Component costs of foodborne illness: a scoping review
Notice bibliographique
Résumé
BACKGROUND: Governments require high-quality scientific evidence to prioritize resource allocation and the cost-of-illness (COI) methodology is one technique used to estimate the economic burden of a disease. However, variable cost inventories make it difficult to interpret and compare costs across multiple studies. METHODS: A scoping review was conducted to identify the component costs and the respective data sources used for estimating the cost of foodborne illnesses in a population. This review was accomplished by: (1) identifying the research question and relevant literature, (2) selecting the literature, (3) charting, collating, and summarizing the results. All pertinent data were extracted at the level of detail reported in a study, and the component cost and source data were subsequently grouped into themes. RESULTS: Eighty-four studies were identified that described the cost of foodborne illness in humans. Most studies (80%) were published in the last two decades (1992-2012) in North America and Europe. The 10 most frequently estimated costs were due to illnesses caused by bacterial foodborne pathogens, with non-typhoidal Salmonella spp. being the most commonly studied. Forty studies described both individual (direct and indirect) and societal level costs. The direct individual level component costs most often included were hospital services, physician personnel, and drug costs. The most commonly reported indirect individual level component cost was productivity losses due to sick leave from work. Prior estimates published in the literature were the most commonly used source of component cost data. Data sources were not provided or specifically linked to component costs in several studies. CONCLUSIONS: The results illustrated a highly variable depth and breadth of individual and societal level component costs, and a wide range of data sources being used. This scoping review can be used as evidence that there is a lack of standardization in cost inventories in the cost of foodborne illness literature, and to promote greater transparency and detail of data source reporting. By conforming to a more standardized cost inventory, and by reporting data sources in more detail, there will be an increase in cost of foodborne illness research that can be interpreted and compared in a meaningful way.
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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».