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Multiple Infections and Lung Damage Models Imply Strategies for Containing the COVID-19 Pandemic

Submitted:

26 February 2020

Posted:

29 February 2020

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Abstract
The COVID-19 pandemic threatens human lives mainly due to rapid disease development that cannot be held in check reliably. To address this difficulty, we explore infection and host response kinetics and their influencing factors. In kinetics, all influencing factors affect viral reproduction, immune response, and lung damages by their accumulating effects in the entire disease course. From existing data, we deduced a two-phase infection model, multiple infection modes, and a progressively degrading lung damage model. From exploring the model behaviors, we propose double tenth reduction strategies for containing the pandemic. The first strategy is reducing incidence rate from the current level to one tenth by avoiding exposures that could result in widespread damages to lungs and taking measures for reducing disease severity to that of a cold. The second strategy is reducing death rate from the current level to one tenth for infected patients by using multiple factors health optimization method. The models imply different treatment strategies for patients at different stages. In the early stage or before virus has spread to the whole lungs, measures are taken to slow down viral reproduction and slow down reinfections; and, after the virus has infected the whole lungs, the focus is maintaining blood micro-circulation and preserving functions of all major organs. The double tenth reduction strategies are expected to generate a series of chain reactions that favor containing the pandemic. Some reactions include a big reduction of the amount of viral discharges from infected patients into the air, the avoidance of panic, chronic stress and emotional distress, and cross-infections which are expected in quarantines. The double ten reductions would make the disease manageable and tolerable.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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