Fundamentals of data for AMR

Introduction

This module introduces the basic concepts, definitions and sources of data related to antimicrobial resistance. It reviews why we need to collect, analyse and report on AMR data, as well as data on antimicrobial use (AMU) and antimicrobial consumption (AMC). The distinction between these is subtle: AMU refers to the quantity of antimicrobial drugs prescribed or administered to an individual person or animal, or group of animals (e.g., herd, flock), and may include information on how antimicrobials are used (e.g. for prophylaxis or the treatment of specific conditions), whereas AMC refers to the total quantity of antimicrobial drugs imported, manufactured and/or sold in a country or region. AMC is sometimes used as a proxy for AMU when detailed data on actual use is not available.

As part of this module you will have the opportunity to reflect on sources of AMR-related data in your own workplace and how they fit into local, national and global systems to collect, collate, analyse and use AMR-related data to inform decision-making. The module also explains standard measurement units for AMR, AMU and AMC. Finally, you will be introduced to important concepts related to error and bias, and how they affect the interpretation and use of AMR, AMU and AMC data.

This is the first in a series of modules related to AMR data. Some of the topics introduced in this module will be expanded on in modules on Sampling, Processing and analysing AMR data, Summarising and presenting AMR data, and Legal and ethical considerations in AMR data.

After completing this module, you will be able to:

• explain why it is important to measure AMR, AMU and AMC data
• identify different types of AMR, AMU and AMC data
• explain how data become useful and lead to informed decision-making in the AMR response
• identify and explain potential sources of error and bias that affect the quality and reliability of AMR, AMU and AMC data.