Detecting Clustering in Disease Transmission Networks
Author Information
Author(s): David Welch
Primary Institution: Pennsylvania State University
Hypothesis
Can clustering in networks be detected from transmission data in epidemic outbreaks?
Conclusion
Clustering parameters cannot be inferred solely from epidemiological data related to transmission trees.
Supporting Evidence
- The study found that the variation in transmission trees from networks with different clustering levels was minimal.
- Epidemic data showed little to no signal of clustering in the underlying contact network.
Takeaway
The study looked at how diseases spread in networks and found that you can't really tell if the network has clustering just by looking at the disease spread data.
Methodology
The study simulated SEIR epidemics over networks with fixed degree distributions and varying levels of clustering, comparing the resulting transmission trees.
Limitations
The study's findings may not apply to networks with extreme clustering levels or different degree distributions.
Digital Object Identifier (DOI)
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