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ORIGINAL RESEARCH article

Front. Microbiol.
Sec. Antimicrobials, Resistance and Chemotherapy
Volume 16 - 2025 | doi: 10.3389/fmicb.2025.1513454

QAAPT: An interoperable Web-based Open-Source tool for Antimicrobial Resistance Data Analysis and Visualization

Provisionally accepted
Mohammad Julhas Sujan Mohammad Julhas Sujan 1*Sanjay Gautam Sanjay Gautam 1*Ahmed Taha Aboushady Ahmed Taha Aboushady 1Adam Clark Adam Clark 2*Sooyoung Kwon Sooyoung Kwon 1*Hea Sun Joh Hea Sun Joh 1Marianne Holm Marianne Holm 1John Stelling John Stelling 2Florian Marks Florian Marks 1,3,4,5Nimesh Poudyal Nimesh Poudyal 1
  • 1 International Vaccine Institute, Seoul, Republic of Korea
  • 2 Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
  • 3 Cambridge Institute for Therapeutic Immunology and Infectious Disease, School of Clinical Medicine, University of Cambridge, Cambridge, England, United Kingdom
  • 4 Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg, Baden-Württemberg, Germany
  • 5 Madagascar Institute for Vaccine Research, University of Antananarivo, Antananarivo,, Madagascar

The final, formatted version of the article will be published soon.

    The analysis and visualisa:on of an:microbial resistance (AMR) surveillance data is a crucial challenge, especially in high-burden, low-middle income countries. We describe the design, development, integra:on, and implementa:on of the Quick Analysis of An:microbial Pa`erns and Trends (QAAPT) tool for AMR data analysis and visualisa:on. The QAAPT was created by the Capturing Data on An:microbial Resistance Pa`erns and Trends in Use in Regions of Asia project, led by the Interna:onal Vaccine Ins:tute (IVI). This open-source web-based tool/applica:on generates sta:s:cal and visual outputs of AMR data, offers data cura:on op:ons, and can be integrated with laboratory informa:on management systems. QAAPT is user-friendly and is operable by someone with limited exper:se in sodware or programming. As a part of the project, the tool was used to analyse data from 72 laboratories across seven different Asian countries. Here, we present the technical aspects of tool development and highlight implementa:on outcomes for analysing and genera:ng visual reports from more than 2.37 million highly heterogeneous an:microbial suscep:bility test data points.

    Keywords: An:microbial, analysis, Data, surveillance, Visualisa:on

    Received: 18 Oct 2024; Accepted: 03 Jan 2025.

    Copyright: © 2025 Sujan, Gautam, Aboushady, Clark, Kwon, Joh, Holm, Stelling, Marks and Poudyal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Mohammad Julhas Sujan, International Vaccine Institute, Seoul, Republic of Korea
    Sanjay Gautam, International Vaccine Institute, Seoul, Republic of Korea
    Adam Clark, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, Massachusetts, United States
    Sooyoung Kwon, International Vaccine Institute, Seoul, Republic of Korea

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.