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Record W4416260983 · doi:10.1016/j.mbs.2025.109567

Do “soft” interventions matter more than vaccination? Rabies as an example

2025· article· en· W4416260983 on OpenAlexafffund
Nyuk Sian Chong, Thanisha Kaliapan, Can Chen, Kok Choon Cheah, Robert J. Smith

Bibliographic record

VenueMathematical Biosciences · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversiti Malaysia Terengganu
KeywordsPsychological interventionRabiesBasic reproduction numberIncidence (geometry)Intervention (counseling)VaccinationReproduction

Abstract

fetched live from OpenAlex

Interventions such as vaccinations, treatment et cetera are usually the gold standard of disease control, as measured by reducing the reproduction number below unity. However, in practice, few diseases are reduced below this eradication threshold and instead persist despite active intervention campaigns. We propose an epidemic model of rabies with a saturated incidence rate that represents "soft" interventions such as public-awareness campaigns, animal curfews, fences etc. We prove local and global stability results based on the reproduction number. However, numerical simulations suggest that eradication is unlikely to occur using current practices. We thus investigate the effect of altering the saturated incidence term using "soft" interventions and show that near-eradication can be achieved even when the reproduction number exceeds unity. Soft interventions such as public-awareness campaigns, reducing contacts, animal curfews and fences can have a greater effect on eradicating rabies than current vaccination programs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.039
GPT teacher head0.342
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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