The effect of social distancing on the reach of an epidemic in social networks

Gutin, Gregory; Hirano, Toshisuke; Hwang, Sung‐Ha; Neary, Philip R.; Toda, Alexis Akira

doi:10.1007/s11403-021-00322-9

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…For instance, an epidemic can propagate even with a small infection rate if the underlying network is highly heterogeneous [5,6]. Furthermore, network scientists have explored network-based strategies to efficiently suppress epidemics, including optimal vaccine allocation [7,8], rapid isolation of infected individuals [9][10][11], and social distancing [12][13][14][15][16]. Recent studies (since COVID-19) have discussed the effectiveness of mask use in limiting the spread of the virus in networks [17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Impact of assortative mixing by mask-wearing on the propagation of epidemics in networks

Watanabe¹,

Hasegawa²

2021

Preprint

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In this study, we discuss the impacts of assortative mixing by mask-wearing on the effectiveness of mask use in suppressing the propagation of epidemics. We employ the mask model, which is an epidemic model involving mask wearers and non-mask wearers. We derive the occurrence probability and mean size of large outbreaks, epidemic threshold, and average epidemic size for the mask model in an assortatively mixed random network that follows an arbitrary degree distribution. Applying our analysis to the Poisson random networks, we find that the assortative (disassortative) mixing by mask-wearing decreases (increases) the epidemic threshold. In high-transmissibility cases, we establish that mask use is most effective in decreasing the occurrence probability and mean size of large outbreaks, as well as the average epidemic size, when the mixing pattern is strongly assortative. In scale-free networks, mask use is most effective when the mixing pattern is strongly assortative and when it is maximally disassortative, provided that the mask coverage is not low.

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Section: Introductionmentioning

confidence: 99%

Impact of assortative mixing by mask-wearing on the propagation of epidemics in networks

Watanabe¹,

Hasegawa²

2021

Preprint

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“…Please note that reducing infectiousness is only a perfect substitute to reducing social contacts in the standard homogeneous mixing SIR-framework Gutin et al (2021). develop a network-based SIR model and show that the effect of social distancing depends on the network structure of the social interactions.…”

mentioning

confidence: 99%

Endogenous viral mutations, evolutionary selection, and containment policy design

Mellacher

2022

J Econ Interact Coord

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How will the novel coronavirus evolve? I study a simple epidemiological model, in which mutations may change the properties of the virus and its associated disease stochastically and antigenic drifts allow new variants to partially evade immunity. I show analytically that variants with higher infectiousness, longer disease duration, and shorter latent period prove to be fitter. “Smart” containment policies targeting symptomatic individuals may redirect the evolution of the virus, as they give an edge to variants with a longer incubation period and a higher share of asymptomatic infections. Reduced mortality, on the other hand, does not per se prove to be an evolutionary advantage. I then implement this model as an agent-based simulation model in order to explore its aggregate dynamics. Monte Carlo simulations show that a) containment policy design has an impact on both speed and direction of viral evolution, b) the virus may circulate in the population indefinitely, provided that containment efforts are too relaxed and the propensity of the virus to escape immunity is high enough, and crucially c) that it may not be possible to distinguish between a slowly and a rapidly evolving virus by looking only at short-term epidemiological outcomes. Thus, what looks like a successful mitigation strategy in the short run, may prove to have devastating long-run effects. These results suggest that optimal containment policy must take the propensity of the virus to mutate and escape immunity into account, strengthening the case for genetic and antigenic surveillance even in the early stages of an epidemic.

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