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Disease contact tracing in random and clustered networks
journal contribution
posted on 2023-06-07, 22:01 authored by Istvan Kiss, Darren M Green, Rowland R KaoThe efficacy of contact tracing, be it between individuals (e.g. sexually transmitted diseases or severe acute respiratory syndrome) or between groups of individuals (e.g. foot-and-mouth disease; FMD), is difficult to evaluate without precise knowledge of the underlying contact structure; i.e. who is connected to whom? Motivated by the 2001 FMD epidemic in the UK, we determine, using stochastic simulations and deterministic 'moment closure' models of disease transmission on networks of premises (nodes), network and disease properties that are important for contact tracing efficiency. For random networks with a high average number of connections per node, little clustering of connections and short latency periods, contact tracing is typically ineffective. In this case, isolation of infected nodes is the dominant factor in determining disease epidemic size and duration. If the latency period is longer and the average number of connections per node small, or if the network is spatially clustered, then the contact tracing performs better and an overall reduction in the proportion of nodes that are removed during an epidemic is observed.
History
Publication status
- Published
Journal
Proceedings B: Biological SciencesISSN
1471-2954Publisher
Royal Society, TheExternal DOI
Issue
1570Volume
272Page range
1407-1414Pages
8.0Department affiliated with
- Mathematics Publications
Full text available
- No
Peer reviewed?
- Yes