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Record W4319442882 · doi:10.21203/rs.3.rs-2460278/v1

Monkeypox: A review of epidemiological modelling studies and how modelling has led to mechanistic insight

2023· review· en· W4319442882 on OpenAlexaff
Chapin S. Korosec, Marina Banuet-Martínez, Yang Yang, Behnaz Jafari, Avneet Kaur, Zahid A Butt, Helen Chen, Svetlana Yanushkevich, Iain R. Moyles, Jane M. Heffernan

Bibliographic record

VenueResearch Square · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsUniversity of British Columbia, Okanagan CampusYork UniversityUniversity of British ColumbiaUniversity of CalgaryUniversity of AlbertaOkanagan University CollegeUniversity of Waterloo
Fundersnot available
KeywordsMonkeypoxOrthopoxvirusSmallpoxZoonosisEpidemiologyTransmission (telecommunications)Public healthBasic reproduction numberBiologyVirologyGeographyVaccinationPopulationEnvironmental healthMedicineVacciniaComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.507
GPT teacher head0.489
Teacher spread0.018 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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