A Comparative Epidemiology Model for Understanding Mental Morbidity and Planning Health System Response to the COVID-19 Pandemic
Notice bibliographique
Résumé
Introduction: This particular coronavirus disease is a pandemic giving rise to great global affliction and uncertainty, even among those who have dedicated their lives to health care or the study of disease, or both. Notwithstanding those directly affected, the lives of all people have been turned upside down. Each person has to cope with her or his personal situation and a story is taking shape for everyone on earth. Coronavirus disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 virus, the source of the 2020 pandemic. This paper contains brief highlights from a duplicable PubMed search of the COVID-19 literature published from January 1 to March 31, 2020, as well as a duplicable search of past influenza-related publications. Excerpts from select papers are highlighted. The main focus of this paper is a descriptive analysis of influenza and other respiratory viruses based on a 16-year population-based dataset. In addition, the paper includes analyses based on the presence or absence of mental disorder (MD) in relation to influenza and all other respiratory viruses. Methods: The investigation is descriptive and exploratory in nature. Employing a case-comparison design, a 16-year population-based dataset was analyzed to both understand the present and plan for the future. While not all viral infections are equal, this paper focuses on system responses by describing the epidemiology of respiratory viruses, such as influenza. Influenza is established in the global population and has caused epidemics in the past. Where possible direct comparisons are made between COVID-19, influenza, and other respiratory viruses. Results: Those with MD had a higher rate of viral infection per 100,000 capita compared to those with the viral infection and no MD. Further, the postviral infection MD rate was not higher compared to the MD per capita rate before viral infection. The postinfluenza rate of MD among those who were without mental disorder before influenza represents an estimate of postinfection mental health burden. Conclusions: In summary, those with preinfluenza MD are at greater risk for viral infection. Further, while the postviral infection MD rate was not higher compared to the MD per capita rate before viral infection, this independent estimate may inform the degree to which services may need to undergo a sustained increase to address the bio psychosocial needs of each served population were COVID-19 to persist and become established in the global population.
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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 ».