Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya.

BACKGROUND: A few studies have assessed the epidemiological impact and the cost-effectiveness of COVID-19 vaccines in settings where most of the population had been exposed to SARS-CoV-2 infection. METHODS: We conducted a cost-effectiveness analysis of COVID-19 vaccine in Kenya from a societal perspective over a 1.5-year time frame. An age-structured transmission model assumed at least 80% of the population to have prior natural immunity when an immune escape variant was introduced. We examine the effect of slow (18 months) or rapid (6 months) vaccine roll-out with vaccine coverage of 30%, 50% or 70% of the adult (>18 years) population prioritising roll-out in those over 50-years (80% uptake in all scenarios). Cost data were obtained from primary analyses. We assumed vaccine procurement at US$7 per dose and vaccine delivery costs of US$3.90-US$6.11 per dose. The cost-effectiveness threshold was US$919.11. FINDINGS: Slow roll-out at 30% coverage largely targets those over 50 years and resulted in 54% fewer deaths (8132 (7914-8373)) than no vaccination and was cost saving (incremental cost-effectiveness ratio, ICER=US$-1343 (US$-1345 to US$-1341) per disability-adjusted life-year, DALY averted). Increasing coverage to 50% and 70%, further reduced deaths by 12% (810 (757-872) and 5% (282 (251-317) but was not cost-effective, using Kenya's cost-effectiveness threshold (US$919.11). Rapid roll-out with 30% coverage averted 63% more deaths and was more cost-saving (ICER=US$-1607 (US$-1609 to US$-1604) per DALY averted) compared with slow roll-out at the same coverage level, but 50% and 70% coverage scenarios were not cost-effective. INTERPRETATION: With prior exposure partially protecting much of the Kenyan population, vaccination of young adults may no longer be cost-effective.

Examining unit costs for COVID-19 case management in Kenya.

INTRODUCTION: We estimated unit costs for COVID-19 case management for patients with asymptomatic, mild-to-moderate, severe and critical COVID-19 disease in Kenya. METHODS: We estimated per-day unit costs of COVID-19 case management for patients. We used a bottom-up approach to estimate full economic costs and adopted a health system perspective and patient episode of care as our time horizon. We obtained data on inputs and their quantities from data provided by three public COVID-19 treatment hospitals in Kenya and augmented this with guidelines. We obtained input prices from a recent costing survey of 20 hospitals in Kenya and from market prices for Kenya. RESULTS: Per-day, per-patient unit costs for asymptomatic patients and patients with mild-to-moderate COVID-19 disease under home-based care are 1993.01 Kenyan shilling (KES) (US$18.89) and 1995.17 KES (US$18.991), respectively. When these patients are managed in an isolation centre or hospital, the same unit costs for asymptomatic patients and patients with mild-to-moderate disease are 6717.74 KES (US$63.68) and 6719.90 KES (US$63.70), respectively. Per-day unit costs for patients with severe COVID-19 disease managed in general hospital wards and those with critical COVID-19 disease admitted in intensive care units are 13 137.07 KES (US$124.53) and 63 243.11 KES (US$599.51). CONCLUSION: COVID-19 case management costs are substantial, ranging between two and four times the average claims value reported by Kenya's public health insurer. Kenya will need to mobilise substantial resources and explore service delivery adaptations that will reduce unit costs.

A Cost-Effectiveness Model for Frail Older Persons: Development and Application to a Physiotherapy-Based Intervention.

INTRODUCTION: The clinical importance of frailty is increasing. Existing economic evaluations of interventions to manage frailty have limited time horizons, but even in older populations there may be important longer-term differences in costs and outcomes. This paper reports on the development of a cost-effectiveness model to predict publicly funded health and aged care costs and quality-adjusted life years (QALYs) over the remaining lifetime of frail Australians and a model-based cost-utility analysis of a physiotherapy-based intervention for frail individuals. METHODS: A cohort-based state transition (Markov) model was developed to predict costs and QALYs over the remaining lifetime of a frail population. Frailty is defined using the phenotypic definition of frailty, and the model comprises health states that describe frailty status, residential status, the experience of bone fractures and depression, and death. Model input parameters were estimated and calibrated using the Dynamic Analyses to Optimise Ageing dataset, supplemented with data from the published literature. RESULTS: The cost-effectiveness model was subject to a range of validation approaches, which did not negate the validity of the model. The evaluated physiotherapy-based frailty intervention has an expected incremental cost per QALY gained of Australian $8129 compared to usual care, but there is a probability of 0.3 that usual care is more effective and less costly than the intervention. DISCUSSION: Frailty reduces quality of life, is costly to manage and it's prevalence is increasing, but new approaches to managing frailty need to demonstrate value for money. The value of the reported cost-effectiveness model is illustrated through the estimation of all important costs and effects of a physiotherapy-based frailty intervention, which facilitates comparisons with funding decisions for other new technologies in Australia.