Elasticity as a measure for online determination of remission points in ongoing epidemics.

Abstract:

: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 health care resources, public health and, as the COVID-19 pandemic has shown, social live. Onsets, peaks, and inflexion points are some of them. An onset is the moment when the epidemic starts. A "peak" indicates a moment at which the incorporated values, both before and after, are lower: a maximum. The inflexion points identify moments in which the rate of growth of the incorporation of new cases changes intensity. In this study, after interpreting the concept of elasticity of a random variable in an innovative way, we propose using it as a new simpler tool for anticipating epidemic remission change-points. In particular, we propose that the "remission point of change" will occur just at the instant when the speed in the accumulation of new cases is lower than the average speed of accumulation of cases up to that moment. This gives stability and robustness to the estimation in the event of possible remission variations. This descriptive measure, which is very easy to calculate and interpret, is revealed as informative and adequate, has the advantage of being distribution-free and can be estimated in real time, while the data is being collected. We use the 2014-2016 Western Africa Ebola virus epidemic to demonstrate this new approach. A couple of examples analyzing COVID-19 data are also included.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Veres-Ferrer EJ,Pavía JM

doi

10.1002/sim.8807

subject

Has Abstract

pub_date

2021-02-20 00:00:00

pages

865-884

issue

4

eissn

0277-6715

issn

1097-0258

journal_volume

40

pub_type

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