Sensors for surveillance of RNA viruses: a One Health perspective
The Lancet Microbe·
- DOI
- 10.1016/j.lanmic.2024.101029
- PMID
- 39681124
- PMCID
- —
- OpenAlex
- W4405359290
- Study type
- Commentary
- Publisher
- Elsevier BV
- Article type
- journal-article
- Integrity
- current
Why this research matters now
Enhanced RNA virus sensing could strengthen infectious disease surveillance systems and support One Health strategies to address pandemic risk from cross-species transmission events.
Structured evidence summary
Research question
The review examines recent advances in sensing technologies for RNA virus detection and their potential deployment in One Health surveillance strategies.
Study design
This is a narrative review that evaluates sensing technologies for detecting viral biomarkers including RNA, antigens, and antibodies, comparing their principles and performance characteristics.
Population and setting
The review discusses RNA virus surveillance across human, animal, and environmental contexts, with particular attention to resource-limited regions and reference to the 2024 H5N1 outbreak in US dairy farms.
Main findings
Recent sensor technologies can achieve sensitivity and reliability comparable to standard laboratory equipment while offering advantages in size, cost, and ease of use. The review identifies that current centralized detection systems are insufficient for required surveillance levels, especially in resource-limited settings.
Public-health relevance
Enhanced RNA virus sensing could strengthen infectious disease surveillance systems and support One Health strategies to address pandemic risk from cross-species transmission events.
Important limitations
This summary is limited to the supplied single-article abstract and metadata. The review discusses expected challenges in deploying sensors within the One Health framework, but the abstract does not detail these challenges or provide comparative performance data for specific sensor platforms.
GIDS interpretation
This review article was classified under One Health, Surveillance, and multiple disease tags including H5N1 and Influenza, reflecting its focus on cross-cutting detection technologies rather than investigation of a specific outbreak signal.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 12 auditable classifier relationships to diseases, places, topics, and study design.