Mathematical modeling of hepatitis C virus transmission in hemodialysis.

BACKGROUND: A deterministic mathematical model is developed to explain nontransfusion nosocomial transmission of hepatitis C virus (HCV) from patient to patient during hemodialysis sessions. METHODS: The model requires 4 sequential steps for cross-transmission: (1) The dialysis session contains at least 1 patient infected with HCV; (2) a hemodialysis staff member connects an uninfected patient to dialysis after having connected an infected patient; (3) the hemodialysis staff member does not change gloves between an infected patient and an uninfected patient; and (4) the uninfected patient is contaminated after exposure to the blood of an infected patient. RESULTS: We tested the model by comparing observed incidences of HCV infection from epidemiologic studies with calculated incidences. Calculated incidences are closed to observed incidences. We assessed the impact of prevalence of HCV infection, no glove change between patients, and nurse:patient ratio on the incidence of HCV infection. We found linear relationships between incidence and prevalence and between incidence and no glove change, and an increasing logarithmic relationship between incidence and nurse:patient ratio. CONCLUSION: Our model should be able to estimate the likely incidence of infection in hemodialysis centers. Compliance with recommended hand hygiene and glove use practices, especially glove changes between patients, is essential to prevent HCV infection in hemodialysis centers, particularly those with high HCV prevalence. Mathematical modeling can used as a tool for control.

Hepatitis C virus infection among dialysis patients in Tunisia: incidence and molecular evidence for nosocomial transmission.

In order to study the incidence of hepatitis C virus (HCV) infection in Tunisian haemodialysis patients and detect its nosocomial transmission, 395 patients were enrolled in a prospective study (November 2001-2003). HCV serological and virological status was determined initially using, respectively a third generation ELISA and an RT-PCR qualitative assay. The genotype of the HCV isolates was determined by sequencing NS5B region. The issue of nosocomial transmission was addressed by sequencing the HVR-1 region of the E2 gene. About 20% of the patients had anti-HCV antibodies and HCV-RNA was detected in 73% of the anti-HCV positive patients. Two cases of de novo HCV infection were identified in two dialysis centers, during virological follow-up of patients susceptible to HCV infection. The incidence of de novo HCV infection was 0.5%. Determining the genotypes in the first center disclosed that all HCV-positive patients were infected with genotype 1b; sequencing of the HVR-1 region of the E2 gene provided strong evidence that the isolate from the newly infected patient and another infected dialysis patient were closely related, confirming nosocomial contamination. The investigation of the second center is pending. Besides, one patient with negative HCV serology had detectable HCV-RNA at the beginning of the study. This case had HCV genotype 1b, two other infected dialysis patients in the same unit had HCV genotypes 4k and 3a; thus precluding nosocomial transmission. Thanks to molecular and phylogenetic methods, one case of nosocomial HCV transmission in haemodialysis was confirmed. Epidemiological investigation suggested nosocomial transmission via the medical and/or nursing staff.