The mechanism behind a cause usually has several components. These can be subdivided into two categories: necessary and sufficient components [1]. Let us take the example of an infectious disease, invasive meningococcal disease. We say it is caused by Neisseria meningitidis (difficult to argue against, as this organism by definition must be present). So it is a "necessary" component of cause.

On the other hand, infection with Neisseria meningitidis does not always result in meningococcal disease. Indeed illness is a rare outcome of the infection. The infection by itself is not "sufficient" and other factors need to be present. Lack of antibodies against this infection, the breakdown of the mucosal barriers by respiratory infection, low humidity, and passive smoking may be other causal factors. 


  • several components are needed to produce a given outcome,
  • any one component is not sufficient on its own,
  • different combinations of components can produce the same outcome

These concepts of necessary and sufficient component causes explain the apparent anomaly whereby attributable fractions in a population (AFpops) can add up to more than 100%. The AFpop for Neisseria meningitidis is 100%. If Neisseria meningitidis were to be eliminated as a coloniser of the human pharynx, there would be no more meningococcal disease. The AFpop for low immunity is probably also close to 100%. This means that vaccination may be highly effective at reducing disease rates even without reducing colonisation.

Various conceptual models aiming to simplify the representation of causal mechanisms have been developed in epidemiology. A well known model is that of infectious disease causation (the agent, host, environment pyramid). Another widely adopted model for chronic disease causation is Rothman’s “sufficient component cause model” whereby the cause of any effect must consist of a constellation of components that act in concert [2].


 1.Rothman KR. Epidemiology: an introduction. Oxford University Press, Oxford 2002.

2. Rothman K, Greenland S. Causation and causal inference in epidemiology. Am J Public Health. 2005;95:S144–S150.