Key risk factors associated with fractal dimension based geographical clustering of Covid-19 data in the Flemish and Brussels region, Belgium
Bibliographic Data
| ID | 22072518 |
|---|---|
| Authors | Yessika Adelwin Natalia (0000-0002-4622-2616, Hasselt University, corresponding author), Christel Faes (0000-0002-1878-9869, Hasselt University), Thomas Neyens (0000-0003-2364-7555, Statistics Belgium), Naïma Hammami (0000-0002-2572-6540), Geert Molenberghs (0000-0002-6453-5448, Statistics Belgium) |
| Year | 2023 |
| Volume | 11 |
| Pages | 1249141-1249141 |
| Publication date | 2023-11-03 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2023.1249141 |
| PMID | 38026374 |
| OpenAlex | W4388303599 |
| Language | EN |
| References cited | 47 |
Introduction: COVID-19 remains a major concern globally. Therefore, it is important to evaluate COVID-19's rapidly changing trends. The fractal dimension has been proposed as a viable method to characterize COVID-19 curves since epidemic data is often subject to considerable heterogeneity. In this study, we aim to investigate the association between various socio-demographic factors and the complexity of the COVID-19 curve as quantified through its fractal dimension. Methods: We collected population indicators data (ethnic composition, socioeconomic status, number of inhabitants, population density, the older adult population proportion, vaccination rate, satisfaction, and trust in the government) at the level of the statistical sector in Belgium. We compared these data with fractal dimension indicators of COVID-19 incidence between 1 January - 31 December 2021 using canonical correlation analysis. Results: Our results showed that these population indicators have a significant association with COVID-19 incidences, with the highest explanatory and predictive power coming from the number of inhabitants, population density, and ethnic composition. Conclusion: It is important to monitor these population indicators during a pandemic, especially when dealing with targeted interventions for a specific population
Fractal · Fractal dimension · Geography · Pandemic · Population · Socioeconomic status · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Demography · Fractal and DNA sequence analysis · Mathematics · Medicine
A tribute to Claude Shannon (1916–2001) and a plea for more rigorous use of species richness, species diversity and the ‘Shannon–Wiener’ Index
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Canonical Correspondence Analysis
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Distrustful, Dissatisfied, and Conspiratorial
| Citation velocity | historical |
|---|---|
| Highly cited | No |