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. 2010 Aug 17;107(33):14757-62.
doi: 10.1073/pnas.1008877107. Epub 2010 Aug 9.

Evidence of intense ongoing endemic transmission of hepatitis C virus in Egypt

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Evidence of intense ongoing endemic transmission of hepatitis C virus in Egypt

F DeWolfe Miller et al. Proc Natl Acad Sci U S A. .

Abstract

Egypt has the highest prevalence of antibodies to hepatitis C virus (HCV) in the world, estimated nationally at 14.7%. An estimated 9.8% are chronically infected. Numerous HCV prevalence studies in Egypt have published various estimates from different Egyptian communities, suggesting that Egypt, relative to the other nations of the world, might be experiencing intense ongoing HCV transmission. More importantly, a new national study provided an opportunity to apply established epidemiologic models to estimate incidence. Validated mathematical models for estimating incidence from age-specific prevalence were used. All previous prevalence studies of HCV in Egypt were reviewed and used to estimate incidence provided that there was sufficient age-specific data required by the models. All reports of anti-HCV antibody prevalence were much higher than any single other national estimate. Age was the strongest and most consistently associated factor to HCV prevalence and HCV RNA positivity. It was not possible to establish a prior reference point for HCV prevalence or incidence to compare with the 2009 incidence estimates. The modeled incidence from the national study and collectively from the modeled incidence from the previous community studies was 6.9/1,000 [95% confidence interval (CI), 5.5-7.4] per person per year and 6.6/1,000 (95% CI, 5.1-7.0) per person per year, respectively. Projected to the age structure of the Egyptian population, more than 500,000 new HCV infections per year were estimated. Iatrogenic transmission is the most likely, underlining exposure to the ongoing transmission. The study demonstrates the urgency to reduce HCV transmission in Egypt.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Publication search results for HCV epidemiologic studies in Egypt. Journal articles were screened for hepatitis C in Egypt, from which those that suggested clinical, treatment-related, or laboratory-based studies were excluded. Additional criteria for selection that were used included (i) reported HCV prevalence or incidence, (ii) described the serologic methods, (iii) were of cross-sectional or prospective epidemiologic design, and (iv) could be abstracted for the purposes of this study.
Fig. 2.
Fig. 2.
Prevalence for anti-HCV antibody by age in 17,286 first-time healthy blood donors in 1992 by age (20). Logistic regression (solid line) demonstrates a monotonic increase of prevalence with age. Prevalence in ages 50 y and older had fewer data, causing statistical instability. Logistic regression: χ2 = 571.96, SE = 0.0025, df = 1, P = 0.000, r2 = 0.81, and 1/e(– α – β x), where α = −3.8063 and β = 0.0627.
Fig. 3.
Fig. 3.
Prevalence of anti-HCV antibody positive and the prevalence of HCV RNA positive by 5-y age groups from the EDHS national sample (26). This graph was prepared from data abstracted from the EDHS national sample (26). The line was fitted by logistic regression for anti-HCV antibody prevalence. Logistic regression: χ2 = 1177.97, df = 1, SE = 0.0024, P = 0.000, r2 = 0.96, and 1/e(– α – β x), where α = −4.4 β = 0.0758.
Fig. 4.
Fig. 4.
Relationship between estimated incidence and overall HCV prevalence from six community cross-sectional studies (–49). The age-specific prevalence was abstracted from each of six cross-sectional reports. Prevalence from the EDHS (26) was also included as a seventh observation. In turn, these data were used as described in Methods to generate an estimate of report-specific incidence, which can be seen in Table 2. Report-specific prevalence and incidence points were plotted on a linear x-y graph with percentage prevalence on the x axis and incidence per 1,000 per year on the y axis. Linear regression: α + βx, where α = 1.23 and β = 0.363, r2 = 0.85 was the best fit and demonstrates an internal validation of the model used to generate a national incidence estimate.

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