Disease surveillance helps us detect disease cases, understand burden of disease and risk factors, provide the basis for timely and informed decision-making, guide control measures, and monitor impacts. Since the onset of COVID-19, surveillance efforts have worked to provide real-time tracking and forecast data, despite challenges with diagnostic capacity, case reporting, insufficient contact tracing, and fragmented data systems. COVID-19 has highlighted the need to invest in modern data systems, expand and skill up the workforce, and ensure data reporting and interpretation retain high ethical and epidemiological standards.

Themes

• COVID-19 data tracking: Surveillance data provides us essential information about burden and distribution of disease in terms of person, place, and time. Specific COVID-19 tracking metrics include number and proportion of positive tests, vaccinations, hospitalizations, viral reproduction numbers, and deaths, among others.
• Surveillance guidance: Valid and reliable data require consistent definitions, surveillance strategies and reporting. Guidance exists to support the public health workforce in implementing surveillance strategies, expanding surveillance, partnering on site surveillance, and reporting cases as part of a national surveillance system.
• The future of disease surveillance: Needs and challenges of COVID-19 have led to expansions and innovations, including social media- and internet-based surveillance, use of apps for contact tracing and self-reporting, wastewater surveillance, and syndromic surveillance. Future, integrated disease surveillance should reflect core principles of population-based monitoring; scaled laboratory confirmation; digitized data and surveillance systems; standardized case definitions and common data elements; and adequate funding. 

Equity & Systems

Integration of common demographic data elements, like race, ethnicity, age, gender, place of residence, occupation, and income among others allows us to disaggregate data by these important factors in order to better understand health disparities and act to disrupt them. Expanded use of social epidemiology measures, for example social vulnerability, income inequality and other social determinants of health, can elucidate inequities in access to vaccines and other interventions.