Non Pharmaceutical Interventions ‘NPIs’, Hospital Overload and Excess Mortality: Statistical Analysis and Mathematical Study of the NPIs Results in ‘COVID 19’ Outbreak

25 Pages Posted: 18 May 2020 Last revised: 4 Jun 2020

See all articles by Gilles Pech de Laclause

Gilles Pech de Laclause

Independent

Arnaud Delenda

University of Rennes 1

Lana Augustincic

University of Zagreb, School of medicine

Date Written: May 10, 2020

Abstract

This study observes the results of epidemic spread and mortality in three comparable countries in demographics and GDP, also affected by the spread of SARS COV-2 and COVID-19 disease: Belgium, the Netherlands and Sweden. These three countries have taken three levels of non-pharmaceutical interventions (NPI within the meaning of WHO) from hard to soft. They have three different health systems, from the most equipped to the least equipped. And their results are significantly different.

Predictive scenarios with a SEIR model for Belgium and Sweden do not verify hypothesis that an epidemiological model could predict a hospital load and mortality, neither in Belgium nor in Sweden. On the contrary, Lock down (Belgium) or Shut down (Netherlands), does not "delay" the peak of new cases or the peak of mortality, it makes it happen sooner, and does not "flatten" the curve of new cases, nor the mortality curve, it "swells" it.

The hypothesis that NPIs have a direct impact on the R indicator of epidemic spread is not demonstrated in mathematics. NPIs have a direct impact on the contact rate per period, which is one of the R calculation parameters.

Assumptions in which epidemiological models are used to select the R value generating a hospital load compatible with the capacity of the health system are not true. These assumptions take the models upside down: the “R” indicator becomes the parameter with which one "plays" to deduce an NPI at the moment t. Models are no longer relevant to this use.

We assume that changing the contact rate by NPI also requires changes in proportion to other parameters, such as the recovery rate, creating perverse effects. In the case of the strictest NPIs, where the contact rate is asymptote, we assume an overload of hospital capacity and excess mortality.

Note:

Funding: No funding was required or provided for this research.

Declaration of Interest: The authors have no conflict of interests to declare.

Keywords: COVID 19, coronavirus, Statistics, Mathematics, Epidemiology, NPIs, lock down

Suggested Citation

Pech de Laclause, Gilles and Delenda, Arnaud and Augustincic, Lana, Non Pharmaceutical Interventions ‘NPIs’, Hospital Overload and Excess Mortality: Statistical Analysis and Mathematical Study of the NPIs Results in ‘COVID 19’ Outbreak (May 10, 2020). Available at SSRN: https://ssrn.com/abstract=3598484 or http://dx.doi.org/10.2139/ssrn.3598484

Gilles Pech de Laclause (Contact Author)

Independent ( email )

No Address Available
Sweden

Arnaud Delenda

University of Rennes 1 ( email )

7 place Hoche
Rennes, 35065
France

Lana Augustincic

University of Zagreb, School of medicine

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