Abstract
The epidemiology of chronic viral infections, such as those caused by Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV), is affected by the risk group structure of the infected population. Risk groups are defined by each of their members having acquired infection through a specific behavior. However, risk group definitions say little about the transmission potential of each infected individual. Variation in the number of secondary infections is extremely difficult to estimate for HCV and HIV but crucial in the design of efficient control interventions. Here we describe a novel method that combines epidemiological and population genetic approaches to estimate the variation in transmissibility of rapidly-evolving viral epidemics. We evaluate this method using a nationwide HCV epidemic and for the first time co-estimate viral generation times and superspreading events from a combination of molecular and epidemiological data. We anticipate that this integrated approach will form the basis of powerful tools for describing the transmission dynamics of chronic viral diseases, and for evaluating control strategies directed against them.
Highlights
Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1,2,3]
Studies on sexually transmitted and vector-borne infections indicate that infected individuals behave far from identically and that variation in the number of secondary infections per infected individual can play a major role in epidemic dynamics
We have shown that phylodynamic methods can be combined with epidemiological surveillance data to estimate the variability in ongoing transmission of a chronic viral epidemic, and to investigate its generation time
Summary
Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1,2,3]. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population [4] (for notations see Table 1). In which all infected individuals behave identically, R0 depends on the transmission probability per contact with a susceptible individual, the duration of infectiousness and the rate at which new contacts are made [2,4,5]. The term ‘superspreaders’ has been coined to describe hosts that contribute disproportionately to onward infection
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