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Using posterior predictive distributions to analyse epidemic models: COVID-19 in Mexico City

Scientists and public health officials have relied on a variety of epidemiological models to forecast the trajectory of the coronavirus pandemic, and to derive guidance for policies aiming to avoid overloading health facilities. All such models contain parameters, and forecasting tools tend to choose these to provide a best fit to available observations.

Modeling the second wave of COVID-19 infections in France and Italy via a stochastic SEIR model

Late in the spring of this year, many nations around the world, especially in Europe, faced public health crises, as coronavirus infections threatened to overwhelm their intensive care facilities. Authorities responded with drastic measures to reduce social contacts, closing businesses and schools, restricting public transport and banning large social events.

Spatiotemporal seismic hazard and risk assessment of M9.0 megathrust earthquake sequences of wood‐frame houses in Victoria, British Columbia, Canada

Large earthquakes and the aftershocks they generate cause considerable damage to buildings. As a result, risk management, evacuation planning and rapid seismic loss estimation require good estimates of the cumulative damage likely to arise from an earthquake sequence. This is especially important in geographical regions of extreme risk.

Topological Comparison Between the Stochastic and the Nearest‐Neighbor Earthquake Declustering Methods Through Network Analysis

On short timescales, earthquakes cluster in both time and space, eventually complicating the analysis of seismicity. One basic goal is to partition the earthquake catalogue into two classes of events — background events, regarded as spontaneous or independent earthquakes, and clustered events, including events triggered by other earthquakes.