{
  "abstract": "Conventional compartmental models may become difficult to parameterize over multi-wave epidemic horizons when susceptibility and transmission conditions change between successive epidemic regimes. This study introduces a reduced macroscopic framework that changes the scale of epidemic description from individual-level transmission structure to effective population-level dynamics. Epidemic waves are formulated as transport processes governed by deterministic boundaries, mass balance, and a small set of effective macroscopic parameters. The susceptible population is represented by a dynamic Effective Susceptible Pool that can be re-initialized at transitions between biologically distinct epidemic regimes, while transmission resistance and external control measures are incorporated at the macroscopic level. The resulting equations admit a dimensionless similarity representation and closed-form analytical solutions, enabling analytical estimation of epidemic trajectories and peak healthcare demand without computationally intensive numerical simulation. The framework is evaluated using comparative time-series data for SARS-CoV-2 and seasonal influenza A within the geographically and demographically consistent setting of Rhode Island. Despite their different biological and immunological regimes, the analyzed trajectories exhibit a common reduced asymptotic scaling form. The results support the use of a macroscopic, scale-reduced representation for cross-calibration of heterogeneous surveillance signals and analytical assessment of healthcare-system demand. Further validation across pathogens, populations, and open-system settings is required.\n\nHighlightsO_LIEpidemic waves are modeled analytically as macroscopic transport processes in non-linear media. C_LIO_LIThe vulnerable population is redefined as a dynamic, re-initialized effective susceptible pool. C_LIO_LIMass immunization acts as a synchronized control operator suppressing the epidemic peak. C_LIO_LIA strict mass-balance deconvolution filter removes post-symptomatic shedding noise. C_LIO_LIPeak hospital capacity thresholds are predicted using an analytically tractable closed-form method. C_LI",
  "abstract_shown": true,
  "affiliations": [
    "Alexianer Krankenhaus Hedwigshoehe"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "D. Below"
    },
    {
      "name": "F. Mairanowski"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/frg3w4bh0kmg8.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.16.26363217",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.16.26363217v1.full",
  "id": "frg3w4bh0kmg8",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.16.26363217v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "public and global health"
    ],
    [
      "openalex",
      "2611|COVID-19 epidemiological studies"
    ]
  ],
  "openalex": "W7213558845",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.16.26363217v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/frg3w4bh0kmg8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:48Z",
      "native_id": "10.64898/2026.09.16.26363217",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.16.26363217v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:public and global health",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "UNIVERSAL EPIDEMIC SCALING: INFLUENZA AND COVID-19",
  "title_text": "UNIVERSAL EPIDEMIC SCALING: INFLUENZA AND COVID-19",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:48Z",
  "url": "https://research.draconitic.com/paper/frg3w4bh0kmg8",
  "venue": "medRxiv",
  "versions": []
}