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Record W2772377732 · doi:10.1186/s40985-017-0072-5

The impact of programs for prevention of mother-to-child transmission of HIV on health care services and systems in sub-Saharan Africa - A review

2017· review· en· W2772377732 on OpenAlexafffund
Jean Claude Mutabazi, Christina Zarowsky, Helen Trottier

Bibliographic record

VenuePublic health reviews · 2017
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health ResearchUniversité de Montréal
KeywordsMedicineHealth careMEDLINEFamily medicinePublic healthInclusion (mineral)Scale (ratio)Transmission (telecommunications)Developing countryEnvironmental healthNursingEconomic growthPsychologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

BACKGROUND: The global scale-up of Prevention of mother-to-child transmission (PMTCT) services is credited for a 52% worldwide decline in new HIV infections among children between 2001 and 2012. However, the epidemic continues to challenge maternal and paediatric HIV control efforts in Sub Saharan Africa (SSA), with repercussions on other health services beyond those directly addressing HIV and AIDS. This systematised narrative review describes the effects of PMTCT programs on other health care services and the implications for improving health systems in SSA as reported in the existing articles and scientific literature. The following objectives framed our review:To describe the effects of PMTCT on health care services and systems in SSA and assess whether the PMTCT has strengthened or weakened health systems in SSATo describe the integration of PMTCT and its extent within broader programs and health systems. METHODS: Articles published in English and French over the period 1st January 2007 (the year of publication of WHO/UNICEF guidelines on global scale-up of the PMTCT) to 31 November 2016 on PMTCT programs in SSA were sought through searches of electronic databases (Medline and Google Scholar). Articles describing the impact (positive and negative effects) of PMTCT on other health care services and those describing its integration in health systems in SSA were eligible for inclusion. We assessed 6223 potential papers, reviewed 225, and included 57. RESULTS: The majority of selected articles offered arguments for increased health services utilisation, notably of ante-natal care, and some evidence of beneficial synergies between PMTCT programs and other health services especially maternal health care, STI prevention and early childhood immunisation. Positive and negative impact of PMTCT on other health care services and health systems are suggested in thirty-two studies while twenty-five papers recommend more integration and synergies. However, the empirical evidence of impact of PMTCT integration on broader health systems is scarce. Underlying health system challenges such as weak physical and human resource infrastructure and poor working conditions, as well as social and economic barriers to accessing health services, affect both PMTCT and the health services with which PMTCT interacts. CONCLUSIONS: PMTCT services increase to some extent the availability, accessibility and utilisation of antenatal care and services beyond HIV care. Vertical PMTCT programs work, when well-funded and well-managed, despite poorly functioning health systems. The beneficial synergies between PMTCT and other services are widely suggested, but there is a lack of large-scale evidence of this.

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.249
GPT teacher head0.513
Teacher spread0.264 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations77
Published2017
Admission routes2
Has abstractyes

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