Prediction of the time evolution of the COVID-19 disease in Guadeloupe with a stochastic evolutionary model

MERIEM ALLALI; PATRICK PORTECOP; MICHEL CARLES; DOMINIQUE GIBERT

The model derived in the present study is highly non-linear with respect to most parameters, and it is expected that non-unique and significantly different solutions fitting the data might be obtained. This could be performed by the means of non-linear inverse methods like simulated annealing (9, 10) and will be presented in a forthcoming study. In the present study, the Z I and time-varying R 0 parameters are adjusted with the Nelder-Mead downhill simplex (11, 12) . The other parameters are determined with clinical observations in the Guadeloupe hospital and data published in the abundant literature concerning COVID-19. March 11, 2020) . These high R 0 are obtained during the week before municipal elections when meetings occurred and were probably places of high contamination rates (13, 14) . This could explain the high R 0 values found with the model. Interestingly, the large R 0 from days 1 to 6 must be combined with a large Z I = 80 to fit the sharp a onset of the ΣN s curve ( Fig. 2A ). The reasons for such a large number of initial infectious remain unknown, but we may suspect either a massive arrival of infected aircraft or ship passengers or the existence of several infectious spots like funeral wakes or election meetings as mentioned above.