ArticleJournal of population economics2021
Local mortality estimates during the COVID-19 pandemic in Italy.
Article in Journal of population economics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 7 citations in OpenAlex.
- Cause-specific excess mortality in Denmark, Finland, Norway, and Sweden during the COVID-19 pandemic 2020-2022: a study using nationwide population data.European journal of epidemiology · 2024Article
- Inequalities in regional excess mortality and life expectancy during the COVID-19 pandemic in Europe.Scientific reports · 2024Article
- Estimating subnational excess mortality in times of pandemic. An application to French départements in 2020.PloS one · 2024Article
- The effect of the COVID-19 pandemic on life expectancy in 27 countries.Scientific reports · 2023Article
- Does Automatic Wage Indexation Destroy Jobs? A Machine Learning Approach.De Economist · 2023Article
- Impact of the COVID-19 Pandemic on Total and Cause-Specific Mortality in Pavia, Northern Italy.International journal of environmental research and public health · 2022Article
- Identifying Predictors of COVID-19 Mortality Using Machine Learning.Life (Basel, Switzerland) · 2022Article
- COVID-19 severity: A new approach to quantifying global cases and deaths.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2022Article
- Local inequalities of the COVID-19 crisis.Regional science and urban economics · 2022Article
- From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy.Journal of population economics · 2022Article
- Mobility in times of pandemics: Evidence on the spread of COVID19 in Italy's labour market areas.Structural change and economic dynamics · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Estimates of the real death toll of the COVID-19 pandemic have proven to be problematic in many countries, Italy being no exception. Mortality estimates at the local level are even more uncertain as they require stringent conditions, such as granularity and accuracy of the data at hand, which are rarely met. The "official" approach adopted by public institutions to estimate the "excess mortality" during the pandemic draws on a comparison between observed all-cause mortality data for 2020 and averages of mortality figures in the past years for the same period. In this paper, we apply the recently developed machine learning control method to build a more realistic counterfactual scenario of mortality in the absence of COVID-19. We demonstrate that supervised machine learning techniques outperform the official method by substantially improving the prediction accuracy of the local mortality in "ordinary" years, especially in small- and medium-sized municipalities. We then apply the best-performing algorithms to derive estimates of local excess mortality for the period between February and September 2020. Such estimates allow us to provide insights about the demographic evolution of the first wave of the pandemic throughout the country. To help improve diagnostic and monitoring efforts, our dataset is freely available to the research community. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00148-021-00857-y.
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