Cost-Effectiveness Analysis of COVID-19 Inactivated Vaccines in Reducing the Economic Burden of Ischaemic Stroke after SARS-CoV-2 Infection.
Vaccines (Basel)
; 11(5)2023 May 07.
Article
em En
| MEDLINE
| ID: mdl-37243061
Due to significant economic burden and disability from ischaemic stroke and the relationship between ischaemic stroke and SARS-CoV-2 infection, we aimed to explore the cost-effectiveness of the two-dose inactivated COVID-19 vaccination program in reducing the economic burden of ischaemic stroke after SARS-CoV-2 infection. We constructed a decision-analytic Markov model to compare the two-dose inactivated COVID-19 vaccination strategy to the no vaccination strategy using cohort simulation. We calculated incremental cost-effectiveness ratios (ICERs) to evaluate the cost-effectiveness and used number of the ischaemic stroke cases after SARS-CoV-2 infection and quality-adjusted life-years (QALYs) to assess effects. Both one-way deterministic sensitivity analysis and probabilistic sensitivity analysis were performed to assess the robustness of the results. We found that the two-dose inactivated vaccination strategy reduced ischaemic stroke cases after SARS-CoV-2 infection by 80.89% (127/157) with a USD 1.09 million as vaccination program cost, saved USD 3675.69 million as direct health care costs and gained 26.56 million QALYs compared with no vaccination strategy among 100,000 COVID-19 patients (ICER < 0 per QALY gained). ICERs remained robust in sensitivity analysis. The proportion of older patients and the proportion of two-dose inactivated vaccination among older people were the critical factors that affected ICER. This study suggests the importance of COVID-19 vaccination is not only in preventing the spread of infectious diseases, but also in considering its long-term value in reducing the economic burden of non-communicable diseases such as ischaemic stroke after SARS-CoV-2 infection.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article