In this work we report that the public reacted on social media at an early stage of the COVID-19 pandemic in a surprisingly accurate way , with activity levels reflecting the severity of the contagion figures registered almost a month later. Specifically, the intensity of COVID-related social media activity from different Italian  regions at the beginning of the epidemic (21-24/2/2020) , predicts well the total number of deaths reached almost a month later (7/4/2020) in each region. It should be noted that at the time of the initial twitter reaction no tabled regional data on the epidemic was readily available  . By the 24th February 2020 only two regions reported death cases and only three reported infected subjects  .
In this work we report that the public reacted on social media at an early stage of the SARS-CoV-2 pandemic, the virus responsible of COVID-19, in a surprisingly accurate way . Early social media activity levels reflected the severity of the disease as registered almost a month later. Specifically, the intensity of COVID-19 related social media activity from different Italian , Spanish and United States regions at the beginning of the epidemic , predicts well the total number of deaths reached almost a month later in each region. More strikingly, at the time of the initial twitter reaction no tabled regional data on the epidemic was readily available in Italy . By the 24th February 2020 only two regions reported death cases and only three reported infected subjects . Our findings could underpin the creation of real-time novelty detection systems aimed at early reporting of SARS-like mortality and thus early activation of control measures in future pandemics .
R
COVID-19 pandemic
SARS-CoV-2 pandemic, the virus responsible of COVID-19,
R
, with activity levels reflecting
. Early social media activity levels reflected
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contagion figures
disease as
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COVID-related
COVID-19 related
A
, Spanish and United States
D
(21-24/2/2020)
D
(7/4/2020)
R
It should be noted that
More strikingly,
A
in Italy
A
. Our findings could underpin the creation of real-time novelty detection systems aimed at early reporting of SARS-like mortality and thus early activation of control measures in future pandemics