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Updated: Aug 8, 2025

Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics
Published on: July 19, 2024
Delhi's network for surveillance of antimicrobial resistance: The journey, challenges and output from first year
Saxena Sonal1, Sharma Anuj2, Andrews A Amala3
1Deapt of Microbiology, Maulana Azad Medical College, New Delhi, India.
Purpose:
Antimicrobial resistance [AMR] has emerged as a global and national priority and establishing an effective surveillance system for antimicrobial resistance is an essential prerequisite for generating evidence for informed policymaking at both national and state levels.
Methods:
Twenty-four laboratories were enrolled after assessment in the WHO-IAMM Network for Surveillance of Antimicrobial Resistance in Delhi [WINSAR-D]. The NARS- NET standard operating procedures were adopted along with its priority pathogen lists and antibiotic panels. The members were trained to use WHONET software and monthly data files were collected, collated, and analyzed.
Results:
Multiple logistic issues such as procurement, erratic supply of consumables, non-availability of standard guidelines, lack of automated systems, high workload and low manpower were reported by the majority of member laboratories. Microbiological challenges such as differentiation between colonization and pathogen in absence of patient details, lack of confirmation of resistance, identification of isolates and lack of dedicated computer and genuine windows software for data were common to most laboratories. The total number of isolates of priority pathogens in 2020 was 31,463. Of these, 50.1% isolates were from urine 20.6% were from blood and 28.3% were from pus aspirate and other sterile body fluids. High levels of resistance were observed for all antibiotics.
Conclusion:
There are many challenges in generating quality AMR data in lower-middle-income countries. There is a need for resource allocation and capacity building at all levels to ensure the collection of quality assured data.
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