{
  "annotation_id": "74e77a02-313b-48b3-8c45-37a173c5fa2d",
  "date_created": "2026-03-02T18:01:31.408000Z",
  "date_modified": "2026-03-02T18:01:31.408000Z",
  "file_hash": "44d457c9fe3edf97e2586c6479b8b37148fdf7fd5e0c58d652a4575197c6366a",
  "private": false,
  "record": {
    "abstract": "Viral kinetics have been extensively studied in the past through the use of\nspatially homogeneous ordinary differential equations describing the time\nevolution of the diseased state. However, spatial characteristics such as\nlocalized populations of dead cells might adversely affect the spread of\ninfection, similar to the manner in which a counter-fire can stop a forest fire\nfrom spreading. In order to investigate the influence of spatial\nheterogeneities on viral spread, a simple 2-D cellular automaton (CA) model of\na viral infection has been developed. In this initial phase of the\ninvestigation, the CA model is validated against clinical immunological data\nfor uncomplicated influenza A infections. Our results will be shown and\ndiscussed.",
    "arxiv_id": "q-bio/0402012",
    "authors": [
      "Catherine Beauchemin",
      "John Samuel",
      "Jack Tuszynski"
    ],
    "categories": [
      "q-bio.CB",
      "q-bio.QM"
    ],
    "doi": "10.1016/j.jtbi.2004.08.001",
    "journal_ref": "Journal of Theoretical Biology, 232(2), 21 January 2005, pp.\n  223-234",
    "title": "A Simple Cellular Automaton Model for Influenza A Viral Infections",
    "url": "https://arxiv.org/abs/q-bio/0402012"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "b8fd6a42-9ebd-4e9f-88ad-1e13f0ff5a1b",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}