Determinants of HIV infection among pregnant women in Cameroon: A contribution toward the elimination of vertical transmission in low- and middle-income countries
Bibliographic record
Abstract
Abstract Background The risk of HIV transmission during antenatal care (ANC) in Cameroon remains a concern. According to recent studies, the prevalence of HIV in the country is around 4.5%, which increases the likelihood of vertical transmission. Objective To identify the determinants of HIV infection among pregnant women attending antenatal clinics (ANC) in Cameroon and to estimate HIV seroprevalence. Methods A cross-sectional study was conducted among ANC attendees aged ≥15 years from September 2022 to June 2023 in 324 health facilities in 08 regions of Cameroon (Adamaoua, Yaounde, East, Far-North, Douala, North, West, South). Sociodemographic and clinical data were collected using questionnaire. HIV screening was performed according to the national algorithm. Estimates of HIV seroprevalence and identification of its determinants using multivariable logistic regression (95% CI) were performed with Excel and SPSS 22 software. Results Overall, 10674 pregnant women were enrolled, with median [IQR] age 25 years [21– 30]; 40.0% at a secondary educational level; 44.1% married monogamously; 46.3% multiparous; 38.8% in the second quarter of pregnancy and 16.5% reporting at least one abortion. Overall HIV seroprevalence was 2.6% [95%CI: 2.33; 2.93]. Significantly higher prevalence was found with the regions of Adamaoua (aOR 3.78 [95%CI: 1.87-7.67], p<0.001), East (9.38 [5.6-15.67], p<0.001), North (3.07 [1.74-5.42], p<0.001), South (2.93 [1.66-5.16]; p<0.001); lack of education (2.08 [1.06-4.06], p=0.032), primary education (2.44 [1.32-4.50], p=0.004) and secondary education (2.29 [1.28-4.08], p=0.005) were significantly associated with HIV infection, while monogamous marriage (0.33 [0.22-0.51], p<0.001), the absence of abortion (0.59 [0.37-0.98], p=0.036) and large multiparous (0.38 [0.17-0.82]; p=0.015) were protective. Conclusion Despite the overall low-prevalence among pregnant women at national-level, several factors are associated with HIV in ANC, the absence or low-level of education, being elderly (>30 years), singleness, history of abortion and low parity predicted the HIV status during ANC. Thus, public health interventions towards these at-risk target groups will help to reduce new infections among pregnant women, hence contributing to achieve eMTCT in Cameroon.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".