In the last decade, national, state, and local public health surveillance and data systems began a major shift toward modernization. COVID-19 reminds us why this shift has been and remains a priority.
Public health surveillance is critical to providing the intelligence needed to safeguard the public's health. While the scientific principles of epidemiology that drive surveillance remain constant, surveillance methods, practices, systems, and infrastructure must continuously evolve to address these increasingly complex threats. As our nation tackles the COVID-19 pandemic, policy makers across the country are using surveillance data to make decisions that have profound effects on the public's health, as well as the economy of the country. At the same time, an unprecedented number of citizens are using that same data, every day, to understand what is happening around them and to make decisions about how to protect their loved one's health.
Early elements of US public health surveillance can be traced to Rhode Island in the 1740s, where colonial law required tavern owners to report contagious diseases among patrons, including specific reporting requirements for smallpox, yellow fever, and cholera.1 Although the data and methods available to health officials today far surpass what was available to their 18th-century counterparts, our nation's surveillance system infrastructure is still plagued by long-standing, obstinate challenges. Fortunately, in recent years, local, state, and federal agencies have partnered with the broader public health community to develop approaches to address these challenges. The COVID-19 pandemic has underscored the importance of these efforts, highlighting the need for accelerated action and increased investments in this space.
Building a 21st-Century Public Health Surveillance System
In the last decade, recognizing the need for dedicated efforts to build a core public health data infrastructure, national public health organizations began collective work to improve data systems and support the secure and efficient flow of data across jurisdictions and levels of government. Led by the Council of State and Territorial Epidemiologists, public health partners developed and released the Driving Public Health in the Fast Lane report, which outlines a series of clear recommendations for a modern, innovative infrastructure.2 It is an essential component to the long-term success of our nation's surveillance infrastructure, along with Centers for Disease Control and Prevention's (CDC's) Roadmap for Data Modernization, which focuses on transforming its data, technology, and workforce capabilities.3
To further modernize plans, the Association of State and Territorial Health Officials convened a group of state and territorial health agency leaders in January 2020 to advise on challenges and opportunities facing health jurisdictions. The core elements set forth by these reports and convenings delineate some of the critical work still ahead of us in a COVID-19 and post-COVID-19 world and include the need for the following:
- Coordinated policies, consensus-based standards, and decision making across states, CDC, and federal partners to develop interoperable systems that allow for efficient data exchange.
- Enterprise-level information technology and data infrastructure that supports cloud-based platforms and real-time data automation.
- A system-wide environment of innovation that enables new public-private partnerships with health care providers, technology companies, and other entities to create new tools that empower communities, patients, and consumers.
Significant, sustained resources are required to translate these recommendations into action. In fiscal year 2020, a federal spending bill dedicated $50 million in funding for the CDC's efforts to modernize public health data systems. Hopefully, this represents the beginning of the $1 billion proposed appropriation the CDC will require over the next 10 years to accomplish this critical mission.
COVID-19 Reinforces the Need for Data Modernization
A national strategy founded on local, state, and territorial data modernization has never been more crucial than in the face of the COVID-19 pandemic. Complete surveillance data, analysis, and seamless data exchange are vital to improving public health's ability to more accurately gauge and respond to health threats, especially among vulnerable or underserved communities. Elected officials and policy makers need these same data to inform health policy frameworks and remain informed about societal consequences of the pandemic and the response to it.
Complete data elements
Incomplete data and resulting difficulties have been underscored and made more apparent during the pandemic. Incomplete reporting of critical elements, such as race and ethnicity, symptom status, and health outcomes, challenges our ability to characterize epidemiologic trends and resource demands at the national level.4 Completeness of data reported into public health systems is often reliant on information submitted by providers. Ideally, increased investment and policy changes will support development of comprehensive electronic data exchange between public health and health care organizations. These systems could then be much more rapidly modified when new reporting requirements arise.
Granular analyses of data are required to improve decision making and focused community interventions. Easy access and contextualized display of real-time information increase transparency and can assist the public in making data-driven choices about their daily interactions and habits. While public health personnel are stretched thin during the pandemic response, collaborations with academic partners may provide much-needed capacity to support epidemiologic analyses and translation of data into action.5 Such public health and academic partnerships should be strengthened.
Secure and timely data exchange between public health, laboratories, and health care providers is critical for the detection of and response to evolving disease patterns. Expert recommendations6 have urged public health departments to leverage increased federal flexibilities governing information exchange during the COVID-19 emergency,7 assert public health legal authorities, and define a clear minimum data set when initiating data exchange efforts. With regard to cross-jurisdictional data exchange, protocols from HIV/AIDS and STI programs may serve as models for the secure and ethical sharing of information for cross-border case investigations.
In the Near Future
While CARES Act investments are notable, they are not sufficient to modernize public health data systems in a comprehensive manner. Congress rightly funded states to enhance and update their epidemiology and laboratory capacity for the COVID-19 response, but to achieve a cohesive core public health data system, specific and sustained funding will remain paramount.
Over the coming years, the governmental public health community must continue pushing for innovative partnerships with the private sector, including in new ways that combine governmental public health and private sector expertise to build a safe, secure environment to test new ideas. For instance, while we still have much to learn about smartphone COVID-19 exposure notification apps built for the joint Apple/Google application interface, it is clear such partnerships can yield significant benefit and potentially lead to huge advancements for the nation's health.
It is equally clear that, like any good investment for long-term benefit, public health data modernization will require an initial down payment when we emerge from our current COVID-19 crisis, and sustained funding thereafter.
1. Thacker SB, Qualters JR, Lee LM. Public health surveillance in the United States: evolution and challenges. MMWR Morb Mortal Wkly Rep. 2012;61(3):3–9. https://www.cdc.gov/mmwr/preview/mmwrhtml/su6103a2.htm
. Accessed August 13, 2020.
2. Council of State and Territorial Epidemiologists. Driving public health in the fast lane. The urgent need for a 21st century data superhighway. https://cdn.ymaws.com/www.cste.org/resource/resmgr/pdfs/pdfs2/Driving_PH_Display.pdf
. Accessed August 11, 2020.
3. Centers for Disease Control and Prevention. Data Modernization Initiative. https://www.cdc.gov/surveillance/surveillance-data-strategies/data-IT-transformation.html
. Accessed August 11, 2020.
4. CIDRAP. COVID-19: the CIDRAP viewpoint, part 5. https://www.cidrap.umn.edu/sites/default/files/public/downloads/cidrap-covid19-viewpoint-part5.pdf
. Published July 9, 2020. Accessed August 13, 2020.
5. Rivers CM, Dean NE. Covid-19 in the US: we're not getting full value from our data. https://blogs.bmj.com/bmj/2020/07/06/covid-19-in-the-us-were-not-getting-full-value-from-our-data
. Published July 6, 2020. Accessed August 13, 2020.
6. McClellan M, Mostashari F. Data interoperability and exchange to support COVID-19 containment. https://healthpolicy.duke.edu/sites/default/files/2020-06/data_interoperability_and_exchange_to_support_covid-19_containment_final.pdf
. Published May 1, 2020. Accessed August 13, 2020.
7. HHS.gov. OCR announces notification of enforcement discretion to allow uses and disclosures of protected health information by business associates for public health and health oversight activities during the COVID-19 nationwide public health emergency. https://www.hhs.gov/about/news/2020/04/02/ocr-announces-notification-of-enforcement-discretion.html
. Published April 2, 2020. Accessed August 13, 2020.