Confidence interval methods for antimicrobial resistance surveillance data
Abstract
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, these aggregations may introduce bias by not accounting for the heterogeneity of the population that each laboratory represents.We used AMR data from up to 381 laboratories...
Paper Details
Title
Confidence interval methods for antimicrobial resistance surveillance data
Published Date
Jun 9, 2021
Volume
10
Issue
1
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