Monkeypox: A review of epidemiological modelling studies and how modelling has led to mechanistic insight
Bibliographic record
Abstract
Abstract Human monkeypox virus (mpox) is a viral zoonosis belonging to the Orthopoxvirus genus of the Poxviridae family that presents with similar symptoms as seen previously in human smallpox patients. mpox is a growing concern internationally with over 80000 cases in non-endemic countries as of December 2022. In this review, we briefly cover the history and origins of mpox and describe its basic virology, noting key differences in mpox viral fitness traits pre and post-2022. We then summarize and critique current knowledge from epidemiological mathematical models, within-host models, and between-host transmission models. We distinguish between models that focus on immunity from vaccination, as well as geography, climatic variables, and animal models. We report various epidemiological parameters, such as the reproduction number R0, in a condensed format for ease of comparison between studies. We focus specifically on how mathematical modelling studies have led to novel mechanistic insight into Monkeypox transmission and pathogenesis. As mpox continues to emerge and is predicted to continue to form subsequent peaks in many historically non-endemic countries, mpox mathematical modelling studies can provide rapid actionable insight into viral dynamics to guide public health measures and mitigation strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".