{
  "id": "cond-mat/0301322",
  "version": "v2",
  "published": "2003-01-17T15:28:18.000Z",
  "updated": "2003-03-18T10:13:37.000Z",
  "title": "Distribution of infected mass in disease spreading in scale-free networks",
  "authors": [
    "Lazaros K. Gallos",
    "Panos Argyrakis"
  ],
  "comment": "7 pages, 3 figures, submitted to Physica A; Improved the discussion and shifted the emphasis on the distributions of figure 2. Because of this we had to change the title of the paper",
  "journal": "Physica A 330, 117 (2003)",
  "categories": [
    "cond-mat.dis-nn",
    "cond-mat.stat-mech",
    "q-bio"
  ],
  "abstract": "We use scale-free networks to study properties of the infected mass $M$ of the network during a spreading process as a function of the infection probability $q$ and the structural scaling exponent $\\gamma$. We use the standard SIR model and investigate in detail the distribution of $M$, We find that for dense networks this function is bimodal, while for sparse networks it is a smoothly decreasing function, with the distinction between the two being a function of $q$. We thus recover the full crossover transition from one case to the other. This has a result that on the same network a disease may die out immediately or persist for a considerable time, depending on the initial point where it was originated. Thus, we show that the disease evolution is significantly influenced by the structure of the underlying population.",
  "revisions": [
    {
      "version": "v2",
      "updated": "2003-03-18T10:13:37.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "scale-free networks",
      "infected mass",
      "disease spreading",
      "distribution",
      "standard sir model"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 7,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}