The predicament of patients with suspected Ebola
Notice bibliographique
Résumé
In their Comment in The Lancet Global Health, Eugene Richardson and colleagues1Richardson ET Barrie MB Nutt CT et al.The Ebola suspect's dilemma.Lancet Glob Health. 2017; 5: e254-e256Summary Full Text Full Text PDF PubMed Scopus (25) Google Scholar criticised the tendency of many analyses of the Ebola epidemic (eg, a WHO report2Agua-Agum J Allegranzi B Ariyarajah A et al.WHO Ebola Response TeamAfter Ebola in West Africa—unpredictable risks, preventable epidemics.N Engl J Med. 2016; 375: 587-596Crossref PubMed Scopus (181) Google Scholar) to ignore that it may be rational for a patient with a fever to avoid an Ebola treatment unit. They use the prisoner's dilemma to explain such non-cooperative behaviour. The prisoner's dilemma, however, is not the most appropriate analytical framework for this situation. It involves two parties, each with their own interests, while the patient's dilemma might better be understood as a game against nature, ie, without a rational and self-interested opponent. We suggest that the threshold approach introduced by Pauker and Kassirer3Pauker SG Kassirer JP Therapeutic decision making: a cost-benefit analysis.N Engl J Med. 1975; 293: 229-234Crossref PubMed Scopus (339) Google Scholar, 4Djulbegovic B Van den Ende J Hamm RM Mayrhofer T Hozo I Pauker SG International Threshold Working GroupWhen is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation.Eur J Clin Invest. 2015; 45: 485-493Crossref PubMed Scopus (31) Google Scholar better explains the described phenomenon. The threshold model prescribes a probability of disease at which treatment becomes a better option than no treatment. The threshold is a function of the relative effects of the possible actions and compares the benefit of treating a true Ebola patient against the harm of treating a non-Ebola patient. In this example, exposure to the virus from contact with other (true) Ebola patients represents the harm condition. Using the mortality numbers provided,1Richardson ET Barrie MB Nutt CT et al.The Ebola suspect's dilemma.Lancet Glob Health. 2017; 5: e254-e256Summary Full Text Full Text PDF PubMed Scopus (25) Google Scholar the benefit is the mortality reduction for true Ebola patients (70·8%–64·3%=6·5%), while the harm is the mortality increase for patients without Ebola (16·1%–0·2%=15·9%). The treatment threshold is calculated as harm/(harm+benefit). Given these data, the treatment threshold is 71·0% (figure). If individuals with suspected Ebola assume that their probability of having Ebola is below this threshold—eg, Richardson and colleagues1Richardson ET Barrie MB Nutt CT et al.The Ebola suspect's dilemma.Lancet Glob Health. 2017; 5: e254-e256Summary Full Text Full Text PDF PubMed Scopus (25) Google Scholar assume a probability of 50%—the rational behaviour from the individual's point of view is to not seek treatment. In conclusion, the threshold model3Pauker SG Kassirer JP Therapeutic decision making: a cost-benefit analysis.N Engl J Med. 1975; 293: 229-234Crossref PubMed Scopus (339) Google Scholar, 4Djulbegovic B Van den Ende J Hamm RM Mayrhofer T Hozo I Pauker SG International Threshold Working GroupWhen is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation.Eur J Clin Invest. 2015; 45: 485-493Crossref PubMed Scopus (31) Google Scholar might explain patients' avoidance of Ebola treatment better and more elegantly than the prisoner's dilemma does. We declare no competing interests. The Ebola suspect's dilemmaIn 1950, Merrill Flood and Melvin Dresher of the RAND Corporation developed a theoretical model of cooperation and conflict, which was later formalised by Albert W Tucker as the prisoner's dilemma.1 This model represents a situation in which two prisoners each have the option to confess or not, but their sentencing outcomes depend crucially on the simultaneous choice of the other (figure).1 Fittingly, it has become the paradigmatic example of individual versus group rationality and is an often used heuristic when conveying introductory social theory to students. Full-Text PDF Open Access
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,134 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,004 | 0,009 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,021 | 0,028 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».