Underestimated Prevalence of HIV, Hepatitis B Virus (HBV), and Hepatitis D Virus (HDV) Triple Infection Globally: Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Hepatitis delta virus (HDV) is a satellite RNA virus that relies on hepatitis B virus (HBV) for transmission. HIV/HBV/HDV coinfection or triple infection is common and has a worse prognosis than monoinfection. OBJECTIVE: We aimed to reveal the epidemiological characteristics of HIV/HBV/HDV triple infection in the global population. METHODS: A systematic literature search in PubMed, Embase, and the Cochrane Library was performed for studies of the prevalence of HIV/HBV/HDV triple infection published from January 1, 1990, to May 31, 2021. The Der Simonian-Laird random effects model was used to calculate the pooled prevalence. RESULTS: We included 14 studies with 11,852 participants. The pooled triple infection rate in the global population was 7.4% (877/11,852; 95% CI 0.73%-29.59%). The results of the subgroup analysis showed that the prevalence of triple infection was significantly higher in the Asian population (214/986, 21.4%; 95% CI 7.1%-35.8%), in men (212/5579, 3.8%; 95% CI 2.5%-5.2%), and in men who have sex with men (216/2734, 7.9%; 95% CI 4.3%-11.4%). In addition, compared with people living with HIV, the HIV/HBV/HDV triple infection rate was higher in people with hepatitis B. CONCLUSIONS: This meta-analysis suggests that the prevalence of HIV/HBV/HDV triple infection in the global population is underestimated, and we should focus more effort on the prevention and control of HIV/HBV/HDV triple infection. TRIAL REGISTRATION: PROSPERO CRD42021273949; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=273949.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".