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Human mobility networks and persistence of rapidly mutating pathogens

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ABSTRACT

Rapidly mutating pathogens may be able to persist in the population and reach an endemic equilibrium by escaping hosts’ acquired immunity. For such diseases, multiple biological, environmental and population-level mechanisms determine the dynamics of the outbreak, including pathogen's epidemiological traits (e.g. transmissibility, infectious period and duration of immunity), seasonality, interaction with other circulating strains and hosts’ mixing and spatial fragmentation. Here, we study a susceptible-infected-recovered-susceptible model on a metapopulation where individuals are distributed in sub-populations connected via a network of mobility flows. Through extensive numerical simulations, we explore the phase space of pathogen's persistence and map the dynamical regimes of the pathogen following emergence. Our results show that spatial fragmentation and mobility play a key role in the persistence of the disease whose maximum is reached at intermediate mobility values. We describe the occurrence of different phenomena including local extinction and emergence of epidemic waves, and assess the conditions for large-scale spreading. Findings are highlighted in reference to previous studies and to real scenarios. Our work uncovers the crucial role of hosts’ mobility on the ecological dynamics of rapidly mutating pathogens, opening the path for further studies on disease ecology in the presence of a complex and heterogeneous environment.

No MeSH data available.


Related in: MedlinePlus

Spatial dynamics. The external panels show the time evolution of the fraction of infected sub-populations D(t)/V for different values of the duration of immunity L and travelling probability p. The central panel shows the different regions where each value of L and p has been chosen. In each panel, curves corresponding to 102 runs with different initial conditions are shown. To facilitate visualization, 90% of them are smoothed.
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RSOS160914F4: Spatial dynamics. The external panels show the time evolution of the fraction of infected sub-populations D(t)/V for different values of the duration of immunity L and travelling probability p. The central panel shows the different regions where each value of L and p has been chosen. In each panel, curves corresponding to 102 runs with different initial conditions are shown. To facilitate visualization, 90% of them are smoothed.

Mentions: In this section, we go more in depth into the understanding of the spatial dynamics following the emergence of a pathogen in the fully susceptible and spatially structured population. Starting from the global persistence diagram reported in figure 2, we characterize the epidemic diffusion in space considering a single value of reference for p in each of the three mobility regimes (p=3×10−5 in the low, p=6×10−4 in the intermediate, and p=10−2 in the high mobility regime), associated with different values of the immunity period L (figure 4).Figure 4.


Human mobility networks and persistence of rapidly mutating pathogens
Spatial dynamics. The external panels show the time evolution of the fraction of infected sub-populations D(t)/V for different values of the duration of immunity L and travelling probability p. The central panel shows the different regions where each value of L and p has been chosen. In each panel, curves corresponding to 102 runs with different initial conditions are shown. To facilitate visualization, 90% of them are smoothed.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383836&req=5

RSOS160914F4: Spatial dynamics. The external panels show the time evolution of the fraction of infected sub-populations D(t)/V for different values of the duration of immunity L and travelling probability p. The central panel shows the different regions where each value of L and p has been chosen. In each panel, curves corresponding to 102 runs with different initial conditions are shown. To facilitate visualization, 90% of them are smoothed.
Mentions: In this section, we go more in depth into the understanding of the spatial dynamics following the emergence of a pathogen in the fully susceptible and spatially structured population. Starting from the global persistence diagram reported in figure 2, we characterize the epidemic diffusion in space considering a single value of reference for p in each of the three mobility regimes (p=3×10−5 in the low, p=6×10−4 in the intermediate, and p=10−2 in the high mobility regime), associated with different values of the immunity period L (figure 4).Figure 4.

View Article: PubMed Central - PubMed

ABSTRACT

Rapidly mutating pathogens may be able to persist in the population and reach an endemic equilibrium by escaping hosts’ acquired immunity. For such diseases, multiple biological, environmental and population-level mechanisms determine the dynamics of the outbreak, including pathogen's epidemiological traits (e.g. transmissibility, infectious period and duration of immunity), seasonality, interaction with other circulating strains and hosts’ mixing and spatial fragmentation. Here, we study a susceptible-infected-recovered-susceptible model on a metapopulation where individuals are distributed in sub-populations connected via a network of mobility flows. Through extensive numerical simulations, we explore the phase space of pathogen's persistence and map the dynamical regimes of the pathogen following emergence. Our results show that spatial fragmentation and mobility play a key role in the persistence of the disease whose maximum is reached at intermediate mobility values. We describe the occurrence of different phenomena including local extinction and emergence of epidemic waves, and assess the conditions for large-scale spreading. Findings are highlighted in reference to previous studies and to real scenarios. Our work uncovers the crucial role of hosts’ mobility on the ecological dynamics of rapidly mutating pathogens, opening the path for further studies on disease ecology in the presence of a complex and heterogeneous environment.

No MeSH data available.


Related in: MedlinePlus