Spatial identification of potential health hazards: A systematic areal search approach

Alina Svechkina, Marina Zusman, Natalya Rybnikova, Boris A. Portnov

Research output: Contribution to journalArticlepeer-review


Background and aims: Large metropolitan areas often exhibit multiple morbidity hotspots. However, the identification of specific health hazards, associated with the observed morbidity patterns, is not always straightforward. In this study, we suggest an empirical approach to the identification of specific health hazards, which have the highest probability of association with the observed morbidity patterns. Methods: The morbidity effect of a particular health hazard is expected to weaken with distance. To account for this effect, we estimate distance decay gradients for alternative locations and then rank these locations based on the strength of association between the observed morbidity and wind-direction weighted proximities to these locations. To validate this approach, we use both theoretical examples and a case study of the Greater Haifa Metropolitan Area (GHMA) in Israel, which is characterized by multiple health hazards. Results: In our theoretical examples, the proposed approach helped to identify correctly the predefined locations of health hazards, while in the real-world case study, the main health hazard was identified as a spot in the industrial zone, which hosts several petrochemical facilities. Conclusion: The proposed approach does not require extensive input information and can be used as a preliminary risk assessment tool in a wide range of environmental settings, helping to identify potential environmental risk factors behind the observed population morbidity patterns.

Original languageAmerican English
Article number5
JournalInternational Journal of Health Geographics
Issue number1
StatePublished - 7 Feb 2017


  • Disease hotspots
  • Multivariate regression analysis
  • Receptor-oriented models
  • Source-oriented models
  • Systematic search approach
  • Wind adjustment

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health
  • General Computer Science
  • General Business,Management and Accounting


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