Based on empirical data, we have developed a brief and easy-to-use screening strategy with higher accuracy and some practical advantages compared with commonly used tools.
A dynamic model for the current coronavirus outbreak is presented. The most important parameters are identified which determine the number of cases progression. Results of a numerical simulation are compared with existing data of the number of COVID-19 cases and deaths in Sao Paulo and Brazil. On the basis of these results we display the e↵ect of social distancing measures taken so far, which flattened the infection curve. A simple three steps procedure is proposed to predict changes in the evolution of the epidemics and we discuss the importance of serological representative surveys to relate the epidemic time to the real time. A criteria to start relaxing social distance measures is suggested.
The collective behavior of molecular motor proteins have been investigated in the literature using models to describe the long-time dynamics of a unidimensional continuum motor distribution. Here, we consider the phenomena related to the transport of particles (vesicles, organelles, virus, etc) in the realm of these continuum motor systems. We argue that cargo movement may result from its ability to perturb the existing motor distribution and to surf at the resulting shock waves separating regions of different motor densities within the transient regime. In this case, the observed bidirectionality of cargo movement is naturally associated with reversals of shocks directions. Comparison of the quantitative results predicted by this model with available data for cargo velocity allows us to suggest that geometrical characteristics of the transported particle shall determine the extension and intensity of the perturbation it produces and thus, its dynamics. Possible implications of these ideas to virus movement at the cell body are discussed in connection with their distinguished morphological characteristics.
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