Public health agencies across the United States have established early warning systems that enable prompt detection and response to disease outbreaks. In contrast, public safety officials lack similar mechanisms to identify emerging crime trends in a timely manner. Both sectors, public health and public safety, face an urgent need for rapid and accurate data to protect communities effectively.

The public health sector has established clear processes for hospitals and other providers to immediately share information on any emerging problems or threats. And it goes even further, by integrating data from a variety of sources—emergency department visits, wastewater testing, and pharmacy sales data—to spot disease outbreaks sooner than they would appear in diagnostic reporting from hospitals and clinics. This early warning system—called “syndromic surveillance”—allows public health agencies to respond more quickly with interventions that can mitigate the impact of disease outbreaks and effectively protect communities.

But the public safety sector still relies on an official crime data reporting process that is slow and cumbersome, and not linked to other sources of information. More than 19,000 U.S. law enforcement agencies independently—and voluntarily—report local crime data with inconsistent formats and varying levels of quality. It takes months to integrate these data, making it difficult to track crime patterns across jurisdictions and depriving public officials of the necessary tools to address emerging public safety concerns in a timely manner.

However, if we could develop a comprehensive public safety early warning system modeled on the public health syndromic surveillance system, we could transition from reacting to crimes in progress to proactive, tailored interventions.

Official crime statistics are reported with significant delays. The FBI releases national crime statistics nine months after the end of the prior calendar year, which is often too late for local officials to identify and prevent emerging crime patterns. For example, in the spring of 2020, gun violence spiked in major U.S. cities. Due to changes in the FBI reporting system, this increase didn’t appear in national crime statistics until the fall of 2023. Similarly, a massive surge in motor vehicle thefts in Milwaukee in the late fall of 2020 provided an early signal of an unprecedented increase across the country that peaked in 2023. By the time the national data captured the full extent of the spike, auto theft was rampant across the country.

To get useful data to local and national policymakers more quickly, NORC at the University of Chicago launched the Live Crime Tracker in 2024. The tracker monitors and reports daily incident-level data from over 50 cities in near-real time. But as effective as the tracker has been, it too is limited by substantial differences in format, standardization, and availability of data. In fact, one of the purposes of the tracker is to highlight these gaps. There is much more to be done to develop a syndromic surveillance system for public safety.

Leverage the broader public data ecosystem to measure and mitigate risk.

Housing, employment, city services, and engagement of the business community and civic organizations all influence the reality and perception of public safety. A more holistic view of public safety and public safety data that takes this complexity into account can lead to more effective policies.

The Chicago Public Safety DataHub, a partnership between NORC and the Civic Committee of Chicago, applies this holistic approach to crime-related risk factors. The datahub integrates multiple data sources for a comprehensive view of the city’s public safety landscape, including community-level risk factors like unemployment rates and community sentiment about public safety.

Our key takeaway is straightforward: while there is an early warning system in public health, there isn’t one in public safety. NORC created the Live Crime Tracker to help fill this gap by making justice data available to the public that updates in near-real time at a high frequency.

To achieve a true public safety early warning system, we need to do more than faster reporting at a higher tempo; we also need to link to other systems (such as public health data). Using a variety of timely data streams to inform program and policy decisions can make communities healthier and safer. By starting with large cities, establishing clear data standards, and fostering cross-sector collaboration, we can build a scalable model that detects emerging threats before they escalate.

Now is the time for policymakers, law enforcement, and researchers to commit to this vision, ensuring that crime prevention is as dynamic, responsive, and equitable as the challenges we face.