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Fundamentals of data for AMR

Fundamentals of data for AMR

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  • 6 hours study
  • Level 2: Intermediate
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    • Antimicrobial resistance (AMR) is a major global concern because drug-resistant infections can kill, spread to others, and impose huge costs on individuals and society. In order to tackle this problem we first need to understand it; we can do this by collecting and sharing high-quality data that is relevant to AMR.

      Data relating to AMR means that trends in resistance and antimicrobial use can be monitored and used to make better decisions to help tackle the AMR crisis. As an AMR surveillance professional, you have a key role to play in this surveillance process, whether it is in collecting, analysing or interpreting data, or in using the data to develop new policies and practices.

      This Fleming Fund course, Tackling antimicrobial resistance, comprises a series of online modules. The aim of this course is to help you to identify, develop and apply skills and knowledge relevant to your role in order to change and improve your working practice and the practice of people that you work with. 

      Fundamentals of data for AMR introduces the basic concepts, definitions and sources of data related to AMR. It looks at why we need to collect, analyse and report on AMR data, as well as data on antimicrobial use (AMU) and antimicrobial consumption (AMC).

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    • This course is part of a collection

      This course is part of a collection

      This course is part of a collection of courses called Tackling antimicrobial resistance. There are 25 courses in this collection so you may find other courses here that maybe of interest to you.

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    • Course learning outcomes

      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.
    • Course dates:

      First Published 22/02/2021.

      Updated 18/06/2021

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    Course reviews

    • Oluwafikemi Iji

      Oluwafikemi Iji2 April 2024 3:22

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    • Kinley Gyem

      Kinley Gyem23 July 2021 8:50

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    • Saraswati Dawadi

      Saraswati Dawadi16 February 2021 11:23

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    About this course

    • 6 hours study
    • Level 2: Intermediate
    • Gain a digital badge

    Ratings

    5 out of 5 stars

    Sign up to get more

    You can start learning at any time. By signing up and enrolling you can track your progress and earn a Statement of Participation upon completion, all for free.

    View this course

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