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Prediction of survival time at sea based on observed body cooling rates.

Authors: P, Tikuisis;

Prediction of survival time at sea based on observed body cooling rates.

Abstract

The prediction of survival time (ST) of individuals stranded at sea is particularly difficult since reliable controlled data are unavailable. An individual's rate of body cooling is governed by the difference between heat loss and heat production. It has been suggested that the rate of deep body cooling can be extrapolated to estimate ST. The observed linearity of this cooling rate against water temperature is consistent with the predictions of an independently-developed mathematical model of ST. This model has been extended to simulate conditions of partial immersion and wet clothing, and subsequently calibrated against observed human cooling rates. The resultant modification allows a much broader range of ST predictions involving calm and rough seas, and non-immersion wet conditions. Predictions are presented for lean vs. fat individuals, a "worst" case scenario where shivering is absent, and partial immersion. While these predictions must be considered speculative and subject to change as better information becomes available, the model can be useful as a decision aid. It would be prudent, however, to consider the predictions in a relative vs. absolute sense; i.e., for comparative purposes.

Keywords

Survival, Shivering, Hypothermia, Models, Theoretical, Models, Biological, Body Temperature, Clothing, Cold Temperature, Thinness, Immersion, Humans, Forecasting

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
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