This research analyzes lightning activity in Northwestern Mexico from January 1, 2015, to December 31, 2019, and seeks to correlate it with cloud-to-ground (CG) stroke attributed fatalities and social variables. The main purpose of this paper is to define the most relevant social variables in CG stroke fatalities in order to improve our current understanding of lightning hazard. The study’s contributors anticipate that these findings will provide insights to help mitigate the loss of human life in this region. The methodology employed in this study focuses on a geospatial analysis of the CG stroke density per square kilometer related to the 50 deaths that occurred in Northwestern Mexico within the five-year time frame studied. In addition, a social-vulnerability indicator is defined by data provided by governmental agencies to assess risk based on socio-economic conditions, including level of education, access to healthcare services, access to basic human services, housing quality and space, household assets, and poverty level of the population. The social-vulnerability indicator combines available data of the general population in comparison to the occurrence of CG stroke fatalities and can contribute to an improved risk assessment of the CG stroke hazard. This geospatial analysis has found that CG stroke fatalities do not necessarily coincide with higher CG stroke density; however, other variables correlate to CG stroke fatalities statistics, including social vulnerability, population type, seasonality (time of the year), grouped age and occupation. This conclusion was determined by applying a principal component analysis (PCA) technique to the definition of the variables most closely related to CG stroke fatalities for the studied time period and region. In addition, physiographic elements were considered to explore their possible influence on the highest CG stroke density and the occurrence of CG stroke fatalities.
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© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
- CG stroke fatalities
- Geospatial analysis