[OC] The Syrian civil war has killed hundreds of thousands, displaced millions, and caused poor health and widespread poverty Visualization

What This Visualization Shows

This data visualization displays "[OC] The Syrian civil war has killed hundreds of thousands, displaced millions, and caused poor health and widespread poverty" and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on Most of our [work on war and peace](https://ourworldindata.org/war-and-peace) focuses on the people killed directly in the fighting. But war has many other costs: it worsens people’s health, leaves them without work, and pushes them out of their homes.

The chart shows this for the civil war in Syria. Since the war began in 2011, more than 400,000 people have been killed in the fighting. At the same time, annual deaths increased as more people died from other causes. Young children were especially affected: estimates suggest that the number of annual child deaths more than doubled.

The war has also forced millions of people to leave their homes: in total, more than seven million are displaced within Syria, and almost as many are refugees [elsewhere](https://ourworldindata.org/data-insights/almost-half-of-people-born-in-syria-have-left-where-have-they-gone).

It also became much harder for people to make a living. Average living standards, measured by GDP per capita, have more than halved since the war began. As a result, poverty and hunger have risen sharply.

These numbers come with uncertainty because conflict makes it hard and dangerous to collect data.

This shows that to understand the costs of war, we need to have a broad perspective and see its impacts on health, displacement, and living standards.

[Millions have died in conflicts since the Cold War; learn more about where and how.](https://ourworldindata.org/conflict-deaths-breakdown), which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

This data visualization represents a sophisticated analysis of complex information patterns that provide valuable insights into underlying trends and relationships. Data visualization serves as a bridge between raw numerical data and human understanding, transforming abstract statistics into comprehensible visual narratives.

The power of data visualization lies in its ability to reveal patterns, outliers, and correlations that might not be apparent in traditional tabular formats. Through careful selection of chart types, color schemes, and interactive elements, effective visualizations can communicate complex information quickly and accurately to diverse audiences.

Modern data visualization combines statistical analysis with design principles to create compelling visual stories. This interdisciplinary approach requires understanding both the underlying data and the cognitive processes involved in visual perception. The result is more effective communication of quantitative insights that can inform decision-making and drive positive change.

Data Analysis and Insights

The patterns revealed in this visualization demonstrate the importance of systematic data analysis in understanding complex phenomena. By examining different data segments, time periods, and categorical breakdowns, we can identify trends that inform strategic planning and decision-making processes.

Statistical analysis of this data reveals variations across different dimensions that provide insights into underlying drivers and relationships. These patterns help identify areas of opportunity, potential risks, and key performance indicators that can guide future actions and resource allocation.

The analytical approach used in this visualization enables comparison across different categories, time periods, or geographic regions, revealing insights that support evidence-based decision-making. This type of analysis is essential for organizations seeking to optimize performance and understand complex market dynamics.

Significance and Applications

This data visualization has important implications for understanding trends and patterns that affect decision-making across multiple sectors. The insights derived from this analysis can inform policy development, business strategy, resource allocation, and operational improvements.

For analysts, researchers, and decision-makers, this type of data visualization provides essential insights for strategic planning and performance optimization. Whether addressing operational challenges, market analysis, or policy development, understanding data patterns helps create more effective strategies and solutions.

The broader significance lies in how this information contributes to our understanding of complex systems and relationships. This knowledge helps predict future trends, identify potential challenges, and develop more informed approaches to problem-solving and opportunity identification.