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10.1371/journal.pone.0251349

http://scihub22266oqcxt.onion/10.1371/journal.pone.0251349
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33984035!8118310!33984035
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suck abstract from ncbi

pmid33984035      PLoS+One 2021 ; 16 (5): e0251349
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  • Three pre-vaccine responses to Covid-like epidemics #MMPMID33984035
  • Young LS; Danial Z
  • PLoS One 2021[]; 16 (5): e0251349 PMID33984035show ga
  • This paper contains a theoretical study of epidemic control. It is inspired by current events but not intended to be an accurate depiction of the SARS-CoV-2 pandemic. We consider the emergence of a highly transmissible pathogen, focusing on metropolitan areas. To ensure some degree of realism, we present a conceptual model of the outbreak and early attempts to stave off the onslaught, including the use of lockdowns. Model outputs show strong qualitative-in some respects even quantitative-resemblance to the events of Spring 2020 in many cities worldwide. We then use this model to project forward in time to examine different paths in epidemic control after the initial surge is tamed and before the arrival of vaccines. Three very different control strategies are analyzed, leading to vastly different outcomes in terms of economic recovery and total infected population (or progress toward herd immunity). Our model, which is a version of the SEIQR model, is a time-dependent dynamical system with feedback-control. One of the main conclusions of this analysis is that the course of the epidemic is not entirely dictated by the virus: how the population responds to it can play an equally important role in determining the eventual outcome.
  • |Algorithms[MESH]
  • |COVID-19/*epidemiology/immunology/*prevention & control[MESH]
  • |Cities/epidemiology[MESH]
  • |Communicable Disease Control[MESH]
  • |Disease Outbreaks[MESH]
  • |Epidemiological Monitoring[MESH]
  • |Humans[MESH]
  • |Immunity, Herd[MESH]
  • |Models, Statistical[MESH]


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