Why Disease Surveillance Matters
Disease surveillance plays a crucial role in safeguarding public health by providing timely and accurate information about the prevalence, incidence, spread, and characteristics of various diseases – and their risk factors – over time and across populations. Health authorities can use surveillance systems to detect outbreaks early, formulate effective response strategies, allocate resources efficiently, and track the impact of interventions. Whether dealing with known infectious diseases like influenza, emerging disease threats like SARS CoV-2 (the virus responsible for COVID-19), or environmental and non-communicable public health threats like cardiovascular disease or air pollution, disease surveillance is an essential tool for minimizing morbidity, mortality, and socioeconomic disruptions. It empowers decision-makers with the information needed to make informed choices that protect communities and prevent the escalation of health crises.
Importance of Assessing Disease Surveillance Systems
Assessing the quality of disease surveillance systems is essential to ensure that accurate, actionable data are provided in a timely way. By evaluating the completeness, timeliness, representativeness, and validity of data, stakeholders can identify gaps, biases, and limitations that might compromise a system’s ability to capture the true burden and dynamics of diseases. The assessment process not only enhances the credibility of public health interventions, but also facilitates the strategic allocation of resources, and continuous improvement of surveillance methodologies. Ultimately, rigorous assessment of disease surveillance systems safeguards public health by fostering trust in the information generated and maximizing the potential to prevent, mitigate, and control disease outbreaks.
Overarching Approaches and Components of a Surveillance System
Disease surveillance systems encompass a range of methodologies designed to monitor and track health events, each tailored to specific contexts and purposes. In this toolkit, the term “surveillance system” refers to all disease surveillance activities undertaken in a country or jurisdiction. A surveillance system typically involves several component parts, which can be applied to human conditions, veterinary conditions, or both, using the approaches detailed below.
Because a disease surveillance system may use several of these methodologies in any one location or jurisdiction, the coordination of data flows and public health response protocols are important.
The optimal approach to an assessment will depend on the type(s) of surveillance methodologies that are being used. Common approaches to and components of disease surveillance include:
Surveillance Approaches
- Veterinary surveillance: Disease surveillance is a public health activity which can be applied to both human and veterinary conditions. Here, veterinary surveillance refers to domestic animals; wild animal surveillance is generally a component of environmental public health surveillance.
- Passive surveillance is a disease surveillance system approach where health jurisdictions receive reports submitted from facilities and laboratories in accordance with established regulations. This is a less expensive strategy surveillance. It is frequently used to cover large areas, but often misses cases.
- Active surveillance is a disease surveillance system approach that employs personnel to regularly contact facilities, laboratories, or community members to seek information about health conditions. The resulting data are more accurate than those from passive surveillance, but is more expensive. For veterinary surveillance, active surveillance also refers to mandated screening, for instance prior to animal movement to markets or slaughterhouses.
Components
Syndromic surveillance focuses on early detection by monitoring patterns of signs and symptoms rather than laboratory-confirmed diagnoses, aiding in the rapid identification of emerging health threats. This approach allows for timelier public health response compared to other, more traditional surveillance methods. It is a highly adaptable approach that leverages non-specific data sources. Influenza-like illness monitoring during flu season is an example of syndromic surveillance.
Sentinel surveillance is a targeted and focused approach to monitoring specific diseases or health conditions within a selected subset of the population. Instead of collecting data from the entire population, sentinel surveillance involves gathering information from a representative group of healthcare facilities, regions, or individuals that are deemed to be at high risk for the disease of interest or when resources are too limited to test entire populations. An example of this is described in the Gonococcal Isolate Surveillance Project (GISP), which has monitored antimicrobial resistance (AMR) trends in Neisseria gonorrhoeae since 1986 in select clinics and laboratories in the US.
Indicator-based surveillance relies on predetermined criteria or standardized case definitions to identify and report specific diseases or conditions, offering structured and standardized data for trend analysis and response planning. National reportable disease surveillance is an example of indicator-based surveillance.
Case-based surveillance involves the detailed tracking and analysis of individual cases of diseases. It focuses on gathering comprehensive epidemiological information about each diagnosed case, including demographic data, clinical presentation, laboratory results, treatment information, and other relevant details. This approach allows health authorities to gain a deep understanding of the characteristics and patterns of the disease within the affected population. An example would be the investigation of cases from an outbreak of foodborne illness to determine the cause of an outbreak.
Event-based surveillance targets unusual occurrences or incidents that may signal potential outbreaks, serving as an alert mechanism. Sources may include reports, search engine entries, stories, rumors or other non-standardized or subjective information from social or traditional media, schools, businesses, or other entities in communities. Integrating these diverse approaches enables health authorities to comprehensively monitor public health, detect anomalies promptly, and take informed actions to safeguard populations. One form of event-based surveillance is community-based or participatory surveillance that involves engaging community members to report health information, leveraging local knowledge for enhanced situational awareness.
Environmental public health surveillance generally refers to the systematic and ongoing collection, analysis, interpretation, and dissemination of data related to environmental factors that have the potential to impact public health. In the past this has included surveys of vectors such as mosquitoes, ticks, and rodents, as well as collection of data on chemical and biological contaminants in water such as lead and coliforms. More recently, methods have been developed for surveillance of wastewater and other environmental media (such as air) for pathogens including SARS CoV-2, poliovirus, and AMR genes.
Genomic disease surveillance involves the use of advanced genomic sequencing techniques to analyze the genetic material (DNA or RNA) of pathogens causing diseases to monitor and track their evolution, spread, and characteristics. This approach allows public health authorities to identify specific strains, trace transmission patterns, and detect mutations that could impact the disease’s behavior, transmissibility, and response to treatments or vaccines. Genomic disease surveillance has proven particularly valuable in tracking the spread of infectious diseases, enabling a deeper understanding of outbreaks, epidemics, and pandemics. By analyzing the genomic data of pathogens collected from different geographic locations and over time, scientists can refine diagnostic methods, predict potential changes in disease dynamics, and tailor control strategies for more effective disease management.