Abstract
The aim of this paper is the derivation of an robust formalism that calculates the so-called social distancing as already determined in the ongoing Corona Virus Disease 2019 (Covid-19 in short) being established in various places in the world between 1.5 m and 2.5 m. This would constitutes a critic space of separation among people in the which aerosols might not be effective to infect healthy people. In addition to wearing masks and face protection, the social distancing appears to be critic to keep people far of infections and consequences produced from it. In this way, the paper has opted by the incorporation of a full deterministic model inside the equation of Weiss, by the which it fits well to the action of outdoor infection when wind manages the direction and displacement of aerosols in space. Thus, while a deterministic approach targets to propose a risk’s probability, a probabilistic scenario established by Weiss in conjunction to the deterministic events would yield an approximated model of outdoor infection when there is a continuous source of infected aerosols that are moving through air in according to a wind velocity. The simulations have shown that the present approach is valid to some extent in the sense that only the 1D case is considered. The model can be extended with the implementation of physical variables that can attenuate the presence of disturbs and random noise that minimizes the effectiveness of present proposal.
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- 1.
Obviously the probability of occupancy is done by 1\(-\mathbf{P}\).
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One can see that sum yields 110 cells, fact that can be understood in terms of errors of model.
- 3.
Among others not less relevant, such as nano particles and drug delivery carriers.
- 4.
However neither temperatures nor specifying indoor and outdoor were done.
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Nieto-Chaupis, H. (2021). The Conjunction of Deterministic and Probabilistic Events in Realistic Scenarios of Outdoor Infections. In: Nakano, T. (eds) Bio-Inspired Information and Communications Technologies. BICT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-030-92163-7_21
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