During an outbreak, formulating a clear definition for what will be considered a 'case' is crucial to confirm the diagnosis of new reported cases, including searching for additional cases. It is not as straightforward as it may initially seem, and multiple factors might complicate identifying newly infected cases, including the following:.

• The large spectrum of different and possible symptoms for individuals having the same disease.
• The potential similarities between symptoms of the outbreak disease and those of other endemic diseases.
• The outbreak context and the feasibility of conducting diagnostic tests to confirm the presence of an infectious agent.

Epidemiologists therefore take a structured approach to defining cases, and may allow for a few different definitions within the same outbreak. Different definitions may be in operation during routine surveillance, compared to during an outbreak when community-based diagnosis by mobile health teams may be required. These definitions may include:

• Suspected case – for example on the basis of common symptoms.

• Probable case – for example, a case that meets clinical criteria and is a contact of a probable or confirmed case.

• Confirmed case – this is usually a diagnosis confirmed by laboratory tests (‘laboratory-confirmed case’) which may involve sending a sample to a laboratory if facilities are not available on-site. However, a ‘clinically confirmed case’ definition is also used occasionally, based on clinical manifestations but with a stricter definition than a possible case.

The broader case definition that allows diagnosing all or most disease cases is known as the most 'sensitive' case definition. However, in trying to capture as many cases as possible, we may risk falsely diagnosing some individuals with the disease (e.g., if they are experiencing a few symptoms common to both the disease of interest and another disease).

The case definition is a tradeoff between a more sensitive definition and a more 'specific' definition. A more 'specific' definition excludes better the individuals who do not have the disease ('false positives'), but may at the same time miss a more significant proportion of individuals who are indeed infected.