Overview of attacks against civilian infrastructure during the Syrian civil war, 2012–2018

• Published in: BMJ global health Vol. 6; no. 10; p. e006384
• Main Authors: Muzzall, Evan, Perlman, Brian, Rubenstein, Leonard S, Haar, Rohini J
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd 01-10-2021; BMJ Publishing Group LTD; BMJ Publishing Group
• Subjects: Civilians; Datasets; Health administration; Health care; Health facilities; health policies and all other topics; Health services; health systems; Human rights; Humanitarianism; Infrastructure; International law; Investigations; Original Research; Sanitation; Social networks; Trauma; Violations; Violence; War; Weapons; United States > US; Syria
• ISSN: 2059-7908; 2059-7908
• DOI: 10.1136/bmjgh-2021-006384

BackgroundHundreds of thousands of people have been killed during the Syrian civil war and millions more displaced along with an unconscionable amount of destroyed civilian infrastructure.MethodsWe aggregate attack data from Airwars, Physicians for Human Rights and the Safeguarding Health in Conflict Coalition/Insecurity Insight to provide a summary of attacks against civilian infrastructure during the years 2012–2018. Specifically, we explore relationships between date of attack, governorate, perpetrator and weapon for 2689 attacks against five civilian infrastructure classes: healthcare, private, public, school and unknown. Multiple correspondence analysis (MCA) via squared cosine distance, k-means clustering of the MCA row coordinates, binomial lasso classification and Cramer’s V coefficients are used to produce and investigate these correlations.ResultsFrequencies and proportions of attacks against the civilian infrastructure classes by year, governorate, perpetrator and weapon are presented. MCA results identify variation along the first two dimensions for the variables year, governorate, perpetrator and healthcare infrastructure in four topics of interest: (1) Syrian government attacks against healthcare infrastructure, (2) US-led Coalition offensives in Raqqa in 2017, (3) Russian violence in Aleppo in 2016 and (4) airstrikes on non-healthcare infrastructure. These topics of interest are supported by results of the k-means clustering, binomial lasso classification and Cramer’s V coefficients.DiscussionFindings suggest that violence against healthcare infrastructure correlates strongly with specific perpetrators. We hope that the results of this study provide researchers with valuable data and insights that can be used in future analyses to better understand the Syrian conflict.