Using network science and numerous mathematical computations, the study observes how social behaviors can enhance or even reduce the transmission of disease in a population.
Leading the project is Dr. Ira Schwartz, head of Nonlinear System Dynamics Section in the Plasma Physics Division, and applied math task area coordinator.
“A considerable result of the research is our ability to quantify how social trends and behaviors, through mathematical analysis, change large scale breakouts when a disease or infection is introduced to a social network,” said Schwartz.
Working alongside Schwartz is Dr. Jason Hindes, a post-doctoral fellow at NRL, together they are investigating how networks of connected agents, such as people, devices and organisms alter normalcy and structure in uncertain environments. They have created new theories that apply network science, uncertainty and nonlinear dynamics that reveal how alterations in pattern occur on a large scale, and how those changes can be managed and controlled.
“The general point of the work is to understand how uncertainty and randomness can cause sudden and dramatic changes in the intricacies of complex systems communicating through networks,” said Hindes. “Knowledge in hand, randomness then becomes a tool for controlling networks.”
The research provides insight to optimally determine how those with few, or several connections should be proportionally treated to eliminate an outbreak. Prior studies have used the idea of primarily treating the most concentrated area of a contacted network.
“Although a disconnection between social behaviors and health seems to exist, there is a direct relation,” said Schwartz. “In our long term vision for the project, we wanted to contribute our new mathematical tools to the field of epidemiology.”
According to the Institute of Medicine (U.S.) Committee on Assessing Interactions Among Social Behavioral, and Genetic Factors in Health, epidemiological studies in adult populations show that social networks can predict the risk of all-cause and cause-specific mortality.
The foundation of Schwartz and Hindes’ research qualifies the connection of individuals in a network and reduce the spread of disease and infection. For this reason, the study has far more applications considering humanity itself is a network of connected individuals.
“Our mathematical and computational approach is logical in understanding terrorist cell recruitment, delayed coupled laser arrays, and autonomous collaborative robots, all of which depend on network communication,” Hindes said.
Schwartz and Hindes are confident their research can be used for real-time counterterrorism. The techniques used in the study comprehend how malevolent ideas spread, and turn into actions that potentially threaten national security. This aspect of the research lends itself to the idea of completely, or drastically degrading terror cell enlistment efforts, even before they start.
The Navy stands to greatly benefit from both scientists’ research. In recent years the Navy has given much attention and planning to the future of its autonomous capabilities. Ships and systems, once worked by humans, are now being enhanced and modified through networked autonomous systems. Schwartz and Hinde’s research will provide the Navy’s autonomous systems a warfighting edge by providing the formula in how to maintain patterns, even when operating in unknown and hostile environments.