ReviewVirulence2013
Biosurveillance enterprise for operational awareness, a genomic-based approach for tracking pathogen virulence.
Review in Virulence, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Known and Unknown Transboundary Infectious Diseases as Hybrid Threats.Frontiers in public health · 2021Article
- What We Need to Consider During and After the SARS-CoV-2 Pandemic.Vector borne and zoonotic diseases (Larchmont, N.Y.) · 2020Article
- Global Spread of Hemorrhagic Fever Viruses: Predicting Pandemics.Methods in molecular biology (Clifton, N.J.) · 2018Article
- Crowdsourced direct-to-consumer genomic analysis of a family quartet.BMC genomics · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
To protect our civilians and warfighters against both known and unknown pathogens, biodefense stakeholders must be able to foresee possible technological trends that could affect their threat risk assessment. However, significant flaws in how we prioritize our countermeasure-needs continue to limit their development. As recombinant biotechnology becomes increasingly simplified and inexpensive, small groups, and even individuals, can now achieve the design, synthesis, and production of pathogenic organisms for offensive purposes. Under these daunting circumstances, a reliable biosurveillance approach that supports a diversity of users could better provide early warnings about the emergence of new pathogens (both natural and manmade), reverse engineer pathogens carrying traits to avoid available countermeasures, and suggest the most appropriate detection, prophylactic, and therapeutic solutions. While impressive in data mining capabilities, real-time content analysis of social media data misses much of the complexity in the factual reality. Quality issues within freeform user-provided hashtags and biased referencing can significantly undermine our confidence in the information obtained to make critical decisions about the natural vs. intentional emergence of a pathogen. At the same time, errors in pathogen genomic records, the narrow scope of most databases, and the lack of standards and interoperability across different detection and diagnostic devices, continue to restrict the multidimensional biothreat assessment. The fragmentation of our biosurveillance efforts into different approaches has stultified attempts to implement any new foundational enterprise that is more reliable, more realistic and that avoids the scenario of the warning that comes too late. This discussion focus on the development of genomic-based decentralized medical intelligence and laboratory system to track emerging and novel microbial health threats in both military and civilian settings and the use of virulence factors for risk assessment. Examples of the use of motif fingerprints for pathogen discrimination are provided.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.