Analysis of Disparities in the Initial Health Care Response to the February 2023 Earthquakes in Turkey and Syria
Notice bibliographique
Résumé
OBJECTIVES: This study analyzes disparities in initial health care responses in Turkey and Syria following the 2023 earthquakes. METHODS: Using Humanitarian Data Exchange, Crude Mortality Rates (CMR) and injury rates in both countries were calculated, and temporal trends of death tolls and injuries in the first month post- catastrophe were compared. World Health Organization (WHO) Flash Appeal estimated funding requirements, and ratios of humanitarian aid personnel in Urban Search and Rescue (USAR) teams per population from ReliefWeb and MAPACTION data were used to gauge disparities. RESULTS: 56 051 096 individuals were exposed, with Turkey having 44 million vs 12 million in Syria. Turkey had higher CMR in affected areas (10.5 vs. 5.0 per 10,000), while Syria had higher CMR in intensely seismic regions (9.3 vs. 7.7 per 1,000). Turkey had higher injury rates (24.6 vs. 9.9 per 10 000). Death and injury rates plateaued in Syria after 3 days, but steadily rose in Turkey. Syria allocated more funding for all priorities per population except health care facilities' rehabilitation. Turkey had 219 USAR teams compared to Syria's 6, with significantly more humanitarian aid personnel (23 vs. 2/100,000). CONCLUSIONS: Significant disparities in the initial health care response were observed between Turkey and Syria, highlighting the need for policymakers to enhance response capabilities in conflict-affected events to reduce the impact on affected populations. NARRATIVE ABSTRACT: The 2023 Turkish-Syrian earthquakes, the most devastating in the region since 1939, heightened challenges in Syria's health care system amid ongoing conflict, disrupting Gaziantep's humanitarian aid supply route. The initial health care responses post-earthquakes in Turkey and Syria were analyzed through a descriptive study, where Crude Mortality Rates (CMR) and injury rates during the first week were calculated. The World Health Organization's funding priorities and the ratio of humanitarian aid personnel in Urban Search and Rescue teams per population were assessed. Turkey had 4-fold higher earthquake exposure and experienced higher CMR and injuries per population, while Syria had higher CMR in intensely seismic regions. Temporal trends showed plateaued death and injury rates in Syria within 3 days, while Turkey's continued to increase. Syria required more funding across nearly all priorities while Turkey had more humanitarian aid personnel per population. Significant health care response disparities were observed, emphasizing the imperative for policymakers to enhance initial responses in conflict-affected events.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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.
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