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Record W2607307934 · doi:10.1186/s12936-017-1792-1

Defining micro-epidemiology for malaria elimination: systematic review and meta-analysis

2017· review· en· W2607307934 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMalaria Journal · 2017
Typereview
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
Fundersnot available
KeywordsMalariaEpidemiologyEnvironmental healthPublic healthMeta-analysisDemographyMedicineTropical medicineImmunologyInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Malaria risk can vary markedly between households in the same village, or between villages, but the determinants of this "micro-epidemiological" variation in malaria risk remain poorly understood. This study aimed to identify factors that explain fine-scale variation in malaria risk across settings and improve definitions and methods for malaria micro-epidemiology. METHODS: A systematic review of studies that examined risk factors for variation in malaria infection between individuals, households, clusters, hotspots, or villages in any malaria-endemic setting was conducted. Four databases were searched for studies published up until 6th October 2015. Crude and adjusted effect estimates for risk factors for malaria infection were combined in random effects meta-analyses. Bias was assessed using the Newcastle-Ottawa Quality Assessment Scale. RESULTS: From 743 retrieved records, 51 studies were selected, representing populations comprising over 160,000 individuals in 21 countries, in high- and low-endemicity settings. Sixty-five risk factors were identified and meta-analyses were conducted for 11 risk factors. Most studies focused on environmental factors, especially increasing distance from a breeding site (OR 0.89, 95% CI 0.86-0.92, 10 studies). Individual bed net use was protective (OR 0.63, 95% CI 0.52-0.77, 12 studies), but not household bed net ownership. Increasing household size (OR 1.08, 95% CI 1.01-1.15, 4 studies) and household crowding (OR 1.79, 95% CI 1.48-2.16, 4 studies) were associated with malaria infection. Health seeking behaviour, medical history and genetic traits were less frequently studied. Only six studies examined whether individual-level risk factors explained differences in malaria risk at village or hotspot level, and five studies reported different risk factors at different levels of analysis. The risk of bias varied from low to high in individual studies. Insufficient reporting and comparability of measurements limited the number of meta-analyses conducted. CONCLUSIONS: Several variables associated with individual-level malaria infection were identified, but there was limited evidence that these factors explain variation in malaria risk at village or hotspot level. Social, population and other factors may confound estimates of environmental risk factors, yet these variables are not included in many studies. A structured framework of malaria risk factors is proposed to improve study design and quality of evidence in future micro-epidemiological studies.

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)0.015
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.671
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0210.008
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.250
GPT teacher head0.463
Teacher spread0.212 · 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