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Infodemics: a new challenge for public health

How can we face the great spreading of information — which is often incorrect — in the current pandemic? How can we measure the effect that information has on the management of the pandemic? These are some of the questions that an international team which includes Fabiana Zollo and Matteo Cinelli, researchers at the Department of Environmental Sciences, Informatics and Statistics, tries to answer in the article “Infodemics: A new challenge for public health”, recently published on Cell

According to its most recent definition by the World Health Organisation, the term “infodemic” refers to “too much information including false or misleading information in digital and pusical environments during a disease outbreak.”  

One of the first points highlighted in the article is the difference between an epidemic and an infodemic: the spreading of the virus is not optional, while the spreading of information is. In fact, we can decide whether to accept or not to accept a piece of information. This makes modelling and forecast models completely different.

The researchers highlighted key differences between the two systems, underlining their strong interconnection and the possibility that they influence each other. The article emphasises that in order to manage the pandemic effectively, the dynamics of information processing need to be taken into account. 

The researchers reccomend starting from these key elements:

  • confirmation bias, i.e., the tendency to look for information that confirms our convictions, and to ignore opposing information;
  • echo chamber, i.e. the creation of communities that share the same narrative (vision) and reinforce it;
  • polarisation.

Considering this process, it is necessary to take into account the new potentials of data science applied to social contexts, in order to better understand, and potentially to forecast, the evolution of public opinion and its effects on society and on policies for the management of pandemics. 

The analysis was conducted thanks to the collaboration of a group of experts in data science, computational epidemiologists, representatives of the World Health Organisation and of Centers for Disease Control and Prevention. The coordinator is Walter Quattrociocchi, Professor at Sapienza University of Rome. Other contributors are Fabiana Zollo from Ca’ Foscari and experts from INSEREM (Institut national de la santé et de la recherche médicale) and Sorbonne University Paris.

Author: Enrico Costa / Translator: Joangela Ceccon