A systematic review of data sources used for socioeconomic impact assessment of antimicrobial resistance from a One Health perspective: a lack of representative data
Issued Date
2026-12-01
Resource Type
eISSN
14787547
Scopus ID
2-s2.0-105029852348
Journal Title
Cost Effectiveness and Resource Allocation
Volume
24
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Cost Effectiveness and Resource Allocation Vol.24 No.1 (2026)
Suggested Citation
Poonsiri C., Sukmanee J., Faradiba D., Chavarina K.K., Prakash A., Anothaisintawee T., Chen Y.T., Sari E.N., Xie Y., Pong C.Y., Lam S.T., Lum E., Graves N., Wee H.L., Teerawattananon Y. A systematic review of data sources used for socioeconomic impact assessment of antimicrobial resistance from a One Health perspective: a lack of representative data. Cost Effectiveness and Resource Allocation Vol.24 No.1 (2026). doi:10.1186/s12962-026-00715-2 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115162
Title
A systematic review of data sources used for socioeconomic impact assessment of antimicrobial resistance from a One Health perspective: a lack of representative data
Corresponding Author(s)
Other Contributor(s)
Abstract
Introduction: Antimicrobial resistance (AMR) has become one of global health threats, having not only clinical impact but also socioeconomic impact. Despite numerous studies attempting to estimate the impact of AMR, there is limited evidence regarding its overall impact from a One Health perspective. As data sources are crucial for accurately estimating the impact, this systematic review aims to identify the data sources used in socioeconomic impact studies of AMR from a One Health perspective. Material and methods: A systematic literature review of studies providing new estimates of AMR impact (“index studies”) from 2010 to 2022 was conducted. Subsequently, we retrieved the “data sources” for the key parameters used in the index studies. The maximum of five data sources for each index study was set to select the parameters with the highest impact on the estimates. The characteristics and details of data sources were extracted. Results: A total of 233 index studies were identified, and 395 data sources were further retrieved and extracted. The majority of data sources were from academic journals (89.4%) published during 2011 to 2020 (70.1%). Approximately half of the data sources were from high-income countries located in the Americas (32.4%) and European (23.0%) regions. Almost all data sources focused on humans (98.2%). There were only five data sources in animals and two data sources focusing on both humans and animals. No data source involving the environment was identified. Conclusion: Most socioeconomic impact studies appropriately utilize up-to-date data sources from the same setting. However, there are some limitations including a disproportion of data from high-income countries, particularly the Americas and European regions. There is also a lack of data addressing AMR in animals and the environment. Thus, future AMR studies concerning pathogens and regions significantly affected by AMR are critical for achieving more comprehensive and representative data.