert opinion. Both internal and external validity can be carefully examined. HIGHLIGHTS: Interim analyses of trials with limited follow-up are often subject to high degrees of administrative censoring, which may result in implausible long-term extrapolations using standard approaches.In this article, we present an innovative methodology based on "blending" survival curves to relax the traditional proportional hazard assumption and simultaneously incorporate external information to guide the extrapolation.The blended method provides a simple and powerful framework to allow a careful consideration of a wide range of plausible scenarios, accounting for model fit to the short-term data as well as the plausibility of long-term extrapolations.

Extensions of Health Economic Evaluations in R for Microsoft Excel Users: A Tutorial for Incorporating Heterogeneity and Conducting Value of Information Analyses.

Advanced health economic analysis techniques currently performed in Microsoft Excel, such as incorporating heterogeneity, time-dependent transitions and a value of information analysis, can be easily transferred to R. Often the outputs of survival analyses (such as Weibull regression models) will estimate the impacts of correlated patient characteristics on patient outcomes, and are utilised directly as inputs for health economic decision models. This tutorial provides a step-by-step guide of how to conduct such analyses with a Markov model developed in R, and offers a comparison with established analyses performed in Microsoft Excel. This is done through the conversion of a previously published Microsoft Excel case study of a hip replacement surgery cost-effectiveness model. We hope that this paper can act as a facilitator in switching decision models from Microsoft Excel to R for complex health economic analyses, providing open-access code and data, suitable for future adaptation.

Health Economic Evaluation Using Markov Models in R for Microsoft Excel Users: A Tutorial.

A health economic evaluation (HEE) is a comparative analysis of alternative courses of action in terms of both costs and consequences. A cost-effectiveness analysis is a type of HEE that compares an intervention to one or more alternatives by estimating how much it costs to gain an additional unit of health outcome. Cost-effectiveness analyses are commonly performed using Microsoft (MS) Excel. However, there is current interest in using other software that is better suited to more complex problems, methods, and data, as well as improved reproducibility and transparency. That is, it is increasingly important to be able to repeat an analysis of a particular data set and obtain the same results, and access the analysis and results in a clear and comprehensive openly available form. In this tutorial we provide a step-by-step guide on how to implement a mainstay model of HEE, namely a Markov model, in the statistical programming language R. The adoption of R for the purpose of cost-effectiveness analysis is highly dependent on the ability of the health economic modeller to understand, learn, and apply programming-type skills. R is likely to be less familiar than MS Excel for many modellers and so coding a cost-effectiveness model in R can be a large jump. We describe the technical details from the perspective of a MS Excel user to help bridge the gap between software and reduce the learning curve by providing for the first-time side-by-side comparisons of the Markov model example in MS Excel and R.

Cost-effectiveness of a medication event monitoring system for tuberculosis management in Morocco.

BACKGROUND: Digital health technologies have been used to enhance adherence to TB medication, but the cost-effectiveness remains unclear. METHODS: We used the real data from the study conducted from April 2014 to December 2020 in Morocco using a smart pillbox with a web-based medication monitoring system, called Medication Event Monitoring Systems (MEMS). Cost-effectiveness was evaluated using a decision analysis model including Markov model for Multi-drug resistant (MDR) TB from the health system perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER) per disability adjusted life-year (DALY) averted. Two-way sensitive analysis was done for the treatment success rate between MEMS and standard of care. RESULTS: The average total per-patient health system costs for treating a new TB patient under MEMS versus standard of care were $398.70 and $155.70, respectively. The MEMS strategy would reduce the number of drug-susceptible TB cases by 0.17 and MDR-TB cases by 0.01 per patient over five years. The ICER of MEMS was $434/DALY averted relative to standard of care, and was most susceptible to the TB treatment success rate of both strategies followed by the managing cost of MEMS. CONCLUSION: MEMS is considered cost-effective for managing infectious active TB in Morocco.

