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Human mobility networks and persistence of rapidly mutating pathogens

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

Schematic representation of the stochastic metapopulation model. Panel (a) represents the disease dynamics that follows a SIRS scheme, where individuals change states with given transition probabilities (Susceptible (S), Infected (I), Recovered (R) and back to S when the acquired immunity is lost). Panel (b) illustrates the structure of the metapopulation network, which consists of sub-populations that are connected by individuals travelling from one to another through a mobility network.
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RSOS160914F1: Schematic representation of the stochastic metapopulation model. Panel (a) represents the disease dynamics that follows a SIRS scheme, where individuals change states with given transition probabilities (Susceptible (S), Infected (I), Recovered (R) and back to S when the acquired immunity is lost). Panel (b) illustrates the structure of the metapopulation network, which consists of sub-populations that are connected by individuals travelling from one to another through a mobility network.

Mentions: We use a stochastic individual-based metapopulation model [32–34], where mobility and infection of individuals are explicitly accounted for as discrete-time processes. Individuals mix homogeneously within the local communities (also called sub-populations, patches or nodes of the metapopulation system), whereas at the global level the coupling between these sub-populations is introduced by individuals that travel along mobility connections (figure 1). The model is thus represented in terms of a network of links, i.e. mobility flows, connecting different nodes representing local populations.Figure 1.


Human mobility networks and persistence of rapidly mutating pathogens
Schematic representation of the stochastic metapopulation model. Panel (a) represents the disease dynamics that follows a SIRS scheme, where individuals change states with given transition probabilities (Susceptible (S), Infected (I), Recovered (R) and back to S when the acquired immunity is lost). Panel (b) illustrates the structure of the metapopulation network, which consists of sub-populations that are connected by individuals travelling from one to another through a mobility network.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

RSOS160914F1: Schematic representation of the stochastic metapopulation model. Panel (a) represents the disease dynamics that follows a SIRS scheme, where individuals change states with given transition probabilities (Susceptible (S), Infected (I), Recovered (R) and back to S when the acquired immunity is lost). Panel (b) illustrates the structure of the metapopulation network, which consists of sub-populations that are connected by individuals travelling from one to another through a mobility network.
Mentions: We use a stochastic individual-based metapopulation model [32–34], where mobility and infection of individuals are explicitly accounted for as discrete-time processes. Individuals mix homogeneously within the local communities (also called sub-populations, patches or nodes of the metapopulation system), whereas at the global level the coupling between these sub-populations is introduced by individuals that travel along mobility connections (figure 1). The model is thus represented in terms of a network of links, i.e. mobility flows, connecting different nodes representing local populations.Figure 1.

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