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Occupancy patterns are known to strongly affect the number of people killed by earthquakes. Existing exposure models for Europe based on housing census do not account for the daily movement of the population between the place of residence (residential occupancy) and places of economic activity (non-residential occupancy), or the seasonal patterns due to tourism. This study presents a framework to upgrade exposure models from static to 'dynamic', i.e., allowing the input population to change in time and space based on daily and monthly population movement patterns. Open-source population data is used to disaggregate and rescale occupants inside residential, commercial and industrial buildings of 28 European countries, resulting in 24 occupancy categories: two times (i.e., day and night) x 12 months at 30 arc-seconds resolution. The static vs dynamic exposure models are compared using the number and distribution of fatalities resulting from loss calculations for a stochastic set of earthquakes generated from the European Seismic Hazard model (ESHM20). The results demonstrate that the spatiotemporal patterns of population can significantly impact earthquake mortality rates and should not be neglected in scenario loss assessment. The results also demonstrate that the worst occurrence time depends on both the distribution of indoor population between building occupancies and the earthquake rupture characteristics. The ability to capture population distribution during the day and night or seasonal changes (e.g., winter vs summer) is a feature that can advance the ongoing rapid damage/loss assessment services in Europe and consequently support emergency response planning.