Mortality Data Integrated into Syndromic Surveillance System

Collaborative Project Routes Mortality Data Through STEVE


  • For years, public health practitioners have analyzed syndromic data with other data sources—such as medication sales and poison control data—to better understand how health events affect people in their communities.
  • CDC's National Syndromic Surveillance Program (NSSP) has integrated some of these data sources into its syndromic surveillance system.
  • Incorporating mortality data has provided early insight into unexpected rises in causes of death or rare causes of death, potentially benefitting policymakers and public health practitioners.
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CDC is working harder than ever to modernize its surveillance systems1 and provide fast access to better data. A good example of modernization in action is the data integration that CDC's NSSP is doing in collaboration with state, city, and county health departments.

For years, public health practitioners have analyzed syndromic data with other data sources to better understand how health events affect people in their communities. Such data sources have included medication sales, poison control data, absenteeism, and laboratory tests and results. In response to the needs of its user base, NSSP has integrated some of these data sources into its syndromic surveillance system for use in daily surveillance and emergency response.

Integrating vital statistics data

In 2021, the NSSP and the Council of State and Territorial Epidemiologists (CSTE) began working with the National Association for Public Health Statistics and Information Systems (NAPHSIS) to integrate mortality data into the NSSP2 from STEVE.3 NAPHSIS designed STEVE as a public health service to facilitate secure exchange of vital statistics data. STEVE can route data securely, quickly, and without manual intervention from health department vital records systems to the National Vital Statistics System and to partnering systems such as NSSP.

Incorporating STEVE's mortality data into NSSP has the potential to benefit numerous end users—from policymakers to public health practitioners (state analysts, statisticians, and epidemiologists). Once mortality data are routed to the NSSP and combined with syndromic data, practitioners can use NSSP's analytic capabilities2 to see the underlying and contributing cause-of-death data.4 These data provide early insight into unexpected rises in causes of death or rare causes of death.4 Practitioners can also use mortality data to validate data routinely collected by syndromic surveillance.

Pilot projects to expand the collaboration

Analysts with NSSP and NAPHSIS expanded their collaboration by setting up pilot projects to transmit STEVE's mortality data from a subset of state public health departments to NSSP.45 In NSSP, the death data are integrated with emergency department data. Feedback from these pilot projects will be used to help all NSSP participants. NSSP is also working with the health departments in the pilot project to evaluate the cost, effort, and data management requirements of adding mortality data to NSSP's array of data sources.

Public health practitioners, health care service providers, and the public need accurate, timely, and more complete information. CDC's NSSP is working to detect threats faster by securely integrating data from multiple sources and by streamlining data exchange. The integration of mortality data with syndromic data adds to public health's understanding of health events and provides essential checks and balances, confirming (or disproving) what we think we know, and all within one integrated syndromic surveillance system.

Note: As a general practice, the NSSP ensures that electronic health information complies with standards for transferring, securing, and sharing data between health care and public health partners and that data-sharing agreements, where needed, are in place. The NSSP is responsive to its user base (state and local health departments), other federal agencies, and health care partners. NSSP works closely with them to integrate and test data sources before making these data and operational processes widely available to NSSP participants.

How public health practitioners use syndromic data

NSSP makes the tools and processes for conducting syndromic surveillance accessible to state and local health departments nationwide, and at no cost.

For those unfamiliar with syndromic surveillance, this type of surveillance looks at groupings of symptoms, called "syndromes," that are indicators of potential health threats. These data are collected when patients seek care in hospital emergency departments, urgent care centers, and other facilities—both before and after a diagnosis is confirmed—all in near real-time.

Syndromic data have served as an early warning system for flu outbreaks. These data have also been used in responses for opioid overdoses, Zika virus infection, e-cigarette or vaping product use-associated lung injury, and COVID-19.

  1. CDC. Data Modernization Implementation Support: Improving Surveillance Systems [Internet]. Atlanta (GA): CDC Center for Surveillance, Epidemiology, and Laboratory Services; 12 Oct 2021 [cited 2022 Feb 8]. Available from:
  2. CDC. National Syndromic Surveillance Program (NSSP): What is Syndromic Surveillance? [Internet]. Atlanta (GA): CDC, Division of Health Informatics and Surveillance; 2021 Sep 24 [cited 2022 Feb 8]. Available from:
  3. NAPHSIS. State and Territorial Exchange of Vital Events (STEVE) [Internet]. [cited 2022 Feb 8]. Available from:
  4. CSTE/CDC+ NAPHSIS: Mortality Project Final Webinar (
  5. This collaborative pilot project routes death data through STEVE to NSSP–ESSENCE. ESSENCE (Electronic Surveillance System for the Early Notification of Community-based Epidemics) is the National Syndromic Surveillance Program's secure, web-based tool to operationalize the public health surveillance workflow. ESSENCE allows analysts, epidemiologists, and others across all levels of public health to collaborate, investigate changes in trends, and to analyze, visualize and share data.