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10.1007/5584_2020_540

http://scihub22266oqcxt.onion/10.1007/5584_2020_540
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32424489!ä!32424489

suck abstract from ncbi


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pmid32424489      Adv+Exp+Med+Biol 2020 ; 1288 (ä): 1-3
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  • Data Analysis of Infection Rates Among Exposed Healthcare Workers Could Reveal Effective Prophylactics Against SARS-CoV-2 #MMPMID32424489
  • Nunez-Mujica G; Kichuk T; Carrasco-Lopez C
  • Adv Exp Med Biol 2020[]; 1288 (ä): 1-3 PMID32424489show ga
  • The global crisis provoked by the SARS-CoV-2 pandemic, and the economic and social consequences associated to the essential policies applied to contain it, necessitates the expedited development of therapeutic solutions. It is a priority to produce data both rapidly and accurately in order to identify current therapies that can be repurposed to offer protection from SARS-CoV-2 infection. As healthcare workers are both at high risk for infection and able to be readily diagnosed, they offer a potential wealth of data to be analyzed. A systematic data analysis of exposure and infection rates among healthcare workers could yield patterns identifying common protective factors, such as medications with prophylactic potential against SARS-CoV-2, that can be fast-tracked into available therapies. With results suggesting their activity against other coronaviruses and their widespread adoption, Antiretroviral cocktails could be a promising initial target for such large-scale data analysis approach.
  • |*Data Analysis[MESH]
  • |Betacoronavirus/*drug effects[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/diagnosis/*prevention & control/therapy/*transmission[MESH]
  • |Health Personnel/*statistics & numerical data[MESH]
  • |Humans[MESH]
  • |Pandemics/*prevention & control[MESH]
  • |Pneumonia, Viral/diagnosis/*prevention & control/therapy/*transmission[MESH]
  • |Post-Exposure Prophylaxis/*methods[MESH]
  • |Pre-Exposure Prophylaxis/*methods[MESH]


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