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An Approach to Track and Analyze the Trend of Antimicrobial Resistance Using Python: A Pilot Study for Anand, Gujarat, India—May 2022–August 2023.

Authors :
Khound, Priyanshu
Pandya, Himanshu
Patel, Rupal
Patel, Naimika
Darji, Siddhi A.
Trivedi, Purvi
Mehta, Vandan
Raulji, Avani
Banerjee, Devjani
Source :
Microbial Drug Resistance: Mechanism, Epidemiology, & Disease. Jan2024, Vol. 30 Issue 1, p1-20. 20p.
Publication Year :
2024

Abstract

The present work deals with the analysis and monitoring of bacterial resistance in using Python for the state of Gujarat, India, where occurrences of drug-resistant bacteria are prevalent. This will provide an insight into the portfolio of drug-resistant bacteria reported, which can be used to track resistance behavior and to suggest a treatment regime for the particular bacteria. The present analysis has been done using Python on Jupyter Notebook as the integrated development environment and its data analysis libraries such as Pandas, Seaborn, and Matplotlib. The data have been loaded from excel file using Pandas and cleaned to transform features into required format. Seaborn and Matplotlib have been used to create data visualizations and represent the data inexplicable manner using graphs, plots, and tables. This program can be used to study disaster epidemiology, tracking, analyzing, and surveillance of antimicrobial resistance with a proper system integration approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10766294
Volume :
30
Issue :
1
Database :
Academic Search Index
Journal :
Microbial Drug Resistance: Mechanism, Epidemiology, & Disease
Publication Type :
Academic Journal
Accession number :
174796402
Full Text :
https://doi.org/10.1089/mdr.2023.0057