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- Title
Fractal dimension based geographical clustering of COVID-19 time series data.
- Authors
Natalia, Yessika Adelwin; Faes, Christel; Neyens, Thomas; Chys, Pieter; Hammami, Naïma; Molenberghs, Geert
- Abstract
Understanding the local dynamics of COVID-19 transmission calls for an approach that characterizes the incidence curve in a small geographical unit. Given that incidence curves exhibit considerable day-to-day variation, the fractal structure of the time series dynamics is investigated for the Flanders and Brussels Regions of Belgium. For each statistical sector, the smallest administrative geographical entity in Belgium, fractal dimensions of COVID-19 incidence rates, based on rolling time spans of 7, 14, and 21 days were estimated using four different estimators: box-count, Hall-Wood, variogram, and madogram. We found varying patterns of fractal dimensions across time and location. The fractal dimension is further summarized by its mean, variance, and autocorrelation over time. These summary statistics are then used to cluster regions with different incidence rate patterns using k-means clustering. Fractal dimension analysis of COVID-19 incidence thus offers important insight into the past, current, and arguably future evolution of an infectious disease outbreak.
- Subjects
BELGIUM; FLANDERS; SCHWABISCH Hall (Germany); FRACTAL dimensions; TIME series analysis; COVID-19; K-means clustering; FRACTAL analysis; VARIOGRAMS
- Publication
Scientific Reports, 2023, Vol 13, Issue 1, p1
- ISSN
2045-2322
- Publication type
Article
- DOI
10.1038/s41598-023-30948-7