In this session, we will discuss different measures of timescale of disease transmission. Transmissibility measures, such as reproductive number, describe the number of people infected by an infected person without giving information on how long it takes for these infections to occur. Obviously, the faster the pathogen can transmit from one person to another, the faster it can spread in the population. Generation time provides the information about the timescale of disease transmission. It is defined as the time between successive infections in a chain of transmission. However, for many infectious diseases, the infection event is difficult or impossible to observe directly or recall accurately. For example, for a person infected by influenza via droplet or airborne transmission, it is practically impossible to tell precisely at which time point the virus has successfully invaded and started an infection within the host. In contrast to the time of infection, onset of symptoms is much more readily observable and recallable. As such, serial interval, defined as the time between symptoms onset of successive cases, are often used as the measure for the timescale of disease transmission, instead, in practice. The 2009 pandemic H1N1 influenza has a serial interval of around 2.5 days. The serial interval for seasonal influenza is around 3.5 days. SARS has a serial interval of around eight days, while measles has a serial interval of around 12 days. The timescale of person-to-person disease transmission, as measured by generation time or serial interval, is an important determinant for the success of quarantine and isolation, which aim to reduce disease transmission by preventing confirmed or probable cases from mixing with the rest of the population. Shorter generation time or serial interval means that confirmed and probable cases would need to be identified and removed from the population sooner in order to prevent them from spreading disease. For example, SARS has an R0 of two to three, and a serial interval of around eight days while influenza has an R0 less than two and a serial interval of around two to three days. The longer serial interval of SARS is one of the reasons why quarantine and isolation are much more effective for controlling the spread of SARS than influenza, even though SARS is more transmissible. Another important determinant of disease transmission is how long it takes for a person to become infectious after he has been infected. Infected individuals typically do not become infectious immediately after infection. This time interval between infection and onset of infectiousness is called the latent period. Infected individuals can become infectious before or after the onset of symptoms, which means that the latent period can be longer or shorter than the incubation period. For example, people infected with SARS become infectious only after they have developed the symptoms, whereas for influenza, a substantial proportion of transmission occurred before the infected people become symptomatic. As a consequence, while isolation of cases and quarantine of case contacts were effective for reducing the transmission of SARS in 2003, the same strategy would be much less effective in reducing the transmission of influenza because by the time an influenza case is identified due to symptoms onset, isolating him at that point would reduce only a small proportion of the overall transmission that he would have caused otherwise. Transmissibility of the pathogen and the timescale of person-to-person transmission together determine the timescale of the epidemic. This timescale is described by either the epidemic growth rate, which is the rate at which the number of cases increases during the exponential growth phase, or the epidemic doubling time, which is the time it takes for the incidence to double. By their definitions, epidemic doubling time is simply log of two divided by the epidemic growth rate. If we know the generation time distribution, for example, using the serial interval data from outbreak investigation, we can estimate the reproductive number from the growth rate observed in the epi curve. For example, if the generation time distribution looks like an exponential distribution, then the reproductive number is equal to one plus the product of the epidemic growth rate and the mean generation time. For another example, if the generation time distribution has a very small coefficient of variation, which is defined as the standard deviation divided by the mean, then the reproductive number is equal to the exponential of the product of the epidemic growth rate and the mean generation time. To summarize, in this session we have discussed different measures of timescale of disease transmission.