Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1]–[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). Under simple epidemiological scenarios, in which all infected individuals behave identically, R0depends on the transmission probability per contact with a susceptible individual, the duration of infectiousness and the rate at which new contacts are made.

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions. 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

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions. 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

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1]–[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). Under simple epidemiological scenarios, in which all infected individuals behave identically, R0depends on the transmission probability per contact with a susceptible individual, the duration of infectiousness and the rate at which new contacts are made.