Covid-19 and Possible Bias in Statistical Information: Pandemic Indicators and the Risk of Infodemic

Abstract. A widely discussed theme at this time in Italy concerns the statistical data used to evaluate the Covid-19 trend, given that some indicators have had considerable influence in determining policy choices. The statistical collection can produce an infodemic process that we must counteract and avoid. In some cases, information on the effects of Covid-19 is difficult to obtain, and data are not always scientifically collected. Pandemic data are often analysed without being standardised, or do not have an established definition. Some indicators are difficult to measure, while the use of a single recognised measure would help to better understand the effects of the pandemic. Moreover, the way in which statistical information on Covid-19 is disseminated also contributes to create a framing that can affect the use of the variables (or indicators) analysed. The correct use and interpretation of indicators becomes relevant when an increasing amount of information contains measurement errors due to non-structured data or interpretative framing. The aim of the article is to identify the potential bias that can be generated by reading pandemic data. The entire process of statistical collection, including its communication, should be monitored because good public choices should depend on the correct use of statistics.