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In preparation for the National Hepatitis C Elimination Program in the country of Georgia, a nationwide household-based hepatitis C virus (HCV) seroprevalence survey was conducted in 2015. Data were used to estimate HCV genotype distribution and better understand potential sex-specific risk factors that contribute to HCV transmission. HCV genotype distribution by sex and reported risk factors were calculated. We used explanatory logistic regression models stratified by sex to identify behavioral and healthcare-related risk factors for HCV seropositivity, and predictive logistic regression models to identify additional variables that could help predict the presence of infection. Factors associated with HCV seropositivity in explanatory models included, among males, history of injection drug use (IDU) (aOR = 22.4, 95% CI = 12.7, 39.8) and receiving a blood transfusion (aOR = 3.6, 95% CI = 1.4, 8.8), and among females, history of receiving a blood transfusion (aOR = 4.0, 95% CI 2.1, 7.7), kidney dialysis (aOR = 7.3 95% CI 1.5, 35.3) and surgery (aOR = 1.9, 95% CI 1.1, 3.2). The male-specific predictive model additionally identified age, urban residence, and history of incarceration as factors predictive of seropositivity and were used to create a male-specific exposure index (Area under the curve [AUC] = 0.84). The female-specific predictive model had insufficient discriminatory performance to support creating an exposure index (AUC = 0.61). The most prevalent HCV genotype (GT) nationally was GT1b (40.5%), followed by GT3 (34.7%) and GT2 (23.6%). Risk factors for HCV seropositivity and distribution of HCV genotypes in Georgia vary substantially by sex. The HCV exposure index developed for males could be used to inform targeted testing programs.

In preparation for the National Hepatitis C Elimination Program in the country of Georgia, a nationwide household-based hepatitis C virus (HCV) seroprevalence survey was conducted in 2015. Data were used to estimate HCV genotype distribution and better understand potential sex-specific risk factors that contribute to HCV transmission. HCV genotype distribution by sex and reported risk factors were calculated. We used explanatory logistic regression models stratified by sex to identify behavioral and healthcare-related risk factors for HCV seropositivity, and predictive logistic regression models to identify additional variables that could help predict the presence of infection. Factors associated with HCV seropositivity in explanatory models included, among males, history of injection drug use (IDU) (aOR = 22.4, 95% CI = 12.7, 39.8) and receiving a blood transfusion (aOR = 3.6, 95% CI = 1.4, 8.8), and among females, history of receiving a blood transfusion (aOR = 4.0, 95% CI 2.1, 7.7), kidney dialysis (aOR = 7.3 95% CI 1.5, 35.3) and surgery (aOR = 1.9, 95% CI 1.1, 3.2). The male-specific predictive model additionally identified age, urban residence, and history of incarceration as factors predictive of seropositivity and were used to create a male-specific exposure index (Area under the curve [AUC] = 0.84). The female-specific predictive model had insufficient discriminatory performance to support creating an exposure index (AUC = 0.61). The most prevalent HCV genotype (GT) nationally was GT1b (40.5%), followed by GT3 (34.7%) and GT2 (23.6%). Risk factors for HCV seropositivity and distribution of HCV genotypes in Georgia vary substantially by sex. The HCV exposure index developed for males could be used to inform targeted testing programs.