Systematic review of the economic evaluation of influenza vaccines in the Guangdong-Hong Kong-Macao Greater Bay Area / 中国药房

ABSTRACT

OBJECTIVE To systematically analyze the status of health economic evaluation studies of influenza vaccination in Guangdong-Hong Kong-Macao Greater Bay Area （GBA） of China， and to provide a methodological reference for future scholars to carry out economic evaluations of influenza vaccine in GBA. METHODS Seven English databases such as PubMed and Embase and three Chinese databases such as CNKI and Wanfang database were searched. The economic evaluation studies of influenza vaccines with the study area of GBA were collected. The search time frame was from the inception to June 30， 2022. After screening the literature and extracting key information， descriptive analysis was conducted on the study design， evaluation methods， model settings， results and conclusions of these collected papers， and the quality of the papers was evaluated using Quality of Health Economic Studies. RESULTS A total of 12 papers were included， of which 7 had a study region of Hong Kong in China， 6 had an older target group， 5 had a society-wide perspective， and the study time frame ranged from 6 months to 9 years. Besides， 8 papers used cost-utility analysis， only 2 used an epidemic model； 8 papers conducted sensitivity analyses， and most of them conducted both one-way sensitivity analysis and probabilistic sensitivity analysis. Moreover， the results of the economic evaluation of 10 papers showed that （combined） vaccination or increased vaccination rates were more economical. In addition， 4 of the 12 papers had a quality score＞75， which were considered high-quality studies. CONCLUSIONS Although most of the included studies showed that vaccination was economical， the quality of the existing paper needed to be improved. It is recommended that subsequent studies on the economic evaluation of influenza vaccines in GBA may consider adding economic evaluations for Macau and other cities in Guangdong of China， prioritizing dynamic models and recent data from local residents， and referring to relevant tools and guidelines to improve thestandardization and scientificity of the study design.