Level of HIV serodiscordance and associated factors among heterosexual couples in Ethiopia: A systematic review and meta-analysis
Bibliographic record
Abstract
HIV-related causes accounted for approximately 770,000 deaths globally in 2018. Globally, there were 1.7 million new infections, and approximately 37.9 million people were living with HIV by the end of 2018. According to the WHO 2018 study, the African Region was the most affected, with 25.7 million people living with HIV in 2018. In Africa, married and cohabiting couples have a high prevalence of HIV discordance, ranging from 3% to 20% in the general population. Therefore, it is crucial to understand the level of HIV serodiscordance among married couples in Ethiopia and the contributing factors. Studies were systematically searched, utilizing international databases such as PubMed, Google Scholar, Cochrane Library, and Embase. The level of quality of the included articles, which employed cross-sectional and cohort study designs, was evaluated using the New Castle Ottawa scale. The systematic review employed a random-effects approach, and statistical analysis was conducted using STATA version 17 software. The presence of statistical heterogeneity within the included studies was assessed using the I-squared statistic. The random-effects meta-analysis model was used to estimate the pooled level of HIV serodiscordance. The results were reported following the Preferred Reporting Item for Systematic Review and Meta-Analyses (PRISMA) guideline. A total of ten (10) observational studies were included in this review. The pooled level of HIV serodiscordance among married heterosexual couples in Ethiopia was found to be 11.4% (95% CI = 7% -15.7%). The results from the meta-analysis indicated a significant positive association between HIV serodiscordance and the variables studied. Specifically, consistently using condoms (OR = 1.82; 95% CI: 1.08-2.56), having a CD4 count of >200 cells/mm3 (OR = 1.45; 95% CI: 1.12-1.77), and having a premarital sexual relationship (OR = 1.93; 95% CI: 1.28-2.57) were strongly linked to couples' serodiscordance. To protect a seronegative partner in a serodiscordant relationship from acquiring HIV infection, it is crucial to implement preventive measures. These measures include providing comprehensive health education on the correct and consistent use of condoms, ensuring regular monitoring and care at an antiretroviral therapy (ART) clinic, and offering voluntary counseling and testing (VCT) services to both sexual partners.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".