Most epidemiological models assume that populations are "weel mixed", which means that all hosts can potentially be in contact with one another. Although this simplifying assumption is acceptable for airborne-transmitted infections in densely populated areas, it can be problematic for when population density is low or for other transmission modes, for example for sexually-transmitted infections. We study how this contact structure between host, which can readily be captured using networks, interacts with the epidemiology and evolution of infectious diseases. Below are some investigations we performed on the topic.
We studied the consequence of adding weights to the contact network, corresponding for instance to the number of sex acts for a sexual contact network. We showed that using biologically-realistic assumptions for the weighting generally lead to a loss of striking properties for epidemics spreading heterogeneous contact networks, which then tend to exhibit properties seen on random networks.
Few network-based models allow for co-infections, that is the simultaneous infection of a host by more than one parasite strain or species. Using a stochastic simulation model, we showed that there is an interaction between the contact network and individual infection histories. Interestingly, these histories, which we analyse as barcodes, can help us make inferences about network properties, about individual node properties (i.e. how 'connected' an individual is), and even about the biological interactions between strains (cross-immunity).
Selinger C, Alizon S (2021) Reconstructing contact network structure and cross-immunity patterns from multiple infection histories. PLoS Comput Biol 17(9):e1009375
Kamp C, Moslonka-Lefebvre M, Alizon S (2013) Epidemic spread on weighted networks. PLoS Comput Biol 9(12):e1003352
For further details, see our publications »