Each week, we will be publishing layman’s abstracts of new articles from our prestigious portfolio of journals in statistics. The aim is to highlight the latest research to a broader audience in an accessible format.

The article featured today is from Statistics in Medicine, with the full article now published in Volume 40, Issue 4 and available to read here.

Veres‐Ferrer, EJ, Pavía, JM. Elasticity as a measure for online determination of remission points in ongoing epidemics. Statistics in Medicine. 2021; 40: 865–884. https://doi.org/10.1002/sim.8807

The correct identification of change-points during ongoing outbreak investigations of infectious diseases is a matter of paramount importance in epidemiology, with major implications for the management of healthcare resources, public health and, as the COVID-19 pandemic has shown, social and economic wellbeing. Onsets, peaks and inflexion points are not the only relevant change-points: the proper identification of remission points is also of paramount importance. The onset is the moment when the epidemic starts, a peak indicates a moment of maximum incidence and a remission coincides with the instant when the outbreak starts to decline in a robust and consistent way. A proper identification of the remission of an epidemic is important because this is the moment when a gradual relaxation of the strict control measures taken by the health authorities can be safely initiated and, as the ongoing COVID-19 pandemic is showing, this can strongly affect the social and economic wellbeing of a country.

In those societies affected by COVID-19, public opinion has insisted on the need to establish a proper balance between the restrictive measures adopted and the effective control of the epidemic, in order to safeguard the economy. This has involved frequent dialectical confrontations between governments and economic social forces, with people demanding simple information tools to be able to reach an informed opinion.

The concept of elasticity has its origin in physics, was quickly adopted by economists, and has recently been extended to areas as diverse as theoretical probability, survival models or risk management. The authors of “Elasticity as a measure for online determination of remission points in ongoing epidemics” find another application for the concept, in epidemiology, as a tool for identifying points of remission of epidemics. They re-interpret its mathematical meaning as an indicator of the speed of accumulation of new cases of a contagious disease.

With this innovative interpretation, the authors identify remission points as the moments when the speed of accumulation of new cases is significantly lower than the average speed of accumulation of cases up to that moment. The measure proposed in the research paper is essentially descriptive, very easy to compute and does not require any prior formulation of hypotheses about the behaviour or the pattern followed by the pandemic. Moreover, it can even be estimated in real time while the data is being collected. These advantages, given the simplicity of the elasticity formulation, are substantial for its use in the event of epidemic outbreaks, providing rapid and robust information that can be very useful for decision makers.