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Record W4405397627 · doi:10.1080/01605682.2024.2436622

Operational research on dengue: critical review and research agenda

2024· article· en· W4405397627 on OpenAlexaff
Laura Silva de Assis, Fábio Luiz Usberti, Emrah Demir, Celso Cavellucci, Gilbert Laporte

Bibliographic record

VenueJournal of the Operational Research Society · 2024
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsHEC Montréal
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsDengue feverOperations researchComputer scienceProject managementManagement scienceProcess managementBusinessSystems engineeringEngineeringMedicineVirology

Abstract

fetched live from OpenAlex

Dengue fever presents a significant global health challenge with profound socioeconomic implications, particularly in developing countries. Effective control strategies for dengue are vital to mitigate its impact on health systems and communities. This study presents a critical review of operational research (OR) studies on dengue research published in the last two decades, including topics such as transmission dynamics, forecasting, and optimization. We also identify current trends, research gaps, and potential research avenues for future investigation in these domains. More specifically, this study serves as a ground resource for academic researchers, practitioners, and healthcare authorities. It provides insights into the latest methodologies to improve dengue control efforts and encourages OR researchers to investigate this crucial health threat. Such efforts can greatly reduce healthcare expenses and improve public health.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.010
Science and technology studies0.0010.003
Scholarly communication0.0040.006
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.255
GPT teacher head0.558
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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