In this work we made use of a stochastic SEIR%DIFDELCMD < {\em %%%  Susceptible-Exposed-Infectious-Recovered model and adapted it conveniently to describe the propagation of COVID-19 during a football tournament. Specifically, we were concerned about the re-start of the Spanish national football league (%DIFDELCMD < {\it %%% "La Liga" ) , which is currently  stopped with 11 fixtures remaining. Our model included two additional states of an individual, namely, confined and quarantined, which can be reached when an individual  has undergone a COVID-19 test with a positive result. The model also accounted for the interaction dynamics of players, considering three different sources of infection: (i) the player social circle, (ii) the interaction with his/her team colleagues during training sessions and (iii) the interaction with rivals during a match. First, we investigated how the time between matchesinfluences the number of players that may be infected at the end of the season. Second, we simulated the effects of increasing the frequency of tests, whose sensitivity was also analyzed. Finally, we discussed different strategies to minimize the probability that COVID-19 propagates in case the season of "La Liga " were re-started after the current lockdown.
In this work %DIFDELCMD < {\em %%% , we present a stochastic discrete-time SEIR ( Susceptible-Exposed-Infectious-Recovered ) model adapted to describe the propagation of COVID-19 during a football tournament. Specifically, we are concerned about the re-start of the Spanish national football league %DIFDELCMD < {\it %%% , La Liga , which is currently -May 2020- stopped with 11 fixtures remaining. Our model includes two additional states of an individual, confined and quarantined, which are reached when an individual presents COVID-19 symptoms or has undergone a virus test with a positive result. The model also accounts for the interaction dynamics of players, considering three different sources of infection: the player social circle, the contact with his/her team colleagues during training sessions , and the interaction with rivals during a match. Our results highlight the influence of the days between matches, the frequency of virus tests and their sensitivity on the number of players infected at the end of the season. Following our findings, we finally present a variety of strategies to minimize the probability that COVID-19 propagates in case the season of La Liga was re-started after the current lockdown.
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