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Record W4414606205 · doi:10.1371/journal.pclm.0000546

Investigating the recommendations and governmental actions to address the emerging risks of vector-borne diseases in Canada’s changing climate: A scoping review

2025· article· en· W4414606205 on OpenAlex
Renée Schryer, Manisha A. Kulkarni

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePLOS Climate · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsAdaptation (eye)Consistency (knowledge bases)Government (linguistics)Inclusion (mineral)Grey literatureClimate change adaptationPopulation healthPopulation

Abstract

fetched live from OpenAlex

Climate change is expected to increase the risks associated with vector-borne diseases, and its implications for human health are already being observed across Canada. The objective of this review was to investigate the recommended adaptation strategies related to the risks associated with vector-borne diseases and examine how various levels of government in Canada are executing these recommended actions in their climate change adaptation plans. A combined methodology was employed, consisting of two distinct searches to examine both the recommended adaptation strategies in the peer-reviewed literature and the adaptation actions from governmental sources in the grey literature. Relevant sources were identified across four databases (Embase, Medline, Scopus, Global Health), as well as national, subnational, and municipal governmental websites across Canada. Data were categorized into eight (8) specific adaptation categories based on previously established frameworks. Data were also collected on which vector-borne diseases were referenced, the vulnerable population groups considered, and the inclusion of a One Health focus. A total of 198 peer-reviewed articles and 89 grey literature sources were reviewed, which contained a total of 591 groups of adaptation recommendations and 184 groups of adaptation actions. The categories of ‘Information and Research’ , ‘Capacity Building’ , and ‘Warning and Observation Systems’ demonstrated the greatest consistency between proposed recommendations and implemented actions. Our findings revealed a strong alignment between the recommended strategies and the adaptation measures being implemented. However, notable discrepancies were present among the categories of ‘ Management, Planning, and Policy’, ‘Practice and Behaviour’ , and ‘Laboratory Methods and Other Tools’ , revealing gaps across the literature and potential opportunities for further action. While many recommended strategies are being incorporated into actions across Canada, significant regional variability and gaps remain. We advocate for an increased investment in adaptation measures targeting vector-borne diseases and a greater integration of the One Health approach in subnational and municipal plans.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.123
GPT teacher head0.383
Teacher spread0.259 · 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