Fractal dimension based geographical clustering of COVID-19 time series data

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 Flande...

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Bibliographic Details
Published in:Scientific reports 2023-03, Vol.13 (1), p.4322-4322, Article 4322
Main Authors: Natalia, Yessika Adelwin, Faes, Christel, Neyens, Thomas, Chys, Pieter, Hammami, Naïma, Molenberghs, Geert
Format: Article
Language:English
Subjects:
631/114/1305
639/705/531
692/699/255
692/700/478/174
Belgium - epidemiology
Coronaviruses
COVID-19
COVID-19 - epidemiology
Disease transmission
Fractals
Geography
Humanities and Social Sciences
Humans
Infectious diseases
multidisciplinary
Science
Science (multidisciplinary)
Statistical analysis
Time Factors
Time series
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Summary: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.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-30948-7