écologie des virus influenza aviaires en Camargue - IRD

Influenza aviaires en Camargueand c = 0 (for more details on c, see online appendix).To identify the role of each transmission route in the observed dynamics, and henceto see if one single transmission route may reproduce the dynamical signature observed inour data, we computed a cross­correlation factor between AIV dynamics and bird populationdynamics. Results highlight that, for our recorded AIV dynamics, a significant crosscorrelationfactor was present and corresponded to a lag of zero (Figure 2A). This means thatAIV dynamics are synchronous with host community dynamics (without any delay). Bothtypes of inter­individual transmission considered in isolation (Figure 2B and 2C) leads to theloss of synchrony between AIV dynamics and host community dynamics, suggesting thatthese transmission routes, in isolation, cannot lead to the dynamical signature recorded in ourstudy site. Figure 2D shows the dynamical signature for a water­borne transmission model. Itis different from those obtained for the inter­individual transmission patterns as maximalcross­correlation is centered on lag of zero. This means that the host community dynamicsdrive the disease transmission (by viral particle production in water and by a high number ofsusceptible individuals) and the environment constitutes a persistent source of infectionthrough time. Thus, each new susceptible bird (either a juvenile or a migrant) may rapidlybecome infectious. This process results in a maximal cross­correlation with no delay betweenhost bird community and disease dynamics.According to these results, the dynamical signature of our disease data seems to becompatible only with a water­borne transmission pattern. This underlines the important roleof water­borne transmission in the processes which drive the dynamics of infection,involving both density­dependent and water­borne transmission components.We then investigated the implications of each transmission route in the model which69