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Record W2150360884 · doi:10.1186/1475-2875-13-111

Estimating the annual entomological inoculation rate for Plasmodium falciparum transmitted by Anopheles gambiae s.l. using three sampling methods in three sites in Uganda

2014· article· en· W2150360884 on OpenAlexfundno aff
Maxwell Kilama, David L. Smith, Robert Hutchinson, Ruth Kigozi, Adoke Yeka, Geoff Lavoy, Moses R. Kamya, Sarah G. Staedke, Martin J. Donnelly, Chris Drakeley, Bryan Greenhouse, Grant Dorsey, Steve W. Lindsay

Bibliographic record

VenueMalaria Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthInternational Development Research Centre
KeywordsAnopheles gambiaeMalariaPlasmodium falciparumVeterinary medicineInsect bites and stingsBiologyAnophelesTransmission (telecommunications)Negative binomial distributionDemographyMedicineStatisticsImmunologyMathematics

Abstract

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BACKGROUND: The Plasmodium falciparum entomological inoculation rate (PfEIR) is a measure of exposure to infectious mosquitoes. It is usually interpreted as the number of P. falciparum infective bites received by an individual during a season or annually (aPfEIR). In an area of perennial transmission, the accuracy, precision and seasonal distribution (i.e., month by month) of aPfEIR were investigated. Data were drawn from three sites in Uganda with differing levels of transmission where falciparum malaria is transmitted mainly by Anopheles gambiae s.l. Estimates of aPfEIR derived from human-landing catches--the classic method for estimating biting rates--were compared with data from CDC light traps, and with catches of knock down and exit traps separately and combined. METHODS: Entomological surveillance was carried out over one year in 2011/12 in three settings: Jinja, a peri-urban area with low transmission; Kanungu, a rural area with moderate transmission; and Nagongera, Tororo District, a rural area with exceptionally high malaria transmission. Three sampling approaches were used from randomly selected houses with collections occurring once a month: human-landing collections (eight houses), CDC light traps (100 houses) and paired knock-down and exit traps each month (ten houses) for each setting. Up to 50 mosquitoes per month from each household were tested for sporozoites with P. falciparum by ELISA. Human biting rate (HBR) data were estimated month by month. P. falciparum Sporozoite rate (PfSR) for yearly and monthly data and confidence intervals were estimated using the binomial exact test. Monthly and yearly estimates of the HBR, the PfSR, and the PfEIR were estimated and compared. RESULTS: The estimated aPfEIR values using human-landing catch data were 3.8 (95% Confidence Intervals, CI 0-11.4) for Jinja, 26.6 (95% CI 7.6-49.4) for Kanungu, and 125 (95% CI 72.2-183.0) for Tororo. In general, the monthly PfEIR values showed strong seasonal signals with two peaks from May-June and October-December, although the precise timing of the peaks differed between sites. Estimated HBRs using human-landing catches were strongly correlated with those made using CDC light traps (r(2) = 0.67, p < 0.001), and with either knock-down catches (r(2) = 0.56, p < 0.001) and exit traps (r(2) = 0.82, p < 0.001) or the combined catches (r(2) = 0.73, p < 0.001). Using CDC light trap catch data, the PfSR in Tororo was strongly negatively correlated with monthly HBR (r(2) = 0.44, p = 0.01). In other sites, no patterns in the PfSR were discernible because either the number P. falciparum of sporozoite positive mosquitoes or the total number of mosquitoes caught was too low. CONCLUSIONS: In these settings, light traps provide an alternative method for sampling indoor-resting mosquitoes to human-landing catches and have the advantage that they protect individuals from being bitten during collection, are easy to use and are not subject to collector bias. Knock-down catches and exit traps could also be used to replace human-landing catches. Although these are cheaper, they are subject to collector bias.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.067
GPT teacher head0.380
Teacher spread0.313 · 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 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

Citations234
Published2014
Admission routes1
Has abstractyes

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