Economic burden of female genital mutilation in 27 high-prevalence countries.

BACKGROUND: Female genital mutilation (FGM) is a traditional harmful practice affecting 200 million women and girls globally. Health complications of FGM occur immediately and over time, and are associated with healthcare costs that are poorly understood. Quantifying the global FGM-related burden is essential for supporting programmes and policies for prevention and mitigation. METHODS: Health complications of FGM are derived from a meta-analysis and stratified by acute, uro-gynaecological, obstetric and psychological/sexual. Treatment costs are calculated from national cohort models of 27 high-burden countries over 30 years. Savings associated with full/partial abandonment are compared with a current incidence reference scenario, assuming no changes in FGM practices. RESULTS: Our model projects an increasing burden of FGM due to population growth. As a reference scenario assuming no change in practices, prevalent cases in 27 countries will rise from 119.4 million (2018) to 205.8 million (2047). Full abandonment could reduce this to 80.0 million (2047), while partial abandonment is insufficient to reduce cases. Current incidence economic burden is US$1.4 billion/year, rising to US$2.1 billion/year in 2047. Full abandonment would reduce the future burden to US$0.8 billion/year by 2047. CONCLUSION: FGM is a human rights violation, a public health issue and a substantial economic burden that can be avoided through effective prevention strategies. While decreasing trends are observed in some countries, these trends are variable and not consistently observed across settings. Additional resources are needed to prevent FGM to avoid human suffering and growing costs. The findings of this study warrant increased political commitment and investment in the abandonment of FGM.

Global return on investment and cost-effectiveness of WHO's HEAR interventions for hearing loss: a modelling study.

BACKGROUND: To address the growing prevalence of hearing loss, WHO has identified a compendium of key evidence-based ear and hearing care interventions to be included within countries' universal health coverage packages. To assess the cost-effectiveness of these interventions and their budgetary effect for countries, we aimed to analyse the investment required to scale up services from baseline to recommended levels, and the return to society for every US$1 invested in the compendium. METHODS: We did a modelling study using the proposed set of WHO interventions (summarised under the acronym HEAR: hearing screening and intervention for newborn babies and infants, pre-school and school-age children, older adults, and adults at higher risk of hearing loss; ear disease prevention and management; access to technologies such as hearing aids, cochlear implants, or hearing assistive technologies; and rehabilitation service provision), which span the life course and include screening and management of hearing loss and related ear diseases, costs and benefits for the national population cohorts of 172 countries. The return on investment was analysed for the period between 2020 and 2030 using three scenarios: a business-as-usual scenario, a progress scenario with a scale-up to 50% of recommended coverage, and an ambitious scenario with scale-up to 90% of recommended coverage. Using data for hearing loss burden from the Global Burden of Disease Study 2019, a transition model with three states (general population, diagnosed, and those who have died) was developed to model the national populations in countries. For the return-on-investment analysis, the monetary value of disability-adjusted life-years (DALYs) averted in addition to productivity gains were compared against the investment required in each scenario. FINDINGS: Scaling up ear and hearing care interventions to 90% requires an overall global investment of US$238·8 billion over 10 years. Over a 10-year period, this investment promises substantial health gains with more than 130 million DALYs averted. These gains translate to a monetary value of more than US$1·3 trillion. In addition, investment in hearing care will result in productivity benefits of more than US$2 trillion at the global level by 2030. Together, these benefits correspond to a return of nearly US$15 for every US$1 invested. INTERPRETATION: This is the first-ever global investment case for integrating ear and hearing care interventions in countries' universal health coverage services. The findings show the economic benefits of investing in this compendium and provide the basis for facilitating the increase of country's health budget for strengthening ear and hearing care services. FUNDING: None.

Exploring relationships between drought and epidemic cholera in Africa using generalised linear models.

