Advancements in genomic surveillance technology can detect deadly' superbugs', preventing their proliferation and transmission, thus improving global health outcomes.

Antimicrobial resistance, caused by the evolution of bacteria, viruses, fungi, and parasites, is causing increased risk of disease transmission, severe illness, and mortality. If not addressed, it is projected that annual global fatalities related to antimicrobial resistance could exceed 10 million by 2050, with low and middle-income nations experiencing the most significant impact.

Addressing Global Antimicrobial Resistance

"Antimicrobial resistance is a complex and global threat requiring large-scale, co-ordinated and cross-disciplinary collaboration to tackle," said Professor Steven Djordjevic from the Australian Institute for Microbiology and Infection at the University of Technology Sydney. "Understanding the evolution, emergence and spread of antimicrobial resistance within and between humans, animals, plants and natural environments is critical in mitigating the colossal impacts associated with this phenomenon," Djordjevic added.

"Antimicrobial resistance can occur when microorganisms acquire genetic information, either by mutation, recombination or transfer of antibiotic resistance genes from the bacterial gene pool," said Professor Erica Donner from the University of South Australia.

"Genomic technologies, combined with AI and machine learning, are powerful platforms for determining resistance trends. They can identify instances where microbes and their genetic material move between different environments, evaluating the impact of intervention strategies. The evolution of antimicrobial resistance is a complex process that includes the overuse and misuse of antibiotics, metals and disinfectants in medicine and agriculture, and widely varying standards of water, sanitation and hygiene."

The Nature Reviews Genetics journal article highlights the need for comprehensive national genomic surveillance initiatives in various sectors, emphasizing the importance of data sharing at both national and international levels, highlighting the urgency of such initiatives.

The scientists offer actionable suggestions for the adoption of genomics-driven surveillance and risk-mitigation approaches, highlighting the necessity for inclusive solutions that facilitate the involvement of partners from lower- and middle-income nations.