Cost-effectiveness analysis of sequential fecal microbiota transplantation for fulminant Clostridioides difficile infection.

BACKGROUND AND AIM: Fulminant Clostridioides difficile infections (FCDI) account for 8% of cases and substantial healthcare burden. Fecal microbiota transplantation is recommended for recurrent CDI, but emerging data support use for FCDI. We aimed to assess the cost-effectiveness of a sequential fecal microbiota transplantation (sFMT) protocol for FCDI compared with current standard therapy. METHODS: A Markov model simulated patients with FCDI in a 1-year time horizon. The treatment algorithm for up to three sFMTs, clinical probabilities, and direct costs were used from published sources. Outcomes were quality-adjusted life years (QALYs) and costs. The healthcare sector perspective was used with a willingness-to-pay threshold of $100 000 per QALY. RESULTS: Sequential fecal microbiota transplantation (FMT) for FCDI was associated with lower overall cost ($28 309 vs $33 980) and higher QALY (0.765 vs 0.686) compared with standard therapy. sFMT is cost-effective in 100% of iterations. sFMT remained cost-effective at cure rates > 44.8% for the first FMT and at stool preparation cost < $6944 per instillation. We find a wide range of efficacies for the first versus second FMT at which sFMT is still preferred. Value of information analysis estimates the expected value of perfect information to be low at $1.89 per person, quantified with net monetary benefit. CONCLUSIONS: An sFMT strategy strongly dominates standard therapy, with lower cost and higher QALY. Sensitivity analysis demonstrates benefit even if FMT cure rates are lower than expected and when multiple FMTs are required. FMT material in 2020 was priced at $1695 per treatment but remains cost-effective at a much higher cost.

An integrated framework for modelling quantitative effects of entry restrictions and travel quarantine on importation risk of COVID-19.

OBJECTIVE: As the potential spread of COVID-19 sparked by imported cases from overseas will pose continuous challenges, it is essential to estimate the effects of control measures on reducing the importation risk of COVID-19. Our objective is to provide a framework of methodology for quantifying the combined effects of entry restrictions and travel quarantine on managing the importation risk of COVID-19 and other pandemics by leveraging different sets of parameters. METHODS: Three major categories of control measures on controlling importation risk were parameterized and modelled by the framework: 1) entry restrictions, 2) travel quarantine, and 3) domestic containment measures. Integrating the parameterized intensity of control measures, a modified SEIR model was developed to simulate the case importation and local epidemic under different scenarios of global epidemic dynamics. A web-based tool was also provided to enable interactive visualization of epidemic simulation. RESULTS: The simulated number of case importation and local spread modelled by the proposed framework of methods fitted well to the historical epidemic curve of China and Singapore. Based on the simulation results, the total numbers of infected cases when reducing 30% of visitor arrivals would be 88·4 (IQR 87·5-89·6) and 58·8 (IQR 58·3-59·5) times more than those when reducing 99% of visitor arrivals in mainland China and Singapore respectively, assuming actual time-varying Rt and travel quarantine policy. If the number of global daily new infections reached 100,000, 85%-91% of inbound travels should be reduced to keep the daily new infected number below 100 for a country with a similar travel volume as Singapore (daily 52,000 tourist arrivals in 2019). Whereas if the number was lower than 10,000, the daily new infected case would be less than 100 even with no entry restrictions. DISCUSSIONS: We proposed a framework that first estimated the intensity of travel restrictions and local containment measures for countries since the first overseas imported case. Our approach then quantified the combined effects of entry restrictions and travel quarantine using a modified SEIR model to simulate the potential epidemic spread under hypothetical intensities of these control measures. We also developed a web-based system that enables interactive simulation, which could serve as a valuable tool for health system administrators to assess policy effects on managing the importation risk. By leveraging different sets of parameters, it could adapt to any specific country and specific type of epidemic. CONCLUSIONS: This framework has provided a valuable tool to parameterize the intensity of control measures, simulate both the case importation and local epidemic, and quantify the combined effects of entry restrictions and travel quarantine on managing the importation risk.