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ESTIMATING WITHIN-HOUSEHOLD CONTACT NETWORKS FROM EGOCENTRIC DATA
Gail E Potter1, Mark S Handcock, Ira M Longini
1University of Washington and Fred Hutchinson Cancer Research Center.
The Annals of Applied Statistics
|March 20, 2012
Summary
This study models within-household social contacts using survey data, revealing that contact patterns are not random. Findings improve epidemic models and highlight lower-than-expected contact probabilities in some households.
Area of Science:
- Epidemiology
- Network Science
- Mathematical Modeling
Background:
- Acute respiratory diseases spread via social contact networks.
- Current epidemic models rely on unverified assumptions about contact behavior.
- Improved contact network data can enhance disease transmission predictions.
Purpose of the Study:
- To develop a novel model for within-household social contacts.
- To analyze contact patterns using the Belgian POLYMOD dataset.
- To improve the accuracy of epidemic simulation models.
Main Methods:
- Developed a latent variable model for within-household contact behavior.
- Estimated age-specific probabilities of household members being home.
- Calculated age-specific contact probabilities conditional on household members being present.
Main Results:
- Contact behavior within households deviates significantly from random mixing assumptions.
- The probability of all household members contacting each other daily is relatively low.
- Higher contact rates were observed in smaller households (2-3 members).
Conclusions:
- The developed model offers a more realistic representation of within-household social contacts.
- Findings suggest a need to revise assumptions in current epidemic simulation models.
- The study provides insights into factors influencing influenza secondary attack rates in households.
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