SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.

Math Biosci

INRA, UR 341 Mathématiques et Informatique Appliquées, 78350 Jouy-en-Josas, France.

Published: March 2012

AI Article Synopsis

  • The paper explores a new model (SIS(c)) for understanding disease spread in networks, especially in situations where infection status isn't just binary (sick or healthy).
  • It derives key relationships analytically, such as the epidemic threshold based on two important factors: infection persistence and transmission probability.
  • The study not only introduces an algorithm for calculating these thresholds but also suggests control strategies targeting specific market categories in the horticultural trade, with broader implications for other networks like food trade and idea dissemination.

Article Abstract

Network theory has been applied to many aspects of biosciences, including epidemiology. Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.g. the spread of Phytophthora ramorum in plant trade networks), a continuum in the infection status of nodes can better capture the reality of epidemics in networks. In this paper, a Susceptible-Infected-Susceptible model along a continuum in the infection status (SIS(c)) is presented, using as a case study directed networks and two parameters governing the epidemic process (probability of infection persistence (p(p)) and of infection transmission (p(t)). The previously empirically reported linear epidemic threshold in a plot of p(p) as a function of p(t) (Pautasso and Jeger, 2008) is derived analytically. Also the previously observed negative correlation between the epidemic threshold and the correlation between links in and out of nodes (Moslonka-Lefebvre et al., 2009) is justified analytically. A simple algorithm to calculate the threshold conditions is introduced. Additionally, a control strategy based on targeting market hierarchical categories such as producers, wholesalers and retailers is presented and applied to a realistic reconstruction of the UK horticultural trade network. Finally, various applications (e.g., seed exchange networks, food trade, spread of ideas) and potential refinements of the SIS(c) model are discussed.

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Source
http://dx.doi.org/10.1016/j.mbs.2012.01.004DOI Listing

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