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Record W2886581204 · doi:10.4314/ahs.v18i3.8

HIV Epidemiology in Uganda: survey based on age, gender, number of sexual partners and frequency of testing

2018· article· en· W2886581204 on OpenAlexaboutno aff
Jay Vithalani, Marta Herreros‐Villanueva

Bibliographic record

VenueAfrican Health Sciences · 2018
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDemographyQuarter (Canadian coin)EpidemiologyHuman immunodeficiency virus (HIV)PopulationDeveloping countrySexual partnerGerontologyEnvironmental healthImmunologyGonorrheaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Human Immunodeficiency Virus (HIV) is a major cause of morbidity and mortality in the world. When compared to the developed countries where HIV prevalence is on the decline, sub-Saharan Africa has experienced either a rise or stagnation in rates. OBJECTIVES: The aim of this study was to test and educate the community in the villages of Masajja and Kibiri of Wakiso district in Uganda for HIV and safe sex practices. METHODS: A sociodemographic survey was also performed to obtain data for gender, age, number of sexual partners during the previous year, frequency of testing and if ever tested positive for other sexually transmitted diseases (STDs). RESULTS: While 7 of the tested individuals were positive for HIV, 77 reported that they had once tested positive for other STDs. Of the 7 HIV positive individuals, 4 were females and 3 males. Over half of the tested individuals reported only one sexual partner in past 12 months and more than a quarter were sexually active with more than one partner. Majority of our population also reported getting HIV tested every 6 months or less. CONCLUSION: Robust implementation of methods such as education and frequent testing can lower Uganda's prevalence of HIV even further.

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)0.014
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.523
GPT teacher head0.556
Teacher spread0.033 · 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
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

Citations40
Published2018
Admission routes1
Has abstractyes

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