{
  "annotation_id": "31133572-8abc-40c6-8f6f-31c6ab15d964",
  "date_created": "2026-03-02T18:01:00.869000Z",
  "date_modified": "2026-03-02T18:01:00.869000Z",
  "file_hash": "da971a1202941c42d315400060d6a03d1e34c8362c8ac64acbc949f5d08bde30",
  "private": false,
  "record": {
    "abstract": "Most epidemic models assume equal mixing among members of a population. An\nalternative approach is to model a population as random network in which\nindividuals may have heterogeneous connectivity. This paper builds on previous\nresearch by describing the exact dynamical behavior of epidemics as they occur\nin random networks. A system of nonlinear differential equations is presented\nwhich describes the behavior of epidemics spreading through random networks\nwith arbitrary degree distributions. The degree distribution is observed to\nhave significant impact on both the final size and time scale of epidemics.",
    "arxiv_id": "physics/0508160",
    "authors": [
      "Erik Volz"
    ],
    "categories": [
      "physics.soc-ph",
      "cond-mat.dis-nn",
      "cond-mat.other",
      "q-bio.OT"
    ],
    "title": "SIR dynamics in structured populations with heterogeneous connectivity",
    "url": "https://arxiv.org/abs/physics/0508160"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3af65112-b0d6-4e5a-bf6b-a58a9015c915",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}