 In this presentation we introduce Epidemiology through two bite-sized learning outcomes. By the end of the presentation you should be able to describe the definition of Epidemiology, understand how Epidemiology supports public health activities. The word Epidemiology comes from a Greek origin. Epi meaning upon, Demos meaning population and Logos meaning study. So if we put it together this translates to a study of that which is visited upon a population. The definition that we now use is Epidemiology is the study of distribution of health outcomes or disease in a population, determinants that influence the occurrence of disease, and application which provides direction for public health action. The distribution of disease can be shown as the frequency and pattern of occurrence. Frequency can be a number or the rate of risk of disease in a population. The pattern of occurrence can be described by time, for example an annual or a daily occurrence, or by place, for example a rural or an urban location, by characteristics, for example by age, gender, ethnicity, determinants the risk factors or causes of occurrence of disease. These relate to exposure, behavior and genetic risk factors. Application is the public health action that can be taken to improve health within a population. Application is also sometimes referred to as disease control strategies. Epidemiology provides important information about a disease within a population and about what the risk factors are or could be. Health workers use this information to implement control strategies, to prevent disease from occurring or spreading, to provide health system with priorities for planning and targeting health services, or to promote the use of evidence for effective clinical care and policy development. In order to understand epidemiological information you need to be familiar with some commonly used terminology, such as prevalence and incidence. Prevalence is a measure of how many people have a disease or a health state in a given population at a specific time. A good analogy for this is a photograph of the population and knowing how many people in the photograph have a disease. To calculate the prevalence of a disease we need to know two numbers. Firstly, the study population, that is the total number of people in the population we are studying. Then we need to know the number of prevalent cases, that is the number of people with the disease at a specific time. To calculate the prevalence we divide the prevalent cases, the numerator, by the study population, the denominator. We can then multiply by 100 to get a percentage. For example, let us consider a school with 50 children and of those 5 pupils wear spectacles. To calculate the prevalence we divide 5 by 50 and then multiply by 100 to get a percentage. This gives us a prevalence of 10% for spectacle wearing children at this school. Prevalence data allows us to understand and quantify the disease burden and health outcome. Health workers can use this information to allocate resources appropriately. They can also use it to measure the impact of health services by collecting prevalence data before and after a health intervention. For example, how much of a change did providing cataract surgery have on reducing blindness in a given population? Prevalence information can be mapped to show where the need is the greatest. For example, as shown in this trachoma map, the areas where active trachoma is most prevalent will benefit from mass distribution of azithromycin. Incidents refers to the number of individuals in a population who develop a disease over a specific time. This is a measure of risk that the disease will occur. To calculate the incidence of a disease, we need to know two numbers. Firstly, the study population, the total number of people in the population we are studying and then the number of incident cases, that is the number of new cases that will develop the disease during a specific time period. To calculate incidents, we divide the number of new cases, the numerator, by the study population that was followed up over a specified period of time as the denominator. In this example, we see how incidents can help medical professionals predict the probability of a complication developing. In our study population, we have 10,000 insulin-dependent diabetics over the age of 40. They were followed up for a period of six years to see how many developed background retinopathy. 800 new cases are identified in that period of six years. To calculate the risk or incidence of developing retinopathy amongst diabetics in this population, we take the number of new cases, 800, and divide by 10,000 the population being followed up. This gives us a risk of 0.08 or 8 new cases in every 100 diabetics who would develop background changes in their retina in six years. In summary, epidemiology provides the clues for the magnitude, distributions and determinants of diseases affecting a population. Prevalence data is very important for planning public health interventions. Incidence data identifies the probability that a health outcome will occur.