Early warning is a major element of disaster risk reduction. It prevents loss of life and reduces the economic and material impact of disasters. To be effective, early warning systems need to actively involve the communities at risk, facilitate public education and awareness of risks, effectively disseminate alerts, and warnings and ensure there is constant state of preparedness. A complete and effective early warning system supports four main functions: risk analysis, monitoring and warning; dissemination and communication; and a response capability.

Risk analysis involves systematically collecting data and undertaking risk assessments of predefined hazards and vulnerabilities. Monitoring and warning involves a study of the factors that indicate a disaster is imminent, as well as the methods used to detect these factors. Dissemination and communication concerns communicating the risk information and warnings to reach those in danger in a way that is clear and understandable. Finally, an adequate response capability requires the building of national and community response plan, testing of the plan, and the promotion of readiness to ensure that people know how to respond to warnings.

Warning system is any system of biological or technical nature deployed by an individual or group to inform of a future danger. Its purpose is to enable the deployer of the warning system to prepare for the danger and act accordingly to mitigate or avoid it.

Biological warning systems

Man-made warning systems

Civilian warning systems

The Integrated Conflict Early Warning System (ICEWS) combines a database of political events and a system using these to provide conflict early warnings. It is supported by the Defense Advanced Research Projects Agency in the United States. The database as well as the model used by Lockheed Martin Advanced Technology Laboratories are currently undergoing operational test and evaluation by the United States Southern Command and United States Pacific Command.

History

ICEWS was a DARPA program conceived and led by Dr. Sean P. O'Brien that launched in 2008. In March 2010, O'Brien authored an article that compared ICEWS with past efforts in the realm, including systems designed by Bruce Bueno de Mesquita. According to the paper, the first of three phases of the ICEWS involved a competition between different groups to successfully predict events of interest based on historical data. The winning team, Lockheed Martin Advanced Technology Laboratories, combined six different conflict modeling systems, including agent-based models such as Barry Silverman's Factionalism and Ian Lustick's Political Science-Identity (PSI) computational modeling platforms, logistic regression models such as those developed by Philip A. Schrodt and the Bayesian statistics model used by Steve Shellman, and geo-spatial network models built by Michael D. Ward.