On 4 November 2020 the Italian government introduced a new policy to address the second wave of COVID-19. Based on a battery of indicators, the 21 administrative regions of Italy were assigned a risk level among yellow, orange, red, and, starting on 6 November 2020, different type of restrictions were applied accordingly. This event represents a natural experiment that allows the evaluation of the effects of non-pharmaceutical interventions, free from those nuisance factors affecting cross-national studies. In this work, we extract the daily growth rate of new cases, hospitalizations and patients in ICU from official data using an unobserved components model and assess how the different restrictions had different impacts in reducing the speed of spread of the virus. We find that all the three packages of restrictions have an effect on the speed of spread of the disease, but while the mildest (yellow) policy leads to a constant number of hospitalizations (zero growth rate), the strictest (red) policy is able to halve the number of accesses to regular wards and intensive care units in about one month. The effects of the intermediate (orange) policy are more volatile and seem to be only slightly more effective than the milder (yellow) policy.
(2021). Assessing the effectiveness of the Italian risk-zones policy during the second wave of COVID-19 [journal article - articolo]. In HEALTH POLICY. Retrieved from http://hdl.handle.net/10446/189589
Assessing the effectiveness of the Italian risk-zones policy during the second wave of COVID-19
Maranzano, Paolo
2021-01-01
Abstract
On 4 November 2020 the Italian government introduced a new policy to address the second wave of COVID-19. Based on a battery of indicators, the 21 administrative regions of Italy were assigned a risk level among yellow, orange, red, and, starting on 6 November 2020, different type of restrictions were applied accordingly. This event represents a natural experiment that allows the evaluation of the effects of non-pharmaceutical interventions, free from those nuisance factors affecting cross-national studies. In this work, we extract the daily growth rate of new cases, hospitalizations and patients in ICU from official data using an unobserved components model and assess how the different restrictions had different impacts in reducing the speed of spread of the virus. We find that all the three packages of restrictions have an effect on the speed of spread of the disease, but while the mildest (yellow) policy leads to a constant number of hospitalizations (zero growth rate), the strictest (red) policy is able to halve the number of accesses to regular wards and intensive care units in about one month. The effects of the intermediate (orange) policy are more volatile and seem to be only slightly more effective than the milder (yellow) policy.File | Dimensione del file | Formato | |
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