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

In order to determine the β parameter and its uncertainty limits from the small-size data sets of Figure 8 , we use a bootstrapping approach (22) . Let us recall that this method relies on a statistical resampling of the data sets in order to reconstitute the statistical variability of the estimated parameter β. In the present study, we performed 1000 bootstrap resamplings for each data set N s and N c , and the so-obtained 1000 estimates of β may be used to compute the probability density kernels shown in Figure 9A . The two probability distributions are poorly statistically coherent with a small overlap of the two curves. Equation 2 may be used to compute R 0 (using T I = 14 days) from the β probability curves. The estimate for R 0 1.85 ± 0.03 is coherent with the values published by Li et al. (21) who found R 0 = 2.2 with a 95% confidence interval [1.4 − 3.9].