The Epidemic Behavior of the Hepatitis C Virus

Abstract

Hepatitis C virus (HCV) is a leading worldwide cause of liver disease. Here, we use a new model of HCV spread to investigate the epidemic behavior of the virus and to estimate its basic reproductive number from gene sequence data. We find significant differences in epidemic behavior among HCV subtypes and suggest that these differences are largely the result of subtype-specific transmission patterns. Our model builds a bridge between the disciplines of population genetics and mathematical epidemiology by using pathogen gene sequences to infer the population dynamic history of an infectious disease.An estimated 170 million people worldwide are at risk of liver cirrhosis and liver cancer due to chronic infection with HCV (1). The virus is responsible for 10,000 deaths per year in the United States, and this rate is expected to increase substantially in the next two decades (2). HCV is a rapidly evolving single-stranded positivesense RNA virus that exhibits enormous genetic diversity. It is classified into six types (labeled 1 through 6) and numerous subtypes (labeled 1a, 1b, etc.), which differ in diversity, geographical distribution, and transmission route (3). Subtypes appear to differ in treatment response, although their role in variation of disease progression is unclear (2, 4 ). Any successful HCV vaccination or control strategy, therefore, requires an understanding of the nature and variability of epidemic behavior among subtypes.HCV was first isolated in 1989, and knowledge of its long-term epidemiology before that date is limited. Highly divergent strains have been found in restricted geographic areas such as West Africa and Southeast Asia, suggesting a long period of infection in these regions. In contrast, several globally prevalent subtypes are much less divergent, indicating a recent worldwide spread of these strains (5-7).We investigate HCV epidemiology using coalescent theory, a population genetic model that describes how the demographic history of a population determines the ancestral relationships of individuals sampled from it (8, 9). Phylogenies reconstructed from contemporary HCV gene sequences contain information about past population dynamics and can, therefore, be used to infer viral epidemic behavior (10). We also demonstrate one way in which the fundamental epidemiological quantity R 0 (the basic reproductive number of a pathogen) can be estimated from gene sequences. R 0 represents the average number of secondary infections generated by one primary case in a susceptible population and can be used to estimate the level of immunization or behavioral change required to control an epidemic (11).The framework of coalescent theory allows us to estimate N(t), a continuous function that represents the effective number of infections at time t. Time t is zero at the present and increases into the past, hence N(0) is the effective number of infections at the present. N(t) can be considered as the inbreeding effective population size of the viral epidemic (12). Previous viral coalescent studies have ...

The Evolutionary and Epidemiological Dynamics of the Paramyxoviridae

“…4b). Strikingly, in all the viruses studied here our estimates of genetic diversity, measured as N e τ, are between 10 and 100 and, hence, considerably lower than those previously recorded in chronic infections such as HIV (Robbins et al 2003) and hepatitis C (Pybus et al 2001). Such consistently low levels of genetic diversity suggest that recurrent population bottlenecks, a characteristic of paramyxovirus population dynamics, are regularly purging, and hence limiting, genetic variation.…”

Tracing the history of hepatitis B virus genotype D in western Japan

“…Such a significant cluster is suitable for a coalescent analysis. The specific demographic model based on the neutral theory [Pybus et al, 2001Lemey et al, 2003], which has a constant size in the past and changes to exponential growth until the present, was applied for investigating the Japanese endemic of HBV/D in Ehime. Several historical factors in Japan have probably affected the spread of HBV/D, such as an increase of intravenous drug abuse in the 1940s during and after World War II, and the increase of blood transfusion procedures and the use of non-sterilized medical materials in the 1960s and 1970s.…”

“…For estimates of demographic history, a non-parametric function N(t), also known as a skyline plot, was obtained by transforming the coalescent intervals of an observed genealogy into a piecewise plot that represented an effective population size through time [Pybus et al, 2001;Pybus and Rambaut, 2002]. A parametric ML was estimated by several models with the computer software Genie v3.0 to build a statistical framework for inferring the demographic history of a population on phylogenies reconstructed from sampled DNA sequences [Pybus and Rambaut, 2002].…”

Phylogeographic Patterns of mtDNA Variation Revealed Multiple Glacial Refugia for the Frog Species Feirana taihangnica Endemic to the Qinling Mountains

“…Demographic analyses, even the coalescent-based method BSP, which incorporates information from the genealogy and may achieve better estimates of the demographic history, could only detect recent expansions (Table 4; Figs. 4,5) and are unable to uncover the bottlenecks in the earlier coalescent time (Jesus et al 2006;Pybus et al 2001;Heled and Drummond 2010). Thus, we cautiously make demographic inferences and are striving to develop an extension of this study using multiple loci and adequate sampling to reconstruct a credible genealogy (Heled and Drummond 2010).…”