Open AccessCovid-19: predictive mathematical formulae for the number of deaths during lockdown and possible scenarios for the post-lockdown period
Author(s) -
A. S. Fokas,
Νικόλαος Δικαίος,
George A. Kastis
Publication year - 2021
Publication title -
proceedings - royal society. mathematical, physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2946
pISSN - 1364-5021
DOI - 10.1098/rspa.2020.0745
Subject(s) - covid-19 , period (music) , statistics , mathematics , medicine , virology , physics , infectious disease (medical specialty) , disease , pathology , outbreak , acoustics
In a recent article, we introduced two novel mathematical expressions and a deep learning algorithm for characterizing the dynamics of the number of reported infected cases with SARS-CoV-2. Here, we show that such formulae can also be used for determining the time evolution of the associated number of deaths: for the epidemics in Spain, Germany, Italy and the UK, the parameters defining these formulae were computed using data up to 1 May 2020, a period of lockdown for these countries; then, the predictions of the formulae were compared with the data for the following 122 days, namely until 1 September. These comparisons, in addition to demonstrating the remarkable predictive capacity of our simple formulae, also show that for a rather long time the easing of the lockdown measures did not affect the number of deaths. The importance of these results regarding predictions of the number of Covid-19 deaths during the post-lockdown period is discussed.