Challenges in Forecasting Antimicrobial Resistance

Sen Pei, Seth Blumberg, Jaime Cascante Vega, Tal Robin, Yue Zhang, Richard J. Medford, Bijaya Adhikari, Jeffrey Shaman

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)679-685
Number of pages7
JournalEmerging Infectious Diseases
Volume29
Issue number4
DOIs
StatePublished - Apr 2023

ASJC Scopus subject areas

  • Epidemiology
  • Microbiology (medical)
  • Infectious Diseases

Fingerprint

Dive into the research topics of 'Challenges in Forecasting Antimicrobial Resistance'. Together they form a unique fingerprint.

Cite this