BACKGROUND: Temperature and precipitation are known to affect Vibrio cholerae outbreaks. Despite this, the impact of drought on outbreaks has been largely understudied. Africa is both drought and cholera prone and more research is needed in Africa to understand cholera dynamics in relation to drought. METHODS: Here, we analyse a range of environmental and socioeconomic covariates and fit generalised linear models to publicly available national data, to test for associations with several indices of drought and make cholera outbreak projections to 2070 under three scenarios of global change, reflecting varying trajectories of CO2 emissions, socio-economic development, and population growth. RESULTS: The best-fit model implies that drought is a significant risk factor for African cholera outbreaks, alongside positive effects of population, temperature and poverty and a negative effect of freshwater withdrawal. The projections show that following stringent emissions pathways and expanding sustainable development may reduce cholera outbreak occurrence in Africa, although these changes were spatially heterogeneous. CONCLUSIONS: Despite an effect of drought in explaining recent cholera outbreaks, future projections highlighted the potential for sustainable development gains to offset drought-related impacts on cholera risk. Future work should build on this research investigating the impacts of drought on cholera on a finer spatial scale and potential non-linear relationships, especially in high-burden countries which saw little cholera change in the scenario analysis.

Cost-benefit analysis of surveillance for surgical site infection following caesarean section.

OBJECTIVE: To estimate the economic burden to the health service of surgical site infection following caesarean section and to identify potential savings achievable through implementation of a surveillance programme. DESIGN: Economic model to evaluate the costs and benefits of surveillance from community and hospital healthcare providers' perspective. SETTING: England. PARTICIPANTS: Women undergoing caesarean section in National Health Service hospitals. MAIN OUTCOME MEASURE: Costs attributable to treatment and management of surgical site infection following caesarean section. RESULTS: The costs (2010) for a hospital carrying out 800 caesarean sections a year based on infection risk of 9.6% were estimated at £18 914 (95% CI 11 521 to 29 499) with 28% accounted for by community care (£5370). With inflation to 2019 prices, this equates to an estimated cost of £5.0 m for all caesarean sections performed annually in England 2018-2019, approximately £1866 and £93 per infection managed in hospital and community, respectively. The cost of surveillance for a hospital for one calendar quarter was estimated as £3747 (2010 costs). Modelling a decrease in risk of infection of 30%, 20% or 10% between successive surveillance periods indicated that a variable intermittent surveillance strategy achieved higher or similar net savings than continuous surveillance. Breakeven was reached sooner with the variable surveillance strategy than continuous surveillance when the baseline risk of infection was 10% or 15% and smaller loses with a baseline risk of 5%. CONCLUSION: Surveillance of surgical site infections after caesarean section with feedback of data to surgical teams offers a potentially effective means to reduce infection risk, improve patient experience and save money for the health service.

A cost comparison of amikacin therapy with bedaquiline, for drug-resistant tuberculosis in the UK.

OBJECTIVES: Prioritisation of oral bedaquiline over the injectable agents in the treatment of multidrug-resistant Tuberculosis (MDR-TB) in the World Health Organisations (WHO) 2019 guidelines prompted this UK analysis of cost implications. The objective was to estimate the costs of amikacin versus bedaquiline in MDR TB treatment regimens using a historical cohort where the injectable agents were the standard of care. METHODS: This was a retrospective study using a known cohort of UK patients treated with an injectable agent, with data available on resource use, costs for the use of amikacin were compared with those for bedaquiline, based on recommended monitoring for bedaquiline. RESULTS: The estimated cost of treatment per patient had mean (sd) of £27,236 (4952) for the observed injectable group, £30,264 (3392) and 36,309 (3901) for the 6 and 8 month amikacin groups, and £31,760 (2092) for the bedaquiline group. The cost in the bedaquiline group was £30,772 (1855) with a 10% reduction and £27,079 (1234) with a 33% reduction in-patient stay. CONCLUSIONS: In most scenarios, bedaquiline is close to cost neutral compared with injectable therapy, especially if, as expected, some reduction in duration of admission is possible as a result of bedaquiline's more rapid culture conversion.

