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Record W2615542916

Multi-Criteria Decision Analysis as an Innovative Approach to Managing Zoonoses: Results from a Study on Lyme Disease in Canada

2013· article· en· W2615542916 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLes Cahiers du GERAD · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsPublic Health Agency of CanadaUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsPsychological interventionMultiple-criteria decision analysisDisease surveillanceLyme diseaseDecision analysisRisk analysis (engineering)Public healthEnvironmental resource managementEnvironmental healthBusinessManagement scienceMedicineOperations researchEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a “One Health” perspective.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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