Gun violence is a vexing problem in the U.S. that needs little explanation. Adequate information and insight are still lacking about ownership and use of firearms, the causes and consequences of their use, and the effects of interventions and technological innovations. The sociological context and the implications on health and on law enforcement involve a variety of disciplines; the spectrum of questions that arise affects policymakers at all levels. Implicit is that obtaining adequate information and understanding requires data of high quality and analyses that can withstand scrutiny by all concerned.

This book provides an overview of adequate data and informative analyses on several important topics in gun violence research. This book exposes the opportunities and needs for the latest statistical efforts and engages new statisticians and data scientists to work across disciplinary lines to help understand and mitigate the effects of gun violence.

Key Features:

· Provides multi-disciplinary perspectives from researchers in criminology, political science, public policy, public health, sociology, and statistics and present their latest efforts in gun violence research across disciplinary lines.

· Provides an overview of the state-of-art statistical and machine learning methods in gun violence research, including network models, synthetic control methods, point processes models, and neural networks.

· Provides a comprehensive review of data sources and describe the evolution of the quality of these data and the reasons for the biases in the historical data sources.