Questions: Infectious Disease Surveillance Systems

Question 1

A city records a tripling of confirmed influenza cases in one week. Before declaring an outbreak, a public health officer should first consider:

• A. Whether hospitals have run out of influenza vaccines
• B. Whether a new, more sensitive diagnostic test was recently deployed in the region
• C. Whether influenza is a notifiable disease in this jurisdiction
• D. Whether all cases share the same neighborhood

Answer: (B)

A spike in surveillance counts can reflect a true increase in disease burden OR an artifact of improved case-finding — a new diagnostic test, expanded reporting requirements, or a media campaign driving more people to seek care. Distinguishing a genuine outbreak from a surveillance artifact requires baseline data and investigation of reporting processes. This is one of the central interpretive challenges in surveillance.

Question 2

Passive surveillance systems are fundamentally inferior to active surveillance and should be replaced by active surveillance whenever resources allow.

• T. True
• F. False

Answer: False

Passive surveillance (mandatory reporting from clinicians and labs) is less sensitive but highly scalable and cost-effective. For high-incidence diseases such as influenza or common STIs, active surveillance of every case would overwhelm public health resources. Active surveillance is most appropriate for high-priority, lower-incidence conditions where completeness matters more than cost — such as novel pathogens or eradication campaigns. The two approaches are complementary, not competing.

Question 3

Why do reported case counts consistently underestimate the true number of infections in a population, and how do epidemiologists attempt to correct for this?

Model answer: Reported counts miss asymptomatic infections, mild cases where people don't seek care, cases that are tested but not reported, and cases in areas with limited healthcare access. Epidemiologists use multiplier methods, seroprevalence surveys (measuring antibody levels in a population sample to estimate prior infection), and capture-recapture techniques to estimate true incidence from observed counts.

Understanding undercounting is essential for correctly interpreting surveillance data. A disease that appears low-burden may simply be poorly detected. Response decisions — vaccination targets, resource allocation — should be based on estimated true burden, not just confirmed case counts.