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Record W2008019532 · doi:10.1371/journal.pone.0083778

Estimation of the HIV Basic Reproduction Number in Rural South West Uganda: 1991–2008

2014· article· en· W2008019532 on OpenAlexaff
Rebecca N. Nsubuga, Richard G. White, Billy N. Mayanja, Leigh Anne Shafer

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Manitoba
FundersMedical Research CouncilBill and Melinda Gates Foundation
KeywordsReproductionHuman immunodeficiency virus (HIV)EstimationBasic reproduction numberBiologyStatisticsGeographyDemographyMedicineEnvironmental healthMathematicsPopulationVirologyEcologySociologyEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: The basic reproduction number, [Formula: see text], is one of the many measures of the epidemic potential of an infection in a population. We estimate HIV [Formula: see text] over 18 years in a rural population in Uganda, examine method-specific differences in estimated [Formula: see text], and estimate behavioural changes that would reduce [Formula: see text] below one. METHODS: Data on HIV natural history and infectiousness were collated from literature. Data on new sexual partner count were available from a rural clinical cohort in Uganda over 1991-2008. [Formula: see text] was estimated using six methods. Behavioural changes required to reduce [Formula: see text] below one were calculated. RESULTS: Reported number of new partners per year was 0 to 16 (women) and 0 to 80 (men). When proportionate sexual mixing was assumed, the different methods yielded comparable [Formula: see text] estimates. Assuming totally assortative mixing led to increased [Formula: see text] estimates in the high sexual activity class while all estimates in the low-activity class were below one. Using the "effective" partner change rate introduced by Anderson and colleagues resulted in [Formula: see text] estimates all above one except in the lowest sexual activity class. [Formula: see text] could be reduced below one if: (a) medium risk individuals reduce their partner acquisition rate by 70% and higher risk individuals reduce their partner acquisition rate by 93%, or (b) higher risk individuals reduce the partner acquisition rate by 95%. CONCLUSIONS: The estimated [Formula: see text] depended strongly on the method used. Ignoring variation in sexual activity leads to an underestimation of [Formula: see text]. Relying on behaviour change alone to eradicate HIV may require unrealistically large reductions in risk behaviour, even though for a small proportion of the population. To control HIV, complementary prevention strategies such as male circumcision and HIV treatment services need rapid scale up.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.034
GPT teacher head0.285
Teacher spread0.252 · 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 designSimulation or modeling
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

Citations26
Published2014
Admission routes1
Has abstractyes

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