Acceptability, cost-effectiveness, and capacity of a facility-based seasonal influenza vaccination among high-risk groups: a study protocol in selected tertiary care hospitals of Bangladesh
Notice bibliographique
Résumé
BACKGROUND: In Bangladesh, seasonal influenza imposes considerable disease and economic burden, especially for those at high-risk of severe disease. The most successful approach for influenza prevention is the administration of a vaccine. Many poor and middle-income nations, including Bangladesh, do not have a national strategy or program in place for seasonal influenza vaccines, despite the World Health Organization's (WHO) advice to prioritize high-risk populations. Additionally, there is a scarcity of substantial data on the cost-effectiveness of seasonal influenza vaccination in these countries. The aim of our study is to determine acceptability, health beliefs, barriers, and intention of receiving influenza vaccine among high-risk populations, assess the cost-effectiveness of implementing a facility-based seasonal influenza vaccination programme, and investigate the required capacity for a potential seasonal influenza vaccination programme. METHODS: We will undertake this study following STROBE guidelines. We will conduct the study in inpatient and outpatient departments of three selected tertiary-level hospitals leveraging the ongoing hospital-based influenza surveillance (HBIS) platform. The study population will include the WHO-defined four high-risk groups excluding healthcare workers: children six months to eight years, pregnant women, elderly ≥ 60 years, and adults with chronic diseases. We will collect quantitative data on participants' acceptability, health beliefs, barriers, and vaccination intentions using the health belief model (HBM) from patients meeting the criteria for high-risk populations attending two public tertiary-level hospitals. In one of the two public tertiary-level hospitals, we will arrange an influenza vaccination campaign before the influenza season, where the vaccine will be offered free of cost to high-risk patients, and in the second hospital, vaccination will not be offered. Both the vaccinated and unvaccinated participants will then be followed-up once a month for one year to record any influenza-like illness, hospitalization, and death. Additional data for objective two will be collected from patients with symptoms of influenza-like illness (ILI) and severe acute respiratory infection (SARI) at one public and one private hospital to determine both direct and indirect costs associated with influenza illness. We will estimate the required number of influenza vaccines, safe injections, and total storage volume utilizing secondary data. We will use a deterministic Markov decision-analytic model to estimate the cost-effectiveness of facility-based influenza vaccination in Bangladesh. DISCUSSION: The results of this study will enable the National Immunization Technical Advisory Group and the Ministry of Health & Family Welfare of Bangladesh to decide what steps to take to develop and implement an influenza vaccination strategy targeting high-risk populations. TRIAL REGISTRATION: The Clinicaltrials.gov registration number is NCT05996549. The registration for the protocol version 2.0 took place in August 2023, with the initial participant being enrolled in March 2022.
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 | 0,022 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,002 |
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 ».