Dynamics of social interactions, in the flow of information and disease spreading in social insects colonies: Effects of environmental events and spatial heterogeneity

Abstract

The relationship between division of labor and individuals' spatial behavior in social insect colonies provides a useful context to study how social interactions influence the spreading of agent (which could be information or virus) across distributed agent systems. In social insect colonies, spatial heterogeneity associated with variations of individual task roles, affects social contacts, and thus the way in which agent moves through social contact networks. We used an Agent Based Model (ABM) to mimic three realistic scenarios of agent spreading in social insect colonies. Our model suggests that individuals within a specific task interact more with consequences that agent could potentially spread rapidly within that group, while agent spreads slower between task groups. Our simulations show a strong linear relationship between the degree of spatial heterogeneity and social contact rates, and that the spreading dynamics of agents follow a modified nonlinear logistic growth model with varied transmission rates for different scenarios. Our work provides an important insights on the dual-functionality of physical contacts. This dual-functionality is often driven via variations of individual spatial behavior, and can have both inhibiting and facilitating effects on agent transmission rates depending on environment. The results from our proposed model not only provide important insights on mechanisms that generate spatial heterogeneity, but also deepen our understanding of how social insect colonies balance the benefit and cost of physical contacts on the agents' transmission under varied environmental conditions. Network models of social insect colonies via local interactions have focused primarily for the spread of three main classes of agents: information, food, and pathogens. In the context of information spreading, colonies should theoretically be organized in a way that allows individuals to transmit relevant information as quickly and accurately as possible [16]. On the other hand, the rapid development of network contacts is problematic to the control and regulation of pathogen spread through contagious interactions [48,23]. Social insects colonies rely on social interactions to balance the need for distribution of useful sources efficiently and the demand to minimize the threat of pathogen spreading by contagious infection through interactions. Kappeler et al. [27] show that the division of a network into subgroups with higher connectivity can inhibit the initial spreading of contagion through social networks, while may rapidly increase spreading within network subgroups or clusters. Task fidelity, shown as a stable and individual pattern of spatial occupancy age-induced, could contribute to this network structure [32]. Thus, it is important to understand the connection between individual interactions in relation to work demand, and their influences on the spreading of other information (or pathogens) through the entire colony.Workers of social insect colonies differentially distribute themselves across col...

Sociality and parasite transmission

“…In particular, scrutinizing the generalized transmission distance suggests that within-group transmission is the most important selective episode for the evolution of social hosts and their parasites. These effects can be modelled (Fefferman et al 2007 ; Hock and Fefferman 2012 ; Sah et al 2018 ; Guo et al 2020 ), and sensitivity analysis (e.g. sensu Frank and Schmid-Hempel 2008 ) will provide further guidelines as to which elements of the generalized distance are most critical for either party.…”

How territoriality reduces disease transmission among social insect colonies

“…While there has been a large body of work examining adaptations to reduce the spread of parasites and pathogens within colonies (Naug and Camazine 2002 ; Fefferman et al 2007 ; Otterstatter and Thomson 2007 ; Buechel and Schmid-Hempel 2016 ; Stroeymeyt et al 2018 ; Cremer et al 2018 ; Udiani and Fefferman 2020 ), equally important are strategies to prevent the introduction of pathogens into the colony in the first place. Foragers can become infected outside the colony from the external environment (Durrer and Schmid-Hempel 1994 ; Andersen et al 2009 ) or from contact with infected nestmates, conspecifics from other colonies, or heterospecifics (Mirabito and Rosengaus 2016 ; Guo et al 2020 ). Infections can also be introduced by the accidental drift of infected individuals from nearby colonies (Oi and Williams 2003 ; Goodwin et al 2006 ; Oi 2006 ).…”

Threshold Dynamics of a Diffusive Herpes Model Incorporating Fixed Relapse Period in a Spatial Heterogeneous Environment

“…Besides, another method of calculating R 0 in one-dimensional space was also presented in [9]. In a recent work [14], the authors studied the dual-functionality of physical contacts driven via variations of individual spatial behavior and provided insights on mechanisms that generate spatial heterogeneity. By using an epidemic model with nonlocal delay and logistic growth, the authors in [15] studied the dynamics of model and investigated how nonlocal delay and logistic growth affect the disease transmission.…”

“…We arrange the rest of this paper as follows. Section 2 is devoted to the well-posedness of system (14). We follow the standard procedures in [25] to define R 0 for ( 14) by the next generation operator approach in Section 3.…”

“…Theorem 3. For each u 0 � ϕ ∈ C + , denote by u(t, x, ϕ) the solution of (14). If R 0 > 1 and ϕ i (0, •) ≡ 0 for i � 2, 3, then there is sufficiently small η > 0 that…”