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Population density impact on COVID-19 mortality rate: A multifractal analysis using French data.

R Pascoal1, H Rocha1,2

  • 1CeBER, FEUC, Univ. Coimbra, Av. Dias da Silva 165, 3004-512 Coimbra, Portugal.

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Population density significantly impacts infectious disease spread, as seen with COVID-19. A new population-weighted density measure better predicts COVID-19 deaths in France than traditional measures.

Keywords:
COVID-19FranceMultifractal analysisPopulation density

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Area of Science:

  • Epidemiology
  • Public Health
  • Spatial Analysis

Background:

  • The COVID-19 pandemic highlighted the need to understand factors influencing infectious disease transmission.
  • The relationship between population density and the spread of highly contagious diseases like COVID-19 is a subject of ongoing debate.
  • Existing studies lack consensus on how population density affects disease outcomes.

Purpose of the Study:

  • To investigate the impact of population density on COVID-19 mortality in France.
  • To evaluate a novel population-weighted density measure against traditional density metrics.
  • To explore the utility of multifractal analysis in understanding disease-environment relationships.

Main Methods:

  • Utilized COVID-19 data from France.
  • Introduced and applied a population-weighted density measure.
  • Employed multifractal analysis to characterize population spatial distributions.
  • Compared the novel density measure with standard density and population predictors.

Main Results:

  • The population-weighted density measure demonstrated a stronger correlation with COVID-19 deaths compared to the commonly used density measure.
  • The novel measure proved competitive with established predictors like total population.
  • Multifractal analysis provided insights into the complex relationship between population distribution and mortality rates.

Conclusions:

  • Population density, particularly when weighted by population, is a critical factor in COVID-19 mortality.
  • The developed density metric offers a more accurate approach to assessing disease risk in diverse spatial contexts.
  • Further research using advanced spatial analysis can elucidate disease dynamics in relation to population structures.