In an epidemic, there is often great concern about the degree to which an infected individual can spread infection to the susceptible individuals in a population. We already know that one way of measuring this is with R-naught, but we can consider using another concept known as the force of infection. We can formally define this as the per capita rate at which susceptible individuals contract infection. Intuitively, the force of infection should increase with the transmissibility of the pathogen and the prevalence of infection in the population. The transmissibility of the pathogen will depend on both characteristics of the pathogen, what is the mechanism of transmission, how prolific is the pathogen within each host, and the characteristics of the population. How many potentially infectious contacts does each individual make in a day? The prevalence of infection, defined as the proportion of the population that is infectious at any given time, gives a measure of the likelihood that any potentially infectious contact is with an infectious individual. Thinking about the force of an infection from the perspective of each susceptible individual offers some new insights into the patterns we expect to see at the scale of the population. In particular, if the force of infection is high then the rate at which individuals come in contact with infection is high and on average, we would expect the interval between infectious contacts to be short. For an immunizing infection, one where getting infected once protects you forever, this would mean that if the force of infection is high we would expect to see infection in younger individuals. On the other hand, if the force of infection is low, either because we're talking about a pathogen with lower inherent transmissibility or a population with a lower rate of contact, then we would expect individuals to be older, on average, by the time they are first exposed to an infection. Given the intuitive relationship between the force of infection and the basic reproductive number from earlier, we would then expect that the higher the basic reproductive number, the earlier on average that individuals would become infected. In fact, one can derive an approximate relationship between the mean age of infection in the population and the basic reproductive number. R-naught equals 1 plus L divided by A where A is the mean age of infection and L is the average life expectancy. This provides a way of estimating the transmissibility of a pathogen, a hard thing to observe directly, from a pattern, the age of first infection that is relatively easy to observe. Here is a survey of the mean age of infection for a variety of pathogens in different places as presented by Andersen and May in 1991. And from this relationship, we can make an approximate estimate of R-naught for each, which indicates differences in R-naught for each pathogen, but also differences for the same pathogen in different places. Of course this simple view has presumed that the force of infection is a constant value for everyone in the population. And intuitively, we may think that not everyone will encounter infection at the same rate. The force of infection is often presumed to be different for individuals of different ages. For example, school children often have very high contact rates within schools compared to adults. Thus we might expect the force of infection to be higher at younger ages. From the patterns we've discussed, we would still expect that the older you are the more likely that it is that you've been infected sometime in the past. But rather than being a function of age alone, this pattern is now expected to be a function of the cumulative force of infection up to your current age. And we can directly measure whether someone has ever been infected by looking for the presence of antibodies to that specific pathogen. Again, while this age specific force of infection might be very difficult to observe directly, the resulting pattern of the proportion of individuals at each age that have antibodies indicating prior exposure is something that can be measured relatively simply by conducting a serological survey. Using calculus, we can back calculate the age specific force of infection from this observed pattern of the proportion of individuals at each age with antibodies indicating prior exposure. These types of observations have been used in the past to highlight which classes of individuals are at the highest risk for infection based on the existing pattern of infection across all individuals. Ultimately, the force of infection provides a way of translating the individual base process of transmission into a population scale pattern of infection that can allow us to quantify properties of pathogens spread in real populations that are otherwise very difficult to see.