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Data set for a predictive model for Spain on the economic impact of the COVID-19 crisis

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DataCite Commons2025-06-10 更新2025-04-09 收录
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https://dataverse.csuc.cat/citation?persistentId=doi:10.34810/data111
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资源简介:
The global COVID-19 spread has forced countries to implement non-pharmacological interventions (NPI) to preserve health systems. Spain is one of the most severely impacted countries, both clinically and economically. In an effort to support policy decision-making, Candel et al.(2021) [https://dx.doi.org/10.2139/ssrn.3745801] have developed a modified Susceptible-Exposed-Infectious-Removed (SEIR) epidemiological model to simulate the pandemic evolution. Its output was used to populate an economic model to quantify healthcare costs and GDP variation, through a regression model which correlates NPI and GDP change from 42 countries. The dataset contains information on the main variables used in order to specify and estimate this predictive model.
提供机构:
CORA.Repositori de Dades de Recerca
创建时间:
2021-05-06
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