The health and cost burden of antibiotic resistant and susceptible Escherichia coli bacteraemia in the English hospital setting: A national retrospective cohort study.

INTRODUCTION: Antibiotic resistance poses a threat to public health and healthcare systems. Escherichia coli causes more bacteraemia episodes in England than any other bacterial species. This study aimed to estimate the burden of E. coli bacteraemia and associated antibiotic resistance in the secondary care setting. MATERIALS AND METHODS: This was a retrospective cohort study, with E. coli bacteraemia as the main exposure of interest. Adult hospital in-patients, admitted to acute NHS hospitals between July 2011 and June 2012 were included. English national surveillance and administrative datasets were utilised. Cox proportional hazard, subdistribution hazard and multistate models were constructed to estimate rate of discharge, rate of in-hospital death and excess length of stay, with a unit bed day cost applied to the latter to estimate cost burden from the healthcare system perspective. RESULTS: 14,042 E. coli bacteraemia and 8,919,284 non-infected inpatient observations were included. E. coli bacteraemia was associated with an increased rate of in-hospital death across all models, with an adjusted subdistribution hazard ratio of 5.88 (95% CI: 5.62-6.15). Resistance was not found to be associated with in-hospital mortality once adjusting for patient and hospital covariates. However, resistance was found to be associated with an increased excess length of stay. This was especially true for third generation cephalosporin (1.58 days excess length of stay, 95% CI: 0.84-2.31) and piperacillin/tazobactam resistance (1.23 days (95% CI: 0.50-1.95)). The annual cost of E. coli bacteraemia was estimated to be £14,346,400 (2012 £), with third-generation cephalosporin resistance associated with excess costs per infection of £420 (95% CI: 220-630). CONCLUSIONS: E. coli bacteraemia places a statistically significant burden on patient health and the hospital sector in England. Resistance to front-line antibiotics increases length of stay; increasing the cost burden of such infections in the secondary care setting.

Interferon gamma release assays for Diagnostic Evaluation of Active tuberculosis (IDEA): test accuracy study and economic evaluation.

