Estimating influenza transmission parameters: Comparing two study designs, 2023-2024.

Area of Science:

• Epidemiology
• Infectious Disease Dynamics
• Public Health Surveillance

Background:

• Household studies are vital for understanding influenza transmission.
• Accurate transmission parameters are essential for modeling epidemics and pandemics.
• Effective influenza control strategies rely on robust data.

Purpose of the Study:

• To compare two methods for estimating household influenza transmission parameters.
• To evaluate index case interviews versus systematic daily follow-up.
• To assess the impact of study design on detecting influenza infections and illness.

Main Methods:

• Comparison of data from index case interviews (n=1537) and systematic daily follow-up (n=857) during the 2023-2024 US influenza season.
• Assessment of symptomatic illness, influenza-like illness (ILI), and laboratory-confirmed influenza virus infection.
• Analysis of serial illness onset intervals between household contacts.

Main Results:

• Systematic daily follow-up detected symptomatic illness in 59% of contacts versus 40% by interview.
• Laboratory-confirmed influenza was identified in 44% of contacts via daily follow-up compared to 12% by interview.
• Both methods yielded a median serial interval of 4 days.
• Influenza-like illness detection was comparable (26% vs. 20%).

Conclusions:

• Index case interviews are resource-efficient but significantly underestimate laboratory-confirmed influenza cases.
• Systematic daily follow-up with laboratory testing provides more accurate transmission data.
• Study design, particularly the inclusion of systematic testing, is critical for capturing influenza transmission dynamics accurately.
• Accurate data are essential for informing effective public health responses to influenza.