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Record W2742089346 · doi:10.1186/s12936-017-1951-4

How many holes is too many? A prototype tool for estimating mosquito entry risk into damaged bed nets

2017· article· en· W2742089346 on OpenAlexaff
J. F. SUTCLIFFE, Xin Ji, Shaoman Yin

Bibliographic record

VenueMalaria Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsTrent University
FundersPresident's Malaria InitiativeCenters for Disease Control and Prevention
KeywordsBed netsAnopheles gambiaeMosquito netMalariaAnophelesMalaria preventionEnvironmental scienceHydrology (agriculture)BiologyGeologyDemographyGeotechnical engineeringEngineeringStructural engineeringPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: Insecticide-treated bed nets (ITNs) have played an integral role in malaria reduction but how insecticide depletion and accumulating physical damage affect ITN performance is poorly understood. More accurate methods are needed to assess damage to bed nets so that they can be designed, deployed and replaced optimally. METHODS: Video recordings of female Anopheles gambiae in near approach (1-½ cm) to occupied untreated rectangular bed nets in a laboratory study were used to quantify the amount of mosquito activity (appearances over time) around different parts of the net, the per-appearance probability of a mosquito coming close to holes of different sizes (hole encounter) and the per-encounter probability of mosquitoes passing through holes of different sizes (hole passage). RESULTS: Appearance frequency on different parts of the net reflected previously reported patterns: the area of the net under greatest mosquito pressure was the roof, followed by the bottom 30 cm of the sides, followed by the 30 cm area immediately above this, followed by the upper two-thirds of the sides. The ratio of activity in these areas was (respectively) 250:33:5:1. Per-appearance probability of hole encounter on all parts of the net was strongly predicted by a factor combining hole perimeter and area. Per-encounter probability of hole passage, in turn, was strongly predicted by hole width. For a given width, there was a 20% greater risk of passage through holes on the roof than holes on the sides. DISCUSSION: Appearance, encounter and passage predictors correspond to various mosquito behaviours that have previously been described and are combined into a prototype mosquito entry risk tool that predicts mosquito entry rates for nets with various amounts of damage. Scenarios that use the entry risk tool to test the recommendations of the WHOPES proportionate hole index (pHI) suggest that the pHI hole size categories and failure to account for hole location likely sometimes lead to incorrect conclusions about net serviceability that could be avoided by using an entry risk tool of the form presented here instead. Practical methods of collecting hole position, shape and size information for bed net assessments using the tool in the field are discussed and include using image analysis and on-line geometric analysis tools.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.312
Teacher spread0.290 · 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.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations24
Published2017
Admission routes1
Has abstractyes

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