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In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes' theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors indicate that predictions are of good quality. [ABSTRACT FROM AUTHOR]

Ground motion produced by low magnitude earthquakes can be used to predict peak values in high seismic risk areas where large earthquakes data are not available. In the present work 20 local earthquakes (M∈[−0.3, 2.2]) occurred in the Campi Flegrei caldera during the last decade were analyzed. We followed this strategy: empirical relations were used to calibrate synthetic modeling, accounting for the source features and wave propagation effects. Once the source and path parameters of ground motion simulation were obtained from the reference data set, we extrapolated scenarios for stronger earthquakes for which real data are not available. The procedure is structured in two steps: (1) evaluation of ground motion prediction equation for Campi Flegrei area and assessment of input parameters for the source, path and site effects in order to use the finite fault stochastic approach (EXSIM code); (2) simulation of two moderate-to-large earthquake scenarios for which only historical data or partial information are available (M4.2 and M5.4). The results show that the investigated area is characterized by high attenuation of peak amplitude and not negligible site effects. The stochastic approach has revealed a good tool to calibrate source, path and site parameters on small earthquakes and to generate large earthquake scenario. The investigated magnitude range represents a lower limit to apply the stochastic method as a calibration tool, due to the small size of involved faults (fault length around 200/300 m). [ABSTRACT FROM AUTHOR]