Understanding and monitoring the evolution of the Covid-19 epidemic from medical emergency calls: the example of the Paris area

Stéphane Gaubert,Érick Chanzy,Théotime Grohens,Marianne Akian,Laurent Goix,David P Parsons,Thomas Loeb,Christophe Leroy,Xavier Allamigeon,Marin Boyet,Pierre Carli,Caroline Télion,Frédéric Adnet,Laurent Massoulié,Éric Lecarpentier,Laurent Tréluyer,Frédéric Lapostolle,Jean-Sébastien Marx,Baptiste Colin

doi:10.5802/crmath.99

Stéphane Gaubert, Érick Chanzy + Show 17 more

Open Access

https://doi.org/10.5802/crmath.99

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Abstract

We portray the evolution of the Covid-19 epidemic during the crisis of March–April 2020 in the Paris area, by analyzing the medical emergency calls received by the EMS of the four central departments of this area (Centre 15 of SAMU 75, 92, 93 and 94). Our study reveals strong dissimilarities between these departments. We show that the logarithm of each epidemic observable can be approximated by a piecewise linear function of time. This allows us to distinguish the different phases of the epidemic, and to identify the delay between sanitary measures and their influence on the load of EMS. This also leads to an algorithm, allowing one to detect epidemic resurgences. We rely on a transport PDE epidemiological model, and we use methods from Perron–Frobenius theory and tropical geometry.

Highlights

The outbreak of Covid-19 in France has put the national Emergency Medical System (EMS), the SAMU, in the front line
These mechanisms rely on simple data generally available in EMS: numbers of patient records tagged as Covid-19, and among these, numbers of records resulting in medical advice, ambulance dispatch, or Mobile Intensive Care Unit dispatch
In order to develop a mathematical analysis of the evolution of the epidemic, we classified the calls tagged as Covid-19 in three categories, according to the decision taken: Class 1: calls resulting in the dispatch of a Mobile Intensive Care Unit; Class 2: calls resulting in the dispatch of an ambulance staffed with EMT; Class 3: calls resulting in no dispatch decision

Summary

Introduction

The outbreak of Covid-19 in France has put the national Emergency Medical System (EMS), the SAMU, in the front line. We provide a method of short term prediction of the evolution of the epidemic, based on mathematical modeling This leads to early detection and early alarm mechanisms allowing one either to confirm that certain sanitary measures are strong enough to contain the epidemic, or to detect its resurgence. These mechanisms rely on simple data generally available in EMS: numbers of patient records tagged as Covid-19, and among these, numbers of records resulting in medical advice, ambulance dispatch, or Mobile Intensive Care Unit dispatch.

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