Bayesian Comparison of Covid Origins Hypotheses

Abstract

Applying standard Bayesian methods to the most reliably known unclassified facts about the Covid epidemic allows crude estimation of the odds for research-related vs. purely zoonotic origins. Here a broadly inclusive zoonotic hypothesis is compared with a rather specific subset of the research-related hypothesis defined by known prior work and grant proposals. The important observations are the type of virus, the city of the first outbreak, the lack of known prior hosts, the anomalous early pattern of evolution, and two specific features of the viral sequence. The resulting odds strongly favor research. The odds remain fairly strong under inclusion of uncertainties in prior odds.

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BibTeX

@misc{weissman2026bayesian,
  title = {{Bayesian Comparison of Covid Origins Hypotheses}},
  author = {Michael B. Weissman},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.29766},
  eprint = {2610.29766},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.29766},
  note = {CC BY 4.0},
}

RIS

TY  - UNPB
TI  - Bayesian Comparison of Covid Origins Hypotheses
AU  - Michael B. Weissman
PY  - 2026
DA  - 2026/10/21
PB  - arXiv
DO  - 10.48550/arxiv.2610.29766
UR  - https://arxiv.org/abs/2610.29766
AB  - Applying standard Bayesian methods to the most reliably known unclassified facts about the Covid epidemic allows crude estimation of the odds for research-related vs. purely zoonotic origins. Here a broadly inclusive zoonotic hypothesis is compared with a rather specific subset of the research-related hypothesis defined by known prior work and grant proposals. The important observations are the type of virus, the city of the first outbreak, the lack of known prior hosts, the anomalous early pattern of evolution, and two specific features of the viral sequence. The resulting odds strongly favor research. The odds remain fairly strong under inclusion of uncertainties in prior odds.
ER  -

Abstract

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