Work

Health security at genomic artificial intelligence–antimicrobial resistance frontiers in low-income countries

Year: 2025

Type: article

Abstract: In low-income countries (LICs), the high burden of infectious diseases intersects with extraordinary genomic and ecological diversity; however, resources for surveillance, data infrastructure, and skilled personnel remain scarce. This imbalance creates a major gap: although LICs bear the brunt of emerging and resistant infections, they are least equipped to harness genomic data for real-time health security decision making.1 Genomic artificial intelligence (AI), the integration of machine learning into pathogen genomic analysis, offers a transformative approach to antimicrobial resistance (AMR) preparedness.

Source: The Lancet Microbe

DOI: 10.1016/j.lanmic.2025.101282

Authors: Dickson Aruhomukama, Dathan M Byonanebye, Francis Kakooza

Institutions: Infectious Diseases Institute, Makerere University

Language: English

Topic: Antibiotic Use and Resistance

Subfield: Applied Microbiology and Biotechnology

Field: Immunology and Microbiology

Domain: Life Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure, Reduced inequalities

Open Access status: gold

Estimated APC paid: $7,280