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COVID-19 in Italy and extreme data mining.
Paolo Massimo Buscema1,2, Francesca Della Torre1, Marco Breda1
1Semeion Research Center of Sciences of Communication, via Sersale, 117, 00128 Rome, Italy.
Physica A
|August 25, 2020
Summary
Topological Weighted Centroid (TWC) is an AI algorithm proving effective for analyzing COVID-19 spread using limited geospatial data. It offers valuable insights even with small datasets, crucial for early epidemic stages.
Area of Science:
- Epidemiology and Artificial Intelligence
- Computational Biology
- Geospatial Analysis
Background:
- The COVID-19 pandemic highlighted the need for effective epidemic analysis tools.
- Traditional big data approaches are often insufficient in early epidemic stages with limited data.
- Small datasets pose challenges for statistical analysis in disease outbreak modeling.
Purpose of the Study:
- To demonstrate the potential of the Topological Weighted Centroid (TWC) evolutionary algorithm for analyzing epidemic data.
- To show that valuable insights can be extracted from small, limited datasets, particularly in the early phases of an epidemic.
- To apply the TWC algorithm to model the COVID-19 epidemic in Italy using only initial case geospatial coordinates.
Main Methods:
- Utilized the Topological Weighted Centroid (TWC) artificial intelligence algorithm.
- Employed a dataset comprising only the geospatial coordinates (longitude and latitude) of early COVID-19 cases in Italy (until February 26th, 2020).
- Performed analyses including outbreak point identification (TWC alpha), contagion probability distribution (TWC beta), future spread prediction (TWC gamma and TWC theta), and transmission path analysis (Theta paths and Markov Machine).
Main Results:
- The TWC algorithm successfully analyzed the evolution of the COVID-19 epidemic using limited geospatial data.
- Generated heat maps illustrating outbreak points, contagion probability, and predicted future infectiousness.
- Identified transmission paths and mutual influence between locations.
Conclusions:
- The Topological Weighted Centroid (TWC) algorithm demonstrates significant potential for extracting relevant information from small datasets in epidemic analysis.
- This AI approach provides valuable insights even when traditional statistical methods are limited by insufficient data.
- The study confirms the efficacy of TWC in understanding and predicting epidemic spread, as demonstrated by the COVID-19 case study in Italy.
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