Community-Based Assessment to Determine the Seroprevalence of HBsAg, Anti-HBs, Anti-HCV, HIV, and Syphilis for Reproductive-Aged Female Syrian Refugees Living in Sanliurfa, Turkey
Bibliographic record
Abstract
Background: Sanliurfa, a city of southeast Turkey hosted to approximately 401,050 Syrian refugees. There are no data about the sexually transmitted infections (STI) of Syrian refugees in literature. Hence, it was aimed to determine the seroprevalence of hepatitis B surface antigens (HBsAg), hepatitis B surface antibodies (anti-HBs), hepatitis C virus antibodies (anti-HCV), human immunodeficiency virus (HIV), and syphilis. Methods: A multi-purpose cross sectional study was conducted between April and May 2015 in different districts of Sanliurfa. This study was supported by United Nations Population Fund with the project titled “Determination of General Health Status and Reproductive Health Problems in Syrian Immigrants”. The sample size was calculated as 460 houses by the probability cluster sampling method. A married Syrian woman was chosen in each house, thus study was successfully carried out in 458 houses. Data included socio-demographic variables; the symptoms of vaginal purulent discharge, bleeding, abdominal pain, and dysuria were collected from each participant. Eight mL of venous blood samples were collected from participants. Sera were analyzed for HBsAg, anti-HBs, anti-HCV, HIV, syphilis. Results: The mean age of the total participants was 30.0 ± 8.9 years. The households of the family ranged from 2 - 27; the mean household size was 9.9 ± 4.9 persons. The seroprevalence rates of the HBsAg, anti-HBs, anti-HCV seropositivity were 4.1%, 17.7%, 0.4%, respectively. No one had neither HIV nor syphilis antibodies. Conclusions: Screening should be provided for STI for female refugees and they should be educated about the increasing awareness, transmission, control, prevention of STIs, blood-borne diseases. Clin Infect Immun. 2018;3(2):45-51 doi: https://doi.org/10.14740/cii57w
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".