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Enregistrement W2792598093 · doi:10.1093/milmed/usx004

Beyond the Dirty Dozen: A Proposed Methodology for Assessing Future Bioweapon Threats

2017· article· en· W2792598093 sur OpenAlex
Theodore J. Cieslak, Mark G. Kortepeter, Ronald J Wojtyk, Hugo-Jan Jansen, Ricardo A. Reyes, James O. Smith

Pourquoi ce travail est dans la base

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Notice bibliographique

RevueMilitary Medicine · 2017
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueBacillus and Francisella bacterial research
Établissements canadiensCanadian Armed Forces
Organismes subventionnairesnon disponible
Mots-clésBiodefenseOutbreakPreparednessDiseaseMedicineBiological warfareComputer securityEnvironmental healthRisk analysis (engineering)Computer scienceVirologyPolitical scienceLaw

Résumé

récupéré en direct d'OpenAlex

Background: Defense policy planners and countermeasure developers are often faced with vexing problems involving the prioritization of resources and efforts. This is especially true in the area of Biodefense, where each new emerging infectious disease outbreak brings with it questions regarding the causative agent's potential for weaponization. Recent experience with West Nile Virus, Severe Acute Respiratory Syndrome, Monkeypox, and H1N1 Influenza highlights this problem. Appropriately, in each of these cases, the possibility of bioterrorism was raised, although each outbreak ultimately proved to have a natural origin. In fact, determining whether an outbreak has an unnatural origin can be quite difficult. Thus, the questions remain: could the causative agents of these and other emerging infectious disease outbreaks pose a future weaponization threat? And how great is that threat? Should precious resources be diverted from other defense efforts in order to prepare for possible hostile employment of novel diseases by belligerents? Answering such critical questions requires some form of systematic threat assessment. Methods: Through extensive collaborative work conducted within NATO's Biomedical Advisory Council, we developed a scoring matrix for evaluating the weaponization potential of the causative agents of such diseases and attempted to validate our matrix by examining the reproducibility of data using known threat agents. Our matrix included 12 attributes of a potential weapon and was provided, along with detailed scoring instructions, to 12 groups of biodefense experts in 6 NATO nations. Study participants were asked to score each of these 12 attributes on a scale of 0-3: Infectivity, Infection-to-Disease Ratio (Reliability), Predictability (& Incubation Period), Morbidity & Mortality (Virulence), Ease of Large-Scale Production & Storage, Aerosol Stability, Atmospheric Stability, Ease of Dispersal, Communicability, Prophylactic Countermeasure Availability, Therapeutic Countermeasure Availability, and Ease of Detection. Reproducibility of scoring data was assessed by examining the standard deviations (SD) of mean scores. Results: Our results were unexpected. Several familiar biothreat diseases such as anthrax and tularemia were judged, by our experts, to be less threatening than many others owing to a number of factors including ease of detection, lack of communicability, and the ready availability of countermeasures. Conversely, several toxins were judged by experts to have very high potential as threat agents owing, in part, to their reliability, virulence, and a lack of available countermeasures. Agreement among experts, as determined by lower SD about a mean score, was greater for more familiar threats. Discussion: Our study was designed to provide a concise and east-to-apply set of criteria that could be used by NATO nations to evaluate emerging infectious disease threats with respect to their weaponization potential. Our results were unexpected. We believe that a lack of appropriate weighting factors may explain these results and suggest that future studies weigh each of the 12 proposed criteria based on the intended use of the assessment data and other situational factors. We believe that the greatest value of our study lies in a codification of the attributes of a biological weapon.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,699
Score d'incertitude au seuil0,532

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,082
Tête enseignante GPT0,392
Écart entre enseignants0,310 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle