MétaCan
Menu
Back to cohort
Record W2111550957 · doi:10.1136/sextrans-2013-051297

Second generation HIV surveillance in Pakistan: evidence for understanding the epidemic and planning a response

2013· editorial· en· W2111550957 on OpenAlexaff
James Blanchard, Laura H. Thompson, Sevgi O. Aral

Bibliographic record

VenueSexually Transmitted Infections · 2013
Typeeditorial
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of ManitobaHealth Sciences Centre
Fundersnot available
KeywordsMedicineHuman immunodeficiency virus (HIV)VirologyEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

More than a decade ago UNAIDS and the WHO published a set of guidelines for the conduct of what was termed ‘second-generation HIV surveillance’, which encouraged the enhancement of HIV surveillance to provide better information about the patterns, status and trajectory of the HIV epidemic to better inform policies and programmes.1 As Rehle and colleagues have noted, key aspects of the second-generation approach include: combining information from different components of surveillance to achieve higher degrees of explanatory power, targeting segments of the population in which most new HIV infections are occurring; and integrating surveillance based on biological markers of infection (ie, HIV serosurveillance) with behavioural data.2 Since then, second-generation surveillance has become widely used in diverse global contexts, with substantial emphasis on two key components. The first component, sentinel HIV surveillance, has been conducted at convenient venues to track the amplitude and trends of HIV prevalence among populations based on presumed stratification of risk, such as women attending antenatal clinics, men and women attending public sexually transmitted disease clinics, and key populations at higher risk (such as female sex workers) receiving HIV prevention services. While this approach has provided important insights into the distribution and trends of HIV in different population segments, it has substantial constraints. Perhaps most importantly, it sacrifices representativeness for sampling efficiency, leading to uncertainty as to how well the results truly reflect the HIV prevalence in these populations. In addition, sentinel surveillance does not incorporate any assessment of behavioural trends, or the linkage between biological, socio-demographic, and behavioural variables with HIV status. As a result, it does not provide information about patterns and trends in the key behaviours that influence epidemics, nor does it permit a more in-depth understanding of relationships between socio-demographic characteristics and behaviours with HIV prevalence. To address this deficit, the …

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.101
GPT teacher head0.400
Teacher spread0.299 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSexually Transmitted InfectionsSame topicHIV, Drug Use, Sexual RiskFrench-language works237,207