Confidence interval methods for antimicrobial resistance surveillance data

Confidence interval methods for antimicrobial resistance surveillance data

Abstract Background Antimicrobial resistance (AMR) is one of the greatest global health challenges today, but burden assessment is hindered by uncertainty of AMR prevalence estimates. Geographical representation of AMR estimates typically pools data collected from several laboratories; however, thes...

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Bibliographic Details
Main Authors: Erta Kalanxhi, Gilbert Osena, Geetanjali Kapoor, Eili Klein
Format: Article
Language:English
Published: BMC 2021-06-01
Series:Antimicrobial Resistance and Infection Control
Subjects:
Antimicrobial resistance
Confidence intervals
Data correlation
Cluster-robust errors
Online Access:https://doi.org/10.1186/s13756-021-00960-5

Internet

https://doi.org/10.1186/s13756-021-00960-5

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