The importance of data to understand the pandemic


Institutional Communication Service

27 April 2020

The Covid-19 pandemic has peaked and has entered a new phase that also involves the analysis of data on the spread of the coronavirus, which is useful to help understand – among other things – the impact of the measures taken by health and political authorities. In the initial phase of the pandemic, a few researchers at the USI Institute of Finance created a 'contagion map' (the 'Coronamapper', see also the report on RSI, in Italian), while now another team (also from the USI Institute of Finance) has developed a particular analysis of the evolution between three geographically close and very interconnected regions: Ticino, Lombardy and Veneto.

With the Coronavirus Insights website, Silvia Dalla Fontana and Nicola Mano, both PhD candidates at the USI Institute of Finance, propose two analyses, one between the northern Italian Regions of Veneto and Lombardy, and one between Lombardy and Ticino. The former was chosen because it not only concerns two Regions among the most affected in Italy, but also the first where outbreaks of the pandemic were recorded, with corresponding quarantine measures imposed already in February. The latter, instead, was chosen because of the close geographic and economic interconnection, given the high daily flow of border workers. In both cases, the handling of the situation and the measures taken by the respective authorities, both in terms of timing and methods, have been different, and it may be useful to understand how much and whether these differences have been important in determining the evolution of the virus. 

"At a time when public debates, personal hypotheses and imaginative reconstructions are raging around the effectiveness of containment measures, there is nothing wiser than to construct one's own opinions on the basis of data. In this sense, the inter-regional comparison between the indexes we propose can be a starting point for maturing awareness of these complex dynamics", Nicola Mano points out.

From the analysis in the cross-border comparison, in particular, some interesting elements emerge. In Ticino, for example, compared to Lombardy, the cases of contagion reported seem to increase faster in March. At the same time, the positive curve, both official and estimated, for Ticino seems to slow down more rapidly in April. Moreover, the number of hospitalised patients over the ones confirmed positive is higher in Lombardy, while the number of patients in intensive care over hospitalised patients is higher in Ticino. Finally, while the number of admitted patients (per 10 thousand inhabitants) is higher in Lombardy, the number of patients in intensive care (per 10 thousand inhabitants) is higher in Ticino. 

"One of the things this experience has taught us is that humanity is deeply defenseless in the face of pandemic situation. Though we can be aware that similar situations may arise again, we believe that any exercise in understanding the data can help us find ourselves better prepared to face possible future challenges", concludes Silvia Dalla Fontana.