Basil Grammaticos
Publications:
Nakamura G., Grammaticos B., Badoual M.
Recruitment Effects on the Evolution of Epidemics in a Simple SIR Model
2021, vol. 26, no. 3, pp. 305-319
Abstract
We analyse the patterns of the current epidemic evolution in various countries with
the help of a simple SIR model. We consider two main effects: climate induced seasonality and
recruitment. The latter is introduced as a way to palliate for the absence of a spatial component
in the SIR model. In our approach we mimic the spatial evolution of the epidemic through a
gradual introduction of susceptible individuals.
We apply our model to the case of France and Australia and explain the appearance of two
temporally well-separated epidemic waves. We examine also Brazil and the USA, which present
patterns very different from those of the European countries. We show that with our model it is
possible to reproduce the observed patterns in these two countries thanks to simple recruitment
assumptions. Finally, in order to show the power of the recruitment approach, we simulate the
case of the 1918 influenza epidemic reproducing successfully the, by now famous, three epidemic
peaks.
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Nakamura G., Grammaticos B., Badoual M.
Confinement Strategies in a Simple SIR Model
2020, vol. 25, no. 6, pp. 509-521
Abstract
We propose a simple deterministic, differential equation-based, SIR model in order
to investigate the impact of various confinement strategies on a most virulent epidemic. Our
approach is motivated by the current COVID-19 pandemic. The main hypothesis is the existence
of two populations of susceptible persons, one which obeys confinement and for which the
infection rate does not exceed 1, and a population which, being non confined for various
imperatives, can be substantially more infective. The model, initially formulated as a differential
system, is discretised following a specific procedure, the discrete system serving as an integrator
for the differential one. Our model is calibrated so as to correspond to what is observed in the
COVID-19 epidemic, for the period from February 19 to April 16.
Several conclusions can be reached, despite the very simple structure of our model. First, it
is not possible to pinpoint the genesis of the epidemic by just analysing data from when the
epidemic is in full swing. It may well turn out that the epidemic has reached a sizeable part of
the world months before it became noticeable. Concerning the confinement scenarios, a universal
feature of all our simulations is that relaxing the lockdown constraints leads to a rekindling of
the epidemic. Thus, we sought the conditions for the second epidemic peak to be lower than
the first one. This is possible in all the scenarios considered (abrupt or gradualexit, the latter
having linear and stepwise profiles), but typically a gradual exit can start earlier than an
abrupt one. However, by the time the gradual exit is complete, the overall confinement times
are not too different. From our results, the most promising strategy is that of a stepwise exit.
Its implementation could be quite feasible, with the major part of the population (perhaps,
minus the fragile groups) exiting simultaneously, but obeying rigorous distancing constraints.
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