A Global Survey of Adverse Event Following Immunization Surveillance Systems for Pregnant Women and Their Infants
Notice bibliographique
Résumé
Background. Expansion of maternal immunization programs is a key priority of the World Health Organization (WHO). Systematic surveillance for adverse events following immunization (AEFI) in pregnancy is needed to capture rare serious adverse events, particularly given the paucity of safety data in this population. A systematic review identified only 16 reports of AEFI surveillance programs for pregnant women and their offspring. The study objective was to identify existing but unpublished active and passive AEFI surveillance systems for pregnant women and their offspring in WHO member countries. Methods. Immunization program managers, national regulators and vaccine safety experts in 148 countries were invited to complete a 14-item online questionnaire in English, French or Spanish. The survey captured maternal immunization policies, and active and passive AEFI surveillance systems for pregnant women and infants. Analysis was descriptive. Stratified analysis was conducted by country income level (using World Bank definitions) and WHO region. Population coverage of AEFI surveillance systems was estimated. Results. There were 51 respondents from 47/148 (32%) countries. Responses were received from all WHO regions. Response rates were 40% among high-income countries (HIC), 30% among middle-income countries (MIC) and 21% among low-income countries (LIC) (p = 0.3). Thirty countries (64%) had a national maternal immunization policy. Active AEFI surveillance systems to detect outcomes in women and/or infants were reported in 5/19 (26%) HIC, 4/23 (17%) MIC and 2/5 (40%) LIC. Passive surveillance systems were in place in 16 (84%) HIC, 19 (83%) MIC and 4 (80%) LIC. At least 8% of the worldwide birth cohort (131,000,000 births/year) is covered by active surveillance for AEFI in mothers and/or infants, and at least 56% is covered by passive AEFI surveillance. Data from 1 active and 3 passive systems have been published. Conclusion. This study identified 50 active and passive AEFI surveillance systems that capture outcomes in pregnant women and/or infants, but few have published findings. AEFI surveillance appears to be feasible in low and high resource settings. The findings will be used to develop recommendations for improving AEFI surveillance and for sharing of information on vaccine safety in pregnancy. Disclosures. All authors: No reported disclosures.
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 | 0,001 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».