Brunori, Paolo ORCID: 0000-0002-1624-905X, Resce, Giuliano and Serlenga, Laura (2022) Searching for the peak: Google Trends and the first COVID-19 wave in Italy. International Journal of Computational Economics and Econometrics, 12 (4). 445 - 458. ISSN 1757-1170
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Abstract
One of the difficulties faced by policymakers during the COVID-19 outbreak in Italy was the monitoring of the virus diffusion. Due to changes in the criteria and insufficient resources to test all suspected cases, the number of ‘confirmed infected’ rapidly proved to be unreliably reported by official statistics. We explore the possibility of using information obtained from Google Trends to predict the evolution of the epidemic. Following the most recent developments on the statistical analysis of longitudinal data, we estimate a dynamic heterogeneous panel. This approach allows to takes into account the presence of common shocks and unobserved components in the error term both likely to occur in this context. We find that Google queries contain useful information to predict number patients admitted to the intensive care units, number of deaths and excess mortality in Italian regions.
Item Type: | Article |
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Official URL: | https://www.inderscienceonline.com/journal/ijcee |
Additional Information: | © 2022 Inderscience Enterprises Ltd. |
Divisions: | International Inequalities Institute |
Subjects: | R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine H Social Sciences > HV Social pathology. Social and public welfare. Criminology H Social Sciences > HM Sociology |
Date Deposited: | 07 Dec 2022 16:21 |
Last Modified: | 01 Nov 2024 05:41 |
URI: | http://eprints.lse.ac.uk/id/eprint/117566 |
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