Sinking accidents are a seafarer’s nightmare. Using 10 years’ of worldwide sinking accident data, this study aims to develop a mortality count model to evaluate the human life loss resulting from sinking accidents using zero-inflated negative binomial regression approaches. The model results show that the increase of the expected human life loss is the largest when a ship suffers a precedent accident of capsizing, followed by fire/explosion or collisions. Lower human life loss is associated with contact and machinery/hull damage accidents. Consistent with our expectation, cruise ships involved in sinking accidents usually suffer more human life loss than non-cruise ships and there is be a bigger mortality count for sinking accidents that occur far away from the coastal area/harbor/port. Fatalities can be less when the ship is moored or docked. The results of this study are beneficial for policy-makers in proposing efficient strategies to reduce sinking accident mortalities.


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    Title :

    A Zero-Inflated Negative Binomial Regression Model to Evaluate Ship Sinking Accident Mortalities


    Additional title:

    Transportation Research Record


    Contributors:
    Chai, Tian (author) / Xiong, De-qi (author) / Weng, Jinxian (author)


    Publication date :

    2018-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English