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A robust spatial correlation analysis for a better understanding of John Snow ghost map

Author

Listed:
  • Giuseppe Arbia

    (Università Cattolica del Sacro Cuore)

  • Vincenzo Nardelli

    (Università Cattolica del Sacro Cuore)

Abstract

John Snow is heralded as a pioneering figure in epidemiology and spatial analysis, notably through his innovative approach to mapping the 1854 cholera outbreak in London. This study seeks to merge the domains of historical epidemiological research and established spatial statistical techniques by utilizing the Moran’s coefficient (a very popular measure of spatial autocorrelation), on the original cholera dataset collected by John Snow. Despite the Moran coefficient celebrated ability to identify spatial autocorrelation patterns, its application to Snow’s dataset dramatically fails in detecting the outbreak of the cholera epidemic, primarily due to the presence of outliers in the dataset. This paper discusses the implications of these evidences in health applications of the standard spatial statistical methods and suggests some robust alternative to tackle the problem.

Suggested Citation

  • Giuseppe Arbia & Vincenzo Nardelli, 2025. "A robust spatial correlation analysis for a better understanding of John Snow ghost map," Letters in Spatial and Resource Sciences, Springer, vol. 18(1), pages 1-11, December.
    • Handle: RePEc:spr:lsprsc:v:18:y:2025:i:1:d:10.1007_s12076-025-00409-y
    DOI: 10.1007/s12076-025-00409-y
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    References listed on IDEAS

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    1. John R. Roy & Jean-Claude Thill, 2004. "Spatial interaction modelling," Advances in Spatial Science, in: Raymond J. G. M. Florax & David A. Plane (ed.), Fifty Years of Regional Science, pages 339-361, Springer.
    2. John R. Roy, 2004. "Spatial Interaction Modelling Embracing Microeconomics," Advances in Spatial Science, in: Spatial Interaction Modelling, chapter 3, pages 74-104, Springer.
    3. Revelli, Federico, 2003. "Reaction or interaction? Spatial process identification in multi-tiered government structures," Journal of Urban Economics, Elsevier, vol. 53(1), pages 29-53, January.
    4. John R. Roy, 2004. "Spatial Interaction Modelling," Advances in Spatial Science, Springer, number 978-3-540-24807-1, February.
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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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