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Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study
Background: Policy-makers have attempted to mitigate the spread of covid-19 with national and local non-pharmaceutical interventions. Moreover, evidence suggests that some areas are more exposed than others to contagion risk due to heterogeneous local characteristics. We study whether Italy’s region...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279774/ https://www.ncbi.nlm.nih.gov/pubmed/34308412 http://dx.doi.org/10.1016/j.lanepe.2021.100169 |
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author | Guaitoli, Gabriele Pancrazi, Roberto |
author_facet | Guaitoli, Gabriele Pancrazi, Roberto |
author_sort | Guaitoli, Gabriele |
collection | PubMed |
description | Background: Policy-makers have attempted to mitigate the spread of covid-19 with national and local non-pharmaceutical interventions. Moreover, evidence suggests that some areas are more exposed than others to contagion risk due to heterogeneous local characteristics. We study whether Italy’s regional policies, introduced on 4th November 2020, have effectively tackled the local infection risk arising from such heterogeneity. Methods: Italy consists of 19 regions (and 2 autonomous provinces), further divided into 107 provinces. We collect 35 province-specific pre-covid variables related to demographics, geography, economic activity, and mobility. First, we test whether their within-region variation explains the covid-19 incidence during the Italian second wave. Using a LASSO algorithm, we isolate variables with high explanatory power. Then, we test if their explanatory power disappears after the introduction of the regional-level policies. Findings: The within-region variation of seven pre-covid characteristics is statistically significant (F-test p-value [Formula: see text]) and explains 19% of the province-level variation of covid-19 incidence, on top of region-specific factors, before regional policies were introduced. Its explanatory power declines to 7% after the introduction of regional policies, but is still significant (p-value [Formula: see text]), even in regions placed under stricter policies (p-value [Formula: see text]). Interpretation: Even within the same region, Italy’s provinces differ in exposure to covid-19 infection risk due to local characteristics. Regional policies did not eliminate these differences, but may have dampened them. Our evidence can be relevant for policy-makers who need to design non-pharmaceutical interventions. It also provides a methodological suggestion for researchers who attempt to estimate their causal effects. Funding: None. |
format | Online Article Text |
id | pubmed-8279774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-82797742021-07-20 Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study Guaitoli, Gabriele Pancrazi, Roberto Lancet Reg Health Eur Research Paper Background: Policy-makers have attempted to mitigate the spread of covid-19 with national and local non-pharmaceutical interventions. Moreover, evidence suggests that some areas are more exposed than others to contagion risk due to heterogeneous local characteristics. We study whether Italy’s regional policies, introduced on 4th November 2020, have effectively tackled the local infection risk arising from such heterogeneity. Methods: Italy consists of 19 regions (and 2 autonomous provinces), further divided into 107 provinces. We collect 35 province-specific pre-covid variables related to demographics, geography, economic activity, and mobility. First, we test whether their within-region variation explains the covid-19 incidence during the Italian second wave. Using a LASSO algorithm, we isolate variables with high explanatory power. Then, we test if their explanatory power disappears after the introduction of the regional-level policies. Findings: The within-region variation of seven pre-covid characteristics is statistically significant (F-test p-value [Formula: see text]) and explains 19% of the province-level variation of covid-19 incidence, on top of region-specific factors, before regional policies were introduced. Its explanatory power declines to 7% after the introduction of regional policies, but is still significant (p-value [Formula: see text]), even in regions placed under stricter policies (p-value [Formula: see text]). Interpretation: Even within the same region, Italy’s provinces differ in exposure to covid-19 infection risk due to local characteristics. Regional policies did not eliminate these differences, but may have dampened them. Our evidence can be relevant for policy-makers who need to design non-pharmaceutical interventions. It also provides a methodological suggestion for researchers who attempt to estimate their causal effects. Funding: None. Elsevier 2021-07-15 /pmc/articles/PMC8279774/ /pubmed/34308412 http://dx.doi.org/10.1016/j.lanepe.2021.100169 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Guaitoli, Gabriele Pancrazi, Roberto Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study |
title | Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study |
title_full | Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study |
title_fullStr | Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study |
title_full_unstemmed | Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study |
title_short | Covid-19: Regional policies and local infection risk: Evidence from Italy with a modelling study |
title_sort | covid-19: regional policies and local infection risk: evidence from italy with a modelling study |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279774/ https://www.ncbi.nlm.nih.gov/pubmed/34308412 http://dx.doi.org/10.1016/j.lanepe.2021.100169 |
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