| Literature DB >> 31687480 |
Gheyath K Nasrallah1,2, Soha R Dargham3, Laith J Abu-Raddad3,4,5.
Abstract
OBJECTIVES: Existing evidence on an epidemiological association between herpes simplex virus (HSV) type 1 and type 2 infections remains conflicting and inconclusive. Using a multi-national database of HSV-1/2 serological testing, we aimed to assess the existence of an association between both infections. DESIGN SETTING AND PARTICIPANTS: An HSV-1/2 cross-sectional serological testing database was assembled by merging databases of seroprevalence studies on men blood donors residing currently in Qatar, but from different countries. Specimens were tested for anti-HSV-1 IgG antibodies using HerpeSelect® 1 ELISA, and for anti-HSV-2 IgG antibodies following a two-test algorithm: HerpeSelect® 2 ELISA to test the sera, and Euroline-WB to confirm positive and equivocal specimens. Logistic regressions were conducted to estimate unadjusted and adjusted infection odds ratios.Entities:
Keywords: Asia; Epidemiological association; Epidemiology; Herpes; Infectious disease; Interaction; Middle East and North Africa; Prevalence; Serological testing; Sexually transmitted infection; Virology
Year: 2019 PMID: 31687480 PMCID: PMC6820085 DOI: 10.1016/j.heliyon.2019.e02549
Source DB: PubMed Journal: Heliyon ISSN: 2405-8440
Sample characteristics of the merged database of the series of seroprevalence studies (Dargham et al., 2018; Nasrallah et al., 2018a, 2018b). Univariable and multivariable logistic regressions assessing the epidemiological association between HSV-1 and HSV-2 infections. Unadjusted and adjusted odds ratios (OR and aOR, respectively) of HSV-2 infection, along with the respective 95% confidence intervals (CI), were reported.
| Sample Characteristics | Univariable Analysis | Multivariable Analysis | |||
|---|---|---|---|---|---|
| N (%) | OR (95% CI) | P-value | aOR (95% CI) | P-value | |
| No | 2427 (96.2) | ||||
| Yes | 87 (3.5) | ||||
| Missing | 8 | ||||
| No | 465 (18.5) | Ref | |||
| Yes | 2053 (81.5) | 0.71 (0.43–1.17) | 0.172 | 0.51 (0.30–0.87) | 0.013 |
| Missing | 4 | ||||
| ≤ 24 | 272 (10.8) | Ref | |||
| 25–29 | 351 (13.9) | 1.94 (0.37–10.06) | 0.432 | 2.09 (0.40–10.86) | 0.383 |
| 30–34 | 427 (16.9) | 4.56 (1.03–20.24) | 0.046 | 5.50 (1.23–24.52) | 0.025 |
| 35–39 | 416 (16.5) | 4.00 (0.89–18.01) | 0.071 | 4.85 (1.07–21.99) | 0.041 |
| 40–44 | 373 (14.8) | 5.24 (1.18–23.25) | 0.029 | 6.38 (1.43–28.52) | 0.015 |
| 45–49 | 298 (11.8) | 4.67 (1.01–21.5) | 0.048 | 5.52 (1.19–25.70) | 0.029 |
| 50–54 | 203 (8.1) | 6.94 (1.5–32.05) | 0.013 | 7.97 (1.70–37.30) | 0.008 |
| ≥ 55 | 180 (7.1) | 16.75 (3.86–72.61) | <0.001 | 19.28 (4.37–85.11) | <0.001 |
| Missing | 2 | ||||
| Low income countries | 348 (13.8) | Ref | Ref | ||
| Lower-middle income countries | 1332 (52.8) | 1.81 (0.76–4.30) | 0.179 | 1.61 (0.67–3.86) | 0.288 |
| Upper-middle income countries | 442 (17.5) | 1.59 (0.59–4.29) | 0.356 | 1.28 (0.47–3.48) | 0.627 |
| High income countries | 400 (15.9) | 4.30 (1.76–10.51) | 0.001 | 3.39 (1.36–8.41) | 0.009 |
All four specimens were equivocal.
Five specimens were equivocal and three specimens had insufficient sera for confirmatory testing.
As Per the World Bank classification (World Bank, 2017): low income countries include Syria and Yemen; lower-middle income countries include Egypt, India, Pakistan, Palestine, Philippines, and Sudan; upper-middle income countries include Iran, Iraq, Jordan, and Lebanon; high-income countries include Qatar.