Prevalence and Risk Factors Associated with HIV Infection among Pregnant Women in Odisha State, India
Bibliographic record
Abstract
Background and Objectives: The purpose of this study was to analyze trends in HIV prevalence and risk factors associated with HIV infection among pregnant women attending antenatal clinics in Odisha State, India. Methods: Data were from the HIV Sentinel Surveillance (HSS) among pregnant women, a descriptive cross-sectional study using consecutive sampling method and conducted in India. Data and samples were collected from pregnant women attending select antenatal clinics that act as designated sentinel sites in Odisha State, India, during the three months surveillance period and in three surveillance years: 2013, 2015, and 2017. All eligible pregnant women aged between 15 and 49 years, attending the sentinel sites for the first time during the surveillance period, were included. Information on their socio-demographic characteristics and blood samples were also collected. Results: In total, 38,384 eligible pregnant women were included in the survey. Of these, 107 women were HIV positive, with an overall prevalence of 0.28%. HIV prevalence indicated a stabilizing trend between 2013 and 2017. However, pregnant women whose spouses were non-agricultural laborers, truck drivers, or migrants were significantly at higher risk of being infected. Likewise, HIV prevalence significantly increased over the years among pregnant women whose spouses were in the service sector (government or private). District-wise fluctuations in HIV prevalence was observed, with the district of Cuttack recording the highest prevalence among the districts. Conclusion and Global Health Implications: Women who are spouses of non-agricultural laborers, truck drivers or migrants need focused interventions, such as creating awareness on HIV and its prevention. Migration, due to poverty and its impact on sexually transmitted diseases among migrants from low and middle-income countries, have been documented globally. Single male migrant specific interventions are recommended to halt the disease progression among pregnant women and general population in Odisha, India. Key words: • HIV sentinel surveillance • Pregnant women • HIV prevalence • Socio-demographic factor • Odisha • India Copyright © 2020 Santhakumar et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) which permits unre-stricted use, distribution, and reproduction in any medium, provided the original work, first published in this journal, is properly cited.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".