Medical aid to war victims in Syria in 2019: a report of organized healthcare support from a charity organization

Abstract

Background: In 2011, a civil war started in Syria, which is on-going and has reached a death toll of over 400,000 people. Humanitarian organizations, including Aid to The Church in Need (ACN), have strived to provide help and medical support to the civilian victims.

Methods: We performed a retrospective analysis of data gathered in ACN projects in Syria in 2019. The datasets included descriptions of diseases, treatments, costs, cities, and hospitals. For each patient, we assigned the following additional categories: type of help (treatment, diagnosis, or nonmedical), type of treatment (medical or surgical), medical specialty, gross anatomic region, and presence of trauma.

Results: A total of 3835 patients benefited from ACN support in Syria in 2019. The majority of financial support went towards treatment (78.4%), while other support went towards nonmedical help (15.7%) or providing a diagnosis (5.9%). Among treatments, 66.6% were medical and 33.4% surgical. The most common medical specialty was internal medicine (48.4%), followed by public health (13.7%) and surgery (7.3%). Anatomic region was undefined in 68.3% of cases and, when defined, was most commonly the abdominal cavity and pelvis (13%). The vast majority of cases 95.1%) were not associated with trauma. Procedural costs were highest in the Valley of Christians region, and lowest in Tartous. Network graphs were used to visualize the three most common diagnoses and treatments for each medical specialty.

Conclusions: The present report describes the treatment of war victims in Syria in 2019. The patients lacked the most basic medical or surgical healthcare. Charity organizations, like ACN, constitute a valuable source of information about the healthcare of war victims. Unfortunately, the methods of describing medical treatment provided to civilian victims remain underdeveloped. Future studies will require the cooperation of healthcare providers, humanists, and social workers. The present findings can help to optimize the provision of humanitarian help by charity organizations, by tailoring projects to the specific needs of Syrian war victims.

Keywords: Healthcare support; Report; Syria; War victims.

Fig. 1

Bubble map of Syria presenting the costs of medical procedures according to region. The size of bubbles near the name of a location is proportional to the cost of medical procedures (in USD). Additionally, the cost in USD is color-coded in the plasma palette, with the lowest cost denoted by blue and the highest by yellow

Fig. 2

Network graph presenting the three most common diagnoses per specialty assigned to patients in Syria in 2019 by Aid to the Church in Need. The medical specialty categories are indicated by node color: cardiology (red), internal medicine (brown), neurology (blue), neurosurgery (green), obstetrics and gynecology (white), oncology (black), ophthalmology (violet), orthopedics (beige), otorhinolaryngology (cyan), pediatrics (gold), psychiatry (plum), public health (lime), and radiology (aqua). The node size (shows as dots) is proportional to the number of diagnoses. Edges (connections between nodes) are shown in grey. ADHD – attention-deficit hyperactivity disorder, CT – computed tomography, MRI – magnetic resonance imaging, PET – positron emission tomography

Fig. 3

Network graph presenting three most common treatments per specialty provided to patients in Syria in 2019 by Aid to the Church in Need. The medical specialty categories are illustrated by node color: cardiology (red), internal medicine (brown), neurology (blue), neurosurgery (green), obstetrics and gynecology (white), oncology (black), ophthalmology (violet), orthopedics (beige), otorhinolaryngology (cyan), pediatrics (gold), psychiatry (plum), public health (lime), and radiology (aqua). The node size (shows as dots) is proportional to the number of treatments. Edges (connections between nodes) are shown in grey. ADHD – attention-deficit hyperactivity disorder, CT – computed tomography, MRI – magnetic resonance imaging, PET – positron emission tomography