A global plan has been set to end human deaths from dog-mediated rabies by 2030 (\"Zero-by-30\"), but whether it could be achieved in some countries, such as China, remains unclear. Although elimination strategies through post-exposure prophylaxis (PEP) use, dog vaccination, and patient risk assessments with integrated bite case management (IBCM) were proposed to be cost-effective, evidence is still lacking in China. We aim to evaluate the future burdens of dog-mediated human rabies deaths in the next decade and provide quantitative evidence on the cost-effectiveness of different rabies-control strategies in China.
Based on data from China\'s national human rabies surveillance system, we used decision-analytic modelling to estimate dog-mediated human rabies death trends in China till 2035. We simulated and compared the expected consequences and costs of different combination strategies of the status quo, improved access to PEP, mass dog vaccination, and use of IBCM.
The predicted human rabies deaths in 2030 in China will be 308 (95%UI: 214-411) and remain stable in the next decade under the status quo. The strategy of improved PEP access alone could only decrease deaths to 212 (95%UI: 147-284) in 2028, remaining unchanged till 2035. In contrast, scaling up dog vaccination to coverage of 70% could eliminate rabies deaths by 2033 and prevent approximately 3,265 (95%UI: 2,477-3,687) extra deaths compared to the status quo during 2024-2035. Moreover, with the addition of IBCM, the \"One Health\" approach through mass dog vaccination could avoid unnecessary PEP use and substantially reduce total cost from 12.53 (95%UI: 11.71-13.34) to 8.73 (95%UI: 8.09-9.85) billion US dollars. Even if increasing the total costs of IBCM from 100 thousand to 652.10 million US dollars during 2024-2035, the combined strategy of mass dog vaccination and use of IBCM will still dominate, suggesting the robustness of our results.
The combined strategy of mass dog vaccination and IBCM requires collaboration between health and livestock/veterinary sectors, and it could eliminate Chinese rabies deaths as early as 2033, with more deaths averted and less cost, indicating that adding IBCM could reduce unnecessary use of PEP and make the \"One Health\" rabies-control strategy most cost-effective.

BACKGROUND: Whilst people with intellectual disability grow older, evidence has emerged internationally about the largely unmet health needs of this specific ageing population. Health checks have been implemented in some countries to address those health inequalities. Evaluations have focused on measuring process outcomes due to challenges measuring quality of life outcomes. In addition, the cost-effectiveness is currently unknown. As part of a national guideline for this population we sought to explore the likely cost-effectiveness of annual health checks in England.
METHODS: Decision-analytical Markov modelling was used to estimate the cost-effectiveness of a strategy, in which health checks were provided for older people with intellectual disability, when compared with standard care. The approach we took was explorative. Individual models were developed for a selected range of health conditions, which had an expected high economic impact and for which sufficient evidence was available for the modelling. In each of the models, hypothetical cohorts were followed from 40 yrs. of age until death. The outcome measure was cost per quality-adjusted life-year (QALY) gained. Incremental cost-effectiveness ratios (ICER) were calculated. Costs were assessed from a health provider perspective and expressed in 2016 GBP. Costs and QALYs were discounted at 3.5%. We carried out probabilistic sensitivity analysis. Data from published studies as well as expert opinion informed parameters.
RESULTS: Health checks led to a mean QALY gain of 0.074 (95% CI 0.072 to 0.119); and mean incremental costs of £4787 (CI 95% 4773 to 5017). For a threshold of £30,000 per QALY, health checks were not cost-effective (mean ICER £85,632; 95% CI 82,762 to 131,944). Costs of intervention needed to reduce from £258 to under £100 per year in order for health checks to be cost-effective.
CONCLUSIONS: Whilst findings need to be considered with caution as the model was exploratory in that it was based on assumptions to overcome evidence gaps, they suggest that the way health systems deliver care for vulnerable populations might need to be re-examined. The work was carried out as part of a national guideline and informed recommendations about system changes to achieve more equal health care provisions.

The payoff time represents an estimate of when the benefits of an intervention outweigh the costs. It is particularly useful for benefit-harm decision making for interventions that have deferred benefits but upfront harms. The aim of this study was to expand the application of the payoff time and provide an example of its use within a decision-analytic model.
Three clinically relevant patient vignettes based on varying levels of estimated 10-year cardiovascular risk (10%, 15%, 20%) were developed. An existing state-transition Markov model taking a health service perspective and a life-time horizon was adapted to include 3 levels of direct treatment disutility (DTD) associated with ongoing statin use: 0.005, 0.01, and 0.015. For each vignette and DTD we calculated a range of outputs including the payoff time inclusive and exclusive of healthcare costs.
For a 10% 10-year cardiovascular risk (vignette 1) with low-levels of DTD (0.005), the payoff time was 8.5 years when costs were excluded and 16 years when costs were included. As the baseline risk of cardiovascular increased, the payoff time shortened. For a 15% cardiovascular risk (vignette 2) and for a low-level of DTD, the payoff time was 5.5 years and 9.5 years, respectively. For a 20% cardiovascular risk (vignette 3), the payoff time was 4.2 and 7.2 years, respectively. For higher levels of DTDs for each vignette, the payoff time lengthened, and in some instances the intervention never paid off, leading to an expected net harm for patients.
This study has shown how the payoff time can be readily applied to an existing decision-analytic model and be used to complement existing measures to guide healthcare decision making.

Our aim was to adapt the traditional framework for expected net benefit of sampling (ENBS) to be more compatible with drug development trials from the pharmaceutical perspective. We modify the traditional framework for conducting ENBS and assume that the price of the drug is conditional on the trial outcomes. We use a value-based pricing (VBP) criterion to determine price conditional on trial data using Bayesian updating of cost-effectiveness (CE) model parameters. We assume that there is a threshold price below which the company would not market the new intervention. We present a case study in which a phase III trial sample size and trial duration are varied. For each trial design, we sampled 10,000 trial outcomes and estimated VBP using a CE model. The expected commercial net benefit is calculated as the expected profits minus the trial costs. A clinical trial with shorter follow-up, and larger sample size, generated the greatest expected commercial net benefit. Increasing the duration of follow-up had a modest impact on profit forecasts. Expected net benefit of sampling can be adapted to value clinical trials in the pharmaceutical industry to optimise the expected commercial net benefit. However, the analyses can be very time consuming for complex CE models.