The case for real-time public health surveillance
Public health surveillance is not a new concept. But with the COVID-19 pandemic, there is new need for a deeper understanding—and modernization into real-time surveillance to enhance public health action.
The terms “endemic” and “epidemic” were first defined by Hippocrates around 400 B.C. to distinguish between diseases. With the implementation of new technologies, public health surveillance has the goal of “systematic collection, analysis, and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice” according to the World Health Organization.
Day-to-day public health surveillance is used for early detection, impact assessment, intervention and implementation, evaluation, and risk assessment that all lead to public health actions. A few of the many applications for public health surveillance include chronic diseases such as cancer and diabetes, infectious diseases such as flu and vector-borne diseases, as well as environmental health and injury control.
Timely detection of health signals
Public health surveillance heavily relies on public health information systems to ensure data standardization and integration. Any delay in responding to disease outbreaks constitutes a very serious threat to global public health. This is why real-time surveillance and enhanced communication between health care facilities and all levels of the public health system is crucial to ensure action.
For example, ICF implements the Demographic and Health Surveys (DHS) Program for USAID, providing technical assistance on more than 300 surveys in at least 90 countries. We manage a wide range of data, from infectious diseases (such as malaria and HIV) to nutrition and fertility.
However, survey data is not the same as real-time surveillance. It takes time to collect the information, analyze the data, and publish.
Working with CDC since 2014, ICF has been continually evolving CDC’s BioSense platform with the goal of strengthening CDC's public health surveillance system. BioSense collects mostly emergency department data and some urgent care data—from chief complaint diagnostics to discharge diagnostics—with the goal of rapidly collecting, evaluating, and sharing syndromic surveillance data to understand and monitor health events. The syndromic data is received within 24 to 48 hours of collection, which makes it a near real-time surveillance system for detecting outbreaks.
BioSense is constantly evolving. It played a large role in the COVID-19 pandemic: not only in finding hotspots of infections but also in vaccine and treatment data, adverse effects of ivermectin, and indirect effects of COVID-19 on mental health. While the BioSense team is working on adding more capabilities, there are some challenges based on the data itself but also where the data comes from. Every site is different, therefore data will look different based on who enters the syndrome into the system. Teams of data scientists, subject matter experts in specific diseases, and other partners must work together to ensure data standardization.
Modernizing the immunization data infrastructure
While the pandemic showcased the need for consolidation of immunization data, there were several challenges in the capacity of public health information systems to engulf large amounts of COVID-19 data along with the vaccination efforts. One solution was to secure real-time data between different entities. The Immunization (IZ) Gateway is a secure cloud-based platform that was built as a central point of connection for entities wishing to query or update immunization data to/from any number of state immunization information systems.
The IZ Gateway establishes a national immunization registry and enables research and analysis for national situational awareness, effectiveness, adverse effects, and rates of vaccination. Currently used by the CDC for COVID-19 reporting, the IZ Gateway offers a simple, standardized, secure, and scalable solution to exchanging data between different systems. While mostly being used for immunization data, the same platform can be adapted for any data exchange to enhance real-time surveillance for health systems.
Social media is also being used to detect potential outbreaks. NYC Department of Health and Mental Hygiene partnered with Columbia University to develop a data mining software to search for restaurant reviews posted on Yelp. If anyone reported a few people getting sick within at least 10 hours after eating at the restaurant, a positive signal alerted the team who could then launch an investigation. Twitter has also been used by some health departments during flu season to let campus students know where to get vaccinated. However, there are some limitations to using social media data for public health surveillance, including a limited reach of users and issues around sharing protected information.
Data-informed decisions regarding outbreaks and patient care
It is essential for researchers, epidemiologists, and policymakers to have access to timely data. Real-time surveillance enables rapid and standardized data sharing to understand how diseases spread, strengthen disease surveillance, and track the overdose crisis and syndromic data.
To continue fighting for better public health systems, we need to ensure interoperability across multiple systems. We also must keep modernizing health IT systems and integrating different workflows at all levels of public health, from clinicians to federal agencies. Continuing to provide and enhance real-time, accurate, epidemiologic and laboratory data will lead to the best public health actions.