BACKGROUND: Interferon gamma release assays (IGRAs) are blood tests recommended for the diagnosis of tuberculosis (TB) infection. There is currently uncertainty about the role and clinical utility of IGRAs in the diagnostic workup of suspected active TB in routine NHS clinical practice. OBJECTIVES: To compare the diagnostic accuracy and cost-effectiveness of T-SPOT.TB® (Oxford Immunotec, Abingdon, UK) and QuantiFERON® TB GOLD In-Tube (Cellestis, Carnegie, VIC, Australia) for diagnosis of suspected active TB and to estimate the diagnostic accuracy of second-generation IGRAs. DESIGN: Prospective within-patient comparative diagnostic accuracy study. SETTING: Secondary care. PARTICIPANTS: Adults (aged ≥ 16 years) presenting as inpatients or outpatients at 12 NHS hospital trusts in London, Slough, Oxford, Leicester and Birmingham with suspected active TB. INTERVENTIONS: The index tests [T-SPOT.TB and QuantiFERON GOLD In-Tube (QFT-GIT)] and new enzyme-linked immunospot assays utilising novel Mycobacterium tuberculosis antigens (Rv3615c, Rv2654, Rv3879c and Rv3873) were verified against a composite reference standard applied by a panel of clinical experts blinded to IGRA results. MAIN OUTCOME MEASURES: Sensitivity, specificity, predictive values and likelihood ratios were calculated to determine diagnostic accuracy. A decision tree model was developed to calculate the incremental costs and incremental health utilities [quality-adjusted life-years (QALYs)] of changing from current practice to using an IGRA as an initial rule-out test. RESULTS: A total of 363 patients had active TB (culture-confirmed and highly probable TB cases), 439 had no active TB and 43 had an indeterminate final diagnosis. Comparing T-SPOT.TB and QFT-GIT, the sensitivities [95% confidence interval (CI)] were 82.3% (95% CI 77.7% to 85.9%) and 67.3% (95% CI 62.1% to 72.2%), respectively, whereas specificities were 82.6% (95% CI 78.6% to 86.1%) and 80.4% (95% CI 76.1% to 84.1%), respectively. T-SPOT.TB was more sensitive than QFT-GIT (relative sensitivity 1.22, 95% CI 1.14 to 1.31; p < 0.001), but the specificities were similar (relative specificity 1.02, 95% CI 0.97 to 1.08; p = 0.3). For both IGRAs the sensitivity was lower and the specificity was higher for human immunodeficiency virus (HIV)-positive than for HIV-negative patients. The most promising novel antigen was Rv3615c. The added value of Rv3615c to T-SPOT.TB was a 9% (95% CI 5% to 12%) relative increase in sensitivity at the expense of specificity, which had a relative decrease of 7% (95% CI 4% to 10%). The use of current IGRA tests for ruling out active TB is unlikely to be considered cost-effective if a QALY was valued at £20,000 or £30,000. For T-SPOT.TB, the probability of being cost-effective for a willingness to pay of £20,000/QALY was 26% and 21%, when patients with indeterminate test results were excluded or included, respectively. In comparison, the QFT-GIT probabilities were 8% and 6%. Although the use of IGRAs is cost saving, the health detriment is large owing to delay in diagnosing active TB, leading to prolonged illness. There was substantial between-patient variation in the tests used in the diagnostic pathway. LIMITATIONS: The recruitment target for the HIV co-infected population was not achieved. CONCLUSIONS: Although T-SPOT.TB was more sensitive than QFT-GIT for the diagnosis of active TB, the tests are insufficiently sensitive for ruling out active TB in routine clinical practice in the UK. Novel assays offer some promise. FUTURE WORK: The novel assays require evaluation in distinct clinical settings and in immunosuppressed patient groups. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and the NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Tuberculosis (TB) is one of the world's most important infectious diseases. In 2014, 1.5 million deaths were caused by the disease ­ about one death every 25 seconds. Traditional diagnosis of TB is based partly on the tuberculin skin test. Blood tests such as QuantiFERON GOLD In-Tube (QFT-GIT; Cellestis, Carnegie, VIC, Australia) and T-SPOT.TB^® (Oxford Immunotec, Abingdon, UK) are now available. However, these two tests are not used as part of current NHS practice because of the lack of evidence about how well the tests perform when diagnosing symptomatic (active) TB in routine clinical practice. The purpose of our study was to compare the ability of QFT-GIT and T-SPOT.TB to differentiate people with active TB from those without active TB in a population suspected of the disease. We also assessed new blood tests that are currently being developed for diagnosis of active TB. We recruited 1074 patients with suspected TB from 14 NHS hospitals in London, Slough, Oxford, Leicester and Birmingham into our study. We found that T-SPOT.TB correctly detected more people with active TB than QFT-GIT; T-SPOT.TB would miss about 18 people out of every 100, whereas QFT-GIT would miss about 33 people out of every 100 with active TB. For this reason, neither test is good enough for routine clinical use because the number of people with active TB who are incorrectly diagnosed as not having active TB is unacceptably high. In addition, neither test is good value for money. However, we did find that some of the newer blood tests performed better than T-SPOT.TB and their usefulness should be further investigated.

Systematic review, meta-analysis and economic modelling of molecular diagnostic tests for antibiotic resistance in tuberculosis.

