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

A. Presentation of the data. This section gives details on the method used for the data analysis and presents the results used to constrain the stochastic model presented in section Stochastic Monte Carlo model. Figure 8 shows the data used in the present study, namely the numbers N s and N c of severe and critical case observed in Guadeloupe from March 13 th until April 2 of year 2020. These data are presented in both linear and semi-logarithmic plots in order to better emphasise a possible exponential-like pattern. Because of the small number of data available at the time of writing the present paper, the exponential increase of either N s or N c is not as conspicuous as for the synthetic case presented in Figure 6 . However, for the data set N s , the semi-logarithmic plot (Fig. 8B) is reasonably linear in the [day 7 − day 16] period. The first 6 points are expected to correspond to the δT s onset period of 6 to 7 days. For the N c data, a linear segment may be identified in the [day 6 − day 19] period. By comparing the onset period in the data with the simulation results of Figure 7 , we may claim that the onset sequence of the data curve N s corresponds to a rather large number of at least 80 initial infectious persons. These persons could for instance be passengers of an aircraft or members of a group infected by a single infectious during a meeting.