{
  "abstract": "BackgroundThe 2026 Bundibugyo Ebola outbreak in Uganda, linked to the ongoing epidemic in the Democratic Republic of the Congo (DRC), spread through human mobility across borders and within the country. Existing modelling has provided regional-level importation estimates but not district-level operational guidance. We developed an exploratory, scenariobased decision-support model to characterise subnational importation and spread patterns.\n\nMethodsWe constructed a directed, weighted mobility network using International Organization for Migration (IOM) Displacement Tracking Matrix (DTM) flows collected from 15-24 May 2026 (11,245 observed movements) and the 2024 Uganda census. A stochastic metapopulation SEIR model was simulated over 90 days across 135 Ugandan districts and two DRC provinces. We evaluated three scenario assumptions--containment (R0 = 0.80), moderate (R0 = 1.35), and weak (R0 = 2.76)--plus a one-factor-at-a-time analysis of nonpharmaceutical intervention (NPI) compliance. Global sensitivity analysis was performed using Morris elementary-effects screening and total-order Sobol indices.\n\nResultsThe mobility network was sparse (density 0.11), highly unequal (Gini 0.67), and modular (0.50). Kisoro had the highest import risk (in-strength 3,823) and export risk (outstrength 1,350). Under all three scenarios, the model projected similar cumulative case counts (median 20-21; pairwise Mann-Whitney p < 0.05). Under containment, Kampala was the only district with a non-zero median (20 cases, 95% simulation interval 20-22); all other districts had median 0. Prediction-interval coverage against the early observed curve was 0.80.\n\nConclusionsUnder the models containment assumptions, rapid 7-1-7 implementation was associated with substantial containment, but this is scenario-specific and does not imply that NPIs are unnecessary. Border surveillance, nationwide preparedness, and community engagement remain essential. These projections should be treated as exploratory and require prospective field-based validation.",
  "abstract_shown": true,
  "affiliations": [
    "IDEMU Mathematical Modelling Unit, Department of Epidemiology and Biostatistics, Makerere University School of Public Health, Kampala, Uganda"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 26,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "A. W. Walekhwa"
    },
    {
      "name": "P. Mbaka"
    },
    {
      "name": "B. K. Nannyonga"
    },
    {
      "name": "S. P. Silal"
    },
    {
      "name": "M. Bbuye"
    },
    {
      "name": "B. Magoba"
    },
    {
      "name": "L. Nakiire"
    },
    {
      "name": "M. Lamorde"
    },
    {
      "name": "T. A. Sulaimon"
    },
    {
      "name": "B. Kwesiga"
    },
    {
      "name": "W. Sabiiti"
    },
    {
      "name": "W. Mutamba"
    },
    {
      "name": "G. Turinawe"
    },
    {
      "name": "B. Nakazibwe"
    },
    {
      "name": "J. Kayiwa"
    },
    {
      "name": "M. Nantongo"
    },
    {
      "name": "P. A. Ipola"
    },
    {
      "name": "P. Kungu"
    },
    {
      "name": "A. R. Ario"
    },
    {
      "name": "A. Kagirita"
    },
    {
      "name": "B. Lubwama"
    },
    {
      "name": "B. J. Kirenga"
    },
    {
      "name": "M. Wayengera"
    },
    {
      "name": "A. N. Muruta"
    },
    {
      "name": "C. Olaro"
    },
    {
      "name": "D. Atwine"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/df3thwnyt49h9.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.06.22.26356210",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.06.22.26356210v3.full",
  "id": "df3thwnyt49h9",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.06.22.26356210v3",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "infectious diseases"
    ],
    [
      "openalex",
      "2725|Viral Infections and Outbreaks Research"
    ]
  ],
  "openalex": "W7165934071",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.06.22.26356210v3.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-06-22",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/df3thwnyt49h9.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:10Z",
      "native_id": "10.64898/2026.06.22.26356210",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.06.22.26356210v3"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:infectious diseases",
      "subfield": "infectious-disease"
    }
  ],
  "title": "Exploratory network-based modelling of Bundibugyo Ebola virus disease importation and spread in Uganda using Displacement Tracking Matrix flow data",
  "title_text": "Exploratory network-based modelling of Bundibugyo Ebola virus disease importation and spread in Uganda using Displacement Tracking Matrix flow data",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:10Z",
  "url": "https://research.draconitic.com/paper/df3thwnyt49h9",
  "venue": "medRxiv",
  "versions": []
}