Define event-driven (event-based) surveillance and give an example.

Define event-driven (event-based) surveillance and give an example.

• A. Event-based surveillance relies on scheduled national surveys of the population.
• B. Event-based surveillance uses routine data from hospitals only.
• C. Event-based surveillance uses reports of unusual health events from media, hotlines, or community sources to identify signals; e.g., reports of clusters of fever in clinics.
• D. Event-based surveillance uses only laboratory data for signals.

Answer: (C)

Event-driven surveillance is a rapid, flexible way to detect potential health threats by collecting and analyzing reports of unusual health events from non-traditional sources, such as media stories, hotlines, community networks, or other informal channels, and then validating and investigating those signals. This approach aims to pick up signals early, before formal, routine data fully capture an outbreak. A classic example is when reports emerge about clusters of fever in clinics; health authorities would investigate to determine whether there is an outbreak and what response is needed. This method is distinct from systems that rely solely on scheduled surveys, routine hospital data, or only laboratory data, which may miss early, non-laboratory signals or delay detection.

Event-driven surveillance is a rapid, flexible way to detect potential health threats by collecting and analyzing reports of unusual health events from non-traditional sources, such as media stories, hotlines, community networks, or other informal channels, and then validating and investigating those signals. This approach aims to pick up signals early, before formal, routine data fully capture an outbreak. A classic example is when reports emerge about clusters of fever in clinics; health authorities would investigate to determine whether there is an outbreak and what response is needed. This method is distinct from systems that rely solely on scheduled surveys, routine hospital data, or only laboratory data, which may miss early, non-laboratory signals or delay detection.