Epidemiology

Epidemiology may sound like it is the study of epidemics, which it is, but it is also much more than that. It is defined as the study of health in populations – which means understanding the causes, numbers, distribution, control and prevention of disease, both infectious (like covid-19) and non-infectious (such as cancer). It is not concerned with individual health but the health of whole populations. It also covers non-human animals and plants.

Epidemiology can trace its origins back to a cholera outbreak in London in 1854. At the time the disease was widely believed to be caused by bad air, but a doctor called John Snow begged to differ. He thought it was carried by an infectious agent in drinking water. During the outbreak he kept track of all the households with cases and recorded where they had obtained their water, allowing him to pinpoint the source as a pump on Broad Street in Soho.

Modern epidemiology is the science of public health. It is split into two complementary sub-disciplines. Descriptive epidemiologists gather basic data about a health condition – who has it, how many cases there are, where they are and how the disease develops over time. This feeds into analytic epidemiology, which builds and tests models of the cause of the disease, how it spreads and how it might ultimately be controlled or stamped out. Both approaches are highly relevant to understanding and managing coronavirus. The early research was descriptive, to gain a basic understanding of the epidemic, such is who is vulnerable; that quickly fed into analytical phase which established the cause (a novel virus) and set about discovering how to control its spread. The much-repeated terms “flattening the curve” and “herd immunity” both come from epidemiology. The first refers to measures to slow down the spread of the disease, so that public health systems do not become overwhelmed. The second means having high-enough levels of immunity in the population to prevent it from spreading further.

Two key concepts in descriptive epidemiology are incidence and prevalence, which are often muddled up. Incidence is the number of people who catch or develop a disease over a given period of time. Prevalence is how many people in a population have the disease at a defined point in time.

Both can inform another of epidemiology’s goals, which is to establish risk. In simple terms that means the probability of developing the disease; for example, about 40 per cent of people develop cancer during their lifetime. That is absolute risk. There’s also relative risk, which is less intuitive. It means how much more likely you are to develop a disease if you do (or don’t) do something, such as eating a bacon sandwich every day. This raises the relative risk of developing bowel cancer by 20 per cent, which is often misinterpreted as meaning that people who eat bacon sandwiches daily have a 20 per cent chance of developing bowel cancer. They do not: it means they elevate their baseline risk (about 5 per cent) by 20 per cent (i.e. to 6 per cent).

Even though the subject matter of epidemiology is the health of populations rather than individuals, it ultimately informs individual health behaviours. Anyone who decides to take up exercise, give up smoking, eat a better diet or wash their hands after being out and about is making personal use of knowledge generated by epidemiologists.