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

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.12.20063008 doi: medRxiv preprint The model indicates that, after approximately one month of low-level infectious spread, the number of cases again dramatically increases after day 90. 4). Both models 2 and 3 fit the data as well as model 1 excepted for the flattening part of the ΣN s data after day 21 (March 31). This indicates that the determination of R 0 during the containment is constrained only by the most recent data values. The quality and reliability of these data is then of a great importance to derive models able to predict an eventual decrease of critical cases. Model 2 (Fig. 3) corresponds to the containment R 0 = 0.6 and gives a maximum number of critical cases of the same order and at the same date as the one obtained with model 1 (Fig. 2) . However, the decrease following the maximum is less steep and low values are reached about 3 weeks later with respect to what is observed with model 1. This translates into a larger cumulative number of critical case and, consequently, in a larger number of deceased patients (compare Fig. 2E and Fig. 3E ). Model 3 (Fig. 4 ) corresponds to R 0 = 0.8. As can be verified in Figure 4A ,C, the flattening of the data after day 21 (March 31) is poorly reproduced making this model less likely than models 1 and 2. However, owing that the flattening of the ΣN s curve relies on a small part of the most recent data,this pessimistic model cannot be totally excluded at the time of writing this article. The maximum values of critical cases may reach a maximum of 30 critical patient followed by a plateau with a small slope during which the instantaneous number N c remains around 15-20 one month after the date of the maximum. This correspond to a situation where the treatment of numerous critical patients must be sustained during a long period, implying the disposal of a sufficiently large medical staff and amount of equipment. As can be observed in Figure 4E the number of deceased patients increases steadily.