ArticleScientific reports2021
Applying a hierarchical clustering on principal components approach to identify different patterns of the SARS-CoV-2 epidemic across Italian regions.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Patterns between evidence seeking behaviors, reasoning, and cognitive reflection: A supervised clustering approach.PloS one · 2026Article
- Construction of Development Scores to Analyze Inequalities in Childhood Immunization Coverage: A Global Analysis from 2000 to 2021.International journal of environmental research and public health · 2025Article
- Influence of decompression surgery on sagittal balance parameters in patients with lumbar spinal stenosis.Scientific reports · 2025Observational
- Using country-level variables to discover country clusters beyond traditional health policy and performance metrics: An unsupervised machine learning approach for HIV healthcare delivery and financing.PLOS global public health · 2025Article
- Rapid and Robust Identification of Sepsis Using SeptiCyte RAPID in a Heterogeneous Patient Population.Journal of clinical medicine · 2024Article
- Preparedness of Nursing Homes: A Typology and Analysis of Responses to the COVID-19 Crisis in a French Network.Healthcare (Basel, Switzerland) · 2024Article
- Understanding epidemic spread patterns: a visual analysis approach.Health systems (Basingstoke, England) · 2024Article
- Limitations of Clustering with PCA and Correlated Noise.Journal of statistical computation and simulation · 2024Article
- Association between quality of governance, antibiotic consumption, and antimicrobial resistance: an analysis of Italian regions.Antimicrobial resistance and infection control · 2023Article
- Comprehensive Study of Drug-Induced Pruritus Based on Adverse Drug Reaction Report Database.Pharmaceuticals (Basel, Switzerland) · 2023Article
- How COVID-19 Pandemic Has Influenced Public Interest in Foods: A Google Trends Analysis of Italian Data.International journal of environmental research and public health · 2023Article
- The Application of Clustering on Principal Components for Nutritional Epidemiology: A Workflow to Derive Dietary Patterns.Nutrients · 2022Article
- Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study.JMIR formative research · 2022Article
- How COVID-19 Has Influenced Public Interest in Antimicrobials, Antimicrobial Resistance and Related Preventive Measures: A Google Trends Analysis of Italian Data.Antibiotics (Basel, Switzerland) · 2022Article
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4 authors.
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Abstract
Italy has experienced the epidemic of Severe Acute Respiratory Syndrome Coronavirus 2, which spread at different times and with different intensities throughout its territory. We aimed to identify clusters with similar epidemic patterns across Italian regions. To do that, we defined a set of regional indicators reflecting different domains and employed a hierarchical clustering on principal component approach to obtain an optimal cluster solution. As of 24 April 2020, Lombardy was the worst hit Italian region and entirely separated from all the others. Sensitivity analysis-by excluding data from Lombardy-partitioned the remaining regions into four clusters. Although cluster 1 (i.e. Veneto) and 2 (i.e. Piedmont and Emilia-Romagna) included the most hit regions beyond Lombardy, this partition reflected differences in the efficacy of restrictions and testing strategies. Cluster 3 was heterogeneous and comprised regions where the epidemic started later and/or where it spread with the lowest intensity. Regions within cluster 4 were those where the epidemic started slightly after Veneto, Emilia-Romagna and Piedmont, favoring timely adoption of control measures. Our findings provide policymakers with a snapshot of the epidemic in Italy, which might help guiding the adoption of countermeasures in accordance with the situation at regional level.
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