BACKGROUND: Drug-resistant tuberculosis (TB), especially multidrug-resistant (MDR, resistance to rifampicin and isoniazid) disease, is associated with a worse patient outcome. Drug resistance diagnosed using microbiological culture takes days to weeks, as TB bacteria grow slowly. Rapid molecular tests for drug resistance detection (1 day) are commercially available and may promote faster initiation of appropriate treatment. OBJECTIVES: To (1) conduct a systematic review of evidence regarding diagnostic accuracy of molecular genetic tests for drug resistance, (2) conduct a health-economic evaluation of screening and diagnostic strategies, including comparison of alternative models of service provision and assessment of the value of targeting rapid testing at high-risk subgroups, and (3) construct a transmission-dynamic mathematical model that translates the estimates of diagnostic accuracy into estimates of clinical impact. REVIEW METHODS AND DATA SOURCES: A standardised search strategy identified relevant studies from EMBASE, PubMed, MEDLINE, Bioscience Information Service (BIOSIS), System for Information on Grey Literature in Europe Social Policy & Practice (SIGLE) and Web of Science, published between 1 January 2000 and 15 August 2013. Additional 'grey' sources were included. Quality was assessed using quality assessment of diagnostic accuracy studies version 2 (QUADAS-2). For each diagnostic strategy and population subgroup, a care pathway was constructed to specify which medical treatments and health services that individuals would receive from presentation to the point where they either did or did not complete TB treatment successfully. A total cost was estimated from a health service perspective for each care pathway, and the health impact was estimated in terms of the mean discounted quality-adjusted life-years (QALYs) lost as a result of disease and treatment. Costs and QALYs were both discounted at 3.5% per year. An integrated transmission-dynamic and economic model was used to evaluate the cost-effectiveness of introducing rapid molecular testing (in addition to culture and drug sensitivity testing). Probabilistic sensitivity analysis was performed to evaluate the impact on cost-effectiveness of diagnostic and treatment time delays, diagnosis and treatment costs, and associated QALYs. RESULTS: A total of 8922 titles and abstracts were identified, with 557 papers being potentially eligible. Of these, 56 studies contained sufficient test information for analysis. All three commercial tests performed well when detecting drug resistance in clinical samples, although with evidence of heterogeneity between studies. Pooled sensitivity for GenoType® MTBDRplus (Hain Lifescience, Nehren, Germany) (isoniazid and rifampicin resistance), INNO-LiPA Rif.TB® (Fujirebio Europe, Ghent, Belgium) (rifampicin resistance) and Xpert® MTB/RIF (Cepheid Inc., Sunnyvale, CA, USA) (rifampicin resistance) was 83.4%, 94.6%, 95.4% and 96.8%, respectively; equivalent pooled specificity was 99.6%, 98.2%, 99.7% and 98.4%, respectively. Results of the transmission model suggest that all of the rapid assays considered here, if added to the current diagnostic pathway, would be cost-saving and achieve a reduction in expected QALY loss compared with current practice. GenoType MTBDRplus appeared to be the most cost-effective of the rapid tests in the South Asian population, although results were similar for GeneXpert. In all other scenarios GeneXpert appeared to be the most cost-effective strategy. CONCLUSIONS: Rapid molecular tests for rifampicin and isoniazid resistance were sensitive and specific. They may also be cost-effective when added to culture drug susceptibility testing in the UK. There is global interest in point-of-care testing and further work is needed to review the performance of emerging tests and the wider health-economic impact of decentralised testing in clinics and primary care, as well as non-health-care settings, such as shelters and prisons. STUDY REGISTRATION: This study is registered as PROSPERO CRD42011001537. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Optimal intervention for an epidemic model under parameter uncertainty.

We will be concerned with optimal intervention policies for a continuous-time stochastic SIR (susceptible-->infective-->removed) model for the spread of infection through a closed population. In previous work on such optimal policies, it is common to assume that model parameter values are known; in reality, uncertainty over parameter values exists. We shall consider the effect upon the optimal policy of changes in parameter estimates, and of explicitly taking into account parameter uncertainty via a Bayesian decision-theoretic framework. We consider policies allowing for (i) the isolation of any number of infectives, or (ii) the immunisation of all susceptibles (total immunisation). Numerical examples are given to illustrate our results.