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10.2991/jegh.k.210108.001

http://scihub22266oqcxt.onion/10.2991/jegh.k.210108.001
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33605119!8242106!33605119
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suck abstract from ncbi

pmid33605119      J+Epidemiol+Glob+Health 2021 ; 11 (2): 146-149
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  • COVID-19: Nothing is Normal in this Pandemic #MMPMID33605119
  • Goncalves L; Turkman MAA; Geraldes C; Marques TA; Sousa L
  • J Epidemiol Glob Health 2021[Jun]; 11 (2): 146-149 PMID33605119show ga
  • This manuscript brings attention to inaccurate epidemiological concepts that emerged during the COVID-19 pandemic. In social media and scientific journals, some wrong references were given to a "normal epidemic curve" and also to a "log-normal curve/distribution". For many years, textbooks and courses of reputable institutions and scientific journals have disseminated misleading concepts. For example, calling histogram to plots of epidemic curves or using epidemic data to introduce the concept of a Gaussian distribution, ignoring its temporal indexing. Although an epidemic curve may look like a Gaussian curve and be eventually modelled by a Gauss function, it is not a normal distribution or a log-normal, as some authors claim. A pandemic produces highly-complex data and to tackle it effectively statistical and mathematical modelling need to go beyond the "one-size-fits-all solution". Classical textbooks need to be updated since pandemics happen and epidemiology needs to provide reliable information to policy recommendations and actions.
  • |*Epidemiologic Research Design[MESH]
  • |*Models, Statistical[MESH]
  • |COVID-19/*epidemiology[MESH]
  • |Humans[MESH]
  • |Normal Distribution[MESH]
  • |Pandemics/*statistics & numerical data[MESH]
  • |Reproducibility of Results[MESH]


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