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Challenges in Forecasting Antimicrobial Resistance

Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms (AMROs) have been absent. In this perspective...

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Autores principales: Pei, Sen, Blumberg, Seth, Vega, Jaime Cascante, Robin, Tal, Zhang, Yue, Medford, Richard J., Adhikari, Bijaya, Shaman, Jeffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045679/
https://www.ncbi.nlm.nih.gov/pubmed/36958029
http://dx.doi.org/10.3201/eid2904.221552
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author Pei, Sen
Blumberg, Seth
Vega, Jaime Cascante
Robin, Tal
Zhang, Yue
Medford, Richard J.
Adhikari, Bijaya
Shaman, Jeffrey
author_facet Pei, Sen
Blumberg, Seth
Vega, Jaime Cascante
Robin, Tal
Zhang, Yue
Medford, Richard J.
Adhikari, Bijaya
Shaman, Jeffrey
author_sort Pei, Sen
collection PubMed
description Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms (AMROs) have been absent. In this perspective, we discuss the utility of AMRO forecasting at different scales, highlight the challenges in this field, and suggest future research priorities. We also discuss challenges in scientific understanding, access to high-quality data, model calibration, and implementation and evaluation of forecasting models. We further highlight the need to initiate research on AMRO forecasting using currently available data and resources to galvanize the research community and address initial practical questions.
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spelling pubmed-100456792023-04-01 Challenges in Forecasting Antimicrobial Resistance Pei, Sen Blumberg, Seth Vega, Jaime Cascante Robin, Tal Zhang, Yue Medford, Richard J. Adhikari, Bijaya Shaman, Jeffrey Emerg Infect Dis Perspective Antimicrobial resistance is a major threat to human health. Since the 2000s, computational tools for predicting infectious diseases have been greatly advanced; however, efforts to develop real-time forecasting models for antimicrobial-resistant organisms (AMROs) have been absent. In this perspective, we discuss the utility of AMRO forecasting at different scales, highlight the challenges in this field, and suggest future research priorities. We also discuss challenges in scientific understanding, access to high-quality data, model calibration, and implementation and evaluation of forecasting models. We further highlight the need to initiate research on AMRO forecasting using currently available data and resources to galvanize the research community and address initial practical questions. Centers for Disease Control and Prevention 2023-04 /pmc/articles/PMC10045679/ /pubmed/36958029 http://dx.doi.org/10.3201/eid2904.221552 Text en https://creativecommons.org/licenses/by/4.0/Emerging Infectious Diseases is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Perspective
Pei, Sen
Blumberg, Seth
Vega, Jaime Cascante
Robin, Tal
Zhang, Yue
Medford, Richard J.
Adhikari, Bijaya
Shaman, Jeffrey
Challenges in Forecasting Antimicrobial Resistance
title Challenges in Forecasting Antimicrobial Resistance
title_full Challenges in Forecasting Antimicrobial Resistance
title_fullStr Challenges in Forecasting Antimicrobial Resistance
title_full_unstemmed Challenges in Forecasting Antimicrobial Resistance
title_short Challenges in Forecasting Antimicrobial Resistance
title_sort challenges in forecasting antimicrobial resistance
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045679/
https://www.ncbi.nlm.nih.gov/pubmed/36958029
http://dx.doi.org/10.3201/eid2904.221552
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