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Record W4362659505 · doi:10.1016/j.pt.2023.03.006

How can the complex epidemiology of malaria in India impact its elimination?

2023· review· en· W4362659505 on OpenAlexfundno aff
Nikhat Khan, Gauri Awasthi, Aparup Das

Bibliographic record

VenueTrends in Parasitology · 2023
Typereview
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthIndian Council of Medical ResearchYork University
KeywordsMalariaPublic healthEpidemiologyEnvironmental healthGlobeAnophelesNeglected tropical diseasesGeographySocioeconomicsBiologyMedicineImmunology

Abstract

fetched live from OpenAlex

Malaria is a human health hazard in the tropical and subtropical zones of the globe and is poised to be eliminated by the year 2030. Despite a decrease in incidence in the past two decades, many endemic countries, including India, report cases regularly. The epidemiology of malaria in India is unique owing to several features of the Plasmodium parasites, Anopheles vectors, ecoepidemiological situations conducive to disease transmission, and susceptible humans living in rural and forested areas. Limitations in public health reach, and poor health-seeking behaviour of vulnerable populations living in hard-to-reach areas, add to the problem. We bring all of these factors together in a comprehensive framework and opine that, in spite of complexities, targeted elimination of malaria in India is achievable with planned programmatic approaches.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.200
GPT teacher head0.505
Teacher spread0.304 · 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.

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

Citations26
Published2023
Admission routes1
Has abstractyes

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