Feasibility study of a field survey to measure antimicrobial usage in humans and animals in the Mekong Delta region of Vietnam. Issue 3 (12th August 2021)

• Record Type: Journal Article
• Authors: Cuong, Nguyen Van; Ly, Nguyen Phuong Cam; Van, Nguyen Thi Bich; Phu, Doan Hoang; Kiet, Bach Tuan; Hien, Vo Be; Padungtod, Pawin; Thwaites, Guy; Choisy, Marc; Carrique-Mas, Juan
• Is Part Of: JAC-antimicrobial resistance. Volume 3:Issue 3(2021)
• Publication Date: 2021-08-12
• Subjects: Anti-infective agents -- Periodicals; Chemotherapy -- Periodicals; Drug resistance in microorganisms -- Periodicals; 616.9041
• DOI: 10.1093/jacamr/dlab107
• Languages: English
• ISSNs: 2632-1823

Abstract

Abstract: Background: Development of antimicrobial use (AMU) surveillance systems in humans and animals is a priority for many low- and middle-income countries; however accurate estimations are hampered by a diversity of animal production systems and metrics. The Mekong Delta region of Vietnam is a 'hotspot' of antimicrobial resistance and is home to a high density of humans and animal populations. Objectives: To measure and compare AMU using different metrics (standing population, biomass and population correction unit) in the Mekong Delta, and to explore the potential of field-based data collection methods in the design of AMU surveillance systems. Methods: We collected AMU data from humans and animals (chickens, ducks, Muscovy ducks, pigs) from 101 small-scale farms in the Mekong Delta over a fixed period (90 days in humans, 7 days in animals). Results: Humans used 7.1 DDDkg, or 175.9 mg of antimicrobial active ingredients (AAIs) per kg of standing body mass annually; animals consumed 60.9 ADDkg or 1324 mg. In the Mekong Delta humans represented 79.3% of the total body mass but consumed 29.6% of AAIs by weight. AAIs regarded of critical importance by WHO represented 56.9% and 50.2% of doses consumed by animals and humans, respectively. Conclusions: Using a One Health approach, we show that AMU can potentially be estimated from cross-sectional surveys, although results are hypothetical due to small sample size and are sensitive to the chosen population denominator. The methodology proposed here can potentially be scaled up be applied to design AMU surveillance in low-resource settings, allowing AMU reduction efforts to be focused on particular animal species.