Author summary Human mobility controls the spreading of infectious diseases worldwide. Pathogens use infected individuals as vehicles to travel from one city to another, between countries and even across continents. We know that the arrival of the first case or seed at a population is connected to the probability of traveling there from the area of disease emergence. The question that we address here is not when the first cases arrive or the local outbreak starts, but whether the continuous arrival of more infected individuals can have an impact on the development of the local outbreak. We show with standard epidemic spreading models that indeed there is a relation between the number of seeds arriving at a location over the resident population, the height of the local incidence peaks and the total population finally affected. It is a non-linear relation, and it depends on the details of the social contact network in the destination area. After this theoretical work and thanks to mobility data from different European countries of Europe, we find that there are solid signs of multiseeding effects similar to those observed in the models in the propagation of the first COVID-19 wave in the continent. We take advantage of this to propose a method to understand and reconstruct the spatial spreading patterns of the main outbreak-producing events in every country. From a public health point of view, surveillance on the importation of cases in a region is fundamental to anticipate the severity of local outbreaks and minimize their consequences.</p> Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. While many factors affect disease incidence at a local level, making it more or less homogeneous with respect to other areas, the importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible population. This can lead to independent outbreaks that spark from distinct areas of the local contact (social) network. Such mechanism has the potential to boost incidence, making control efforts and contact tracing less effective. Here, through a modeling approach we show that the effect produced by the number of initial infections is non-linear on the incidence peak and peak time. When case importations are carried by mobility from an already infected area, this effect is further enhanced by the local demography and underlying mixing patterns: the impact of every seed is larger in smaller populations. Finally, both in the model simulations and the analysis, we show that a multi-seeding effect combined with mobility restrictions can explain the observed spatial heterogeneities in the first wave of COVID-19 incidence and mortality in five European countries. Our results allow us for identifying what we have called epidemic epicenter: an area that shapes incidence and mortality peaks in the entire country. The present work further clarifies the nonlinear effects that mobility can have on the evolution of an epidemic and highlight their relevance for epidemic control.</p>