COVID-19: nothing is normal in this pandemic

Luzia Gonçalves, Maria Antónia Amaral Turkman, Carlos Geraldes, Tiago A Marques, Lisete Sousa

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)146 - 149
JournalJournal of Epidemiology and Global Health
Issue number2
Early online date20 Jan 2021
Publication statusPublished - Jun 2021


  • COVID-19
  • Epidemic curve
  • Gaussian curve
  • Log-normal distribution
  • Normal distribution


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