DNA analysis in disaster victim identification

Montelius, Kerstin; Lindblom, Bertil

doi:10.1007/s12024-011-9276-z

Cited by 59 publications

(36 citation statements)

References 38 publications

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“…As the female victim is a Kyrgyzstan national, there was some issues with the embassy and to obtain the first degree relatives blood. To overcome this issue, another option for AM DNA samples recommended by INTERPOL is the personal objects used by the deceased [3]. Profiles generated from personal objects can be directly compared to the DNAprofiles of victims.…”

Section: Discussionmentioning

confidence: 99%

Secondary identifier for positive identification in DVI

Khoo¹,

Lai²,

Hasmi³

et al. 2016

Forensic Sci Crimino

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In the context of mass fatality incident, it is of utmost importance to identify the victims rapidly and accurately, both for judicial reasons and to provide closure for family members. Disaster Victim Identification (DVI) work is an interdisciplinary manner, engaging the services of experts in various disciplines, comprising of pathologists, anthropologists, odontologists, radiologists, fingerprint and DNA experts to work collaboratively towards the identification of victims. The DVI process is conducted by adopting the fundamental principle where the highest possible quality standards should be applied and victims are to be treated with dignity and respect, in accordance to the internationally recognised INTERPOL DVI guide. The primary identifiers are the most reliable means of identification. They are fingerprint analysis, comparative dental analysis and DNA analysis. Secondary means of identification include personal description, medical findings and medical records as well as evidence and clothing found on the body. Most often than not, secondary identifiers are often used to complement the primary identifiers. However, there is always an exception. This paper highlights a case of the Dauphin helicopter crash in which identifications for all the victims were done using only secondary means of identification. Having said that, victims' bodies were released to family members without awaiting the DNA result. 24 hours later, the DNA analysis results were matched and confirmed the identity of the victims to be correct.

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Section: Discussionmentioning

confidence: 99%

Secondary identifier for positive identification in DVI

Khoo¹,

Lai²,

Hasmi³

et al. 2016

Forensic Sci Crimino

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“…direct profile matching. This may necessitate sampling from sources including tooth brushes, razors, brushes, combs, hats, underwear and dental appliances where it is known that the missing person's DNA is most likely to be located (Montelius and Lindblom 2012). To avoid erroneous DNA mixtures, the expert has to ensure that the items can only have been used by the missing person and cross checking between these different sources will ensure that a robust profile is secured.…”

Section: Primary Methods Of Identificationmentioning

confidence: 99%

5. Forensic Identification

Edkins¹

2017

Missing

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“…Here we expand on victim identification, making the simplifying assumption that there is no commingling of remains so that we are solely attempting to make identifications. Rather than working directly with posterior probabilities as in the previous section, we will work with likelihood ratios and prior odds as this is much more common in the disaster victim and personal identification literature (Goodwin et al, 1999;Adams, 2003b;Brenner and Weir, 2003;Alonso et al, 2005;Christensen, 2005;Lin et al, 2006;Steadman et al, 2006;Prinz et al, 2007;Kaye, 2009;Budowle et al, 2011;Butler, 2011;Hartman et al, 2011;Abraham et al, 2012;Montelius and Lindblom, 2012;Jackson and Black, 2013). As mentioned above, likelihood ratios from DNA are typically reported as the inverse of the population frequency for the matched (between ante-mortem and post-mortem) genotype, although this is only possible when a "direct reference" ante-mortem sample is available (so that the numerator is equal to 1.0).…”

Section: Identification In a "Closed Population" Mass Disastermentioning

confidence: 99%

Bayes in biological anthropology

Konigsberg

Frankenberg

2013

American J Phys Anthropol

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In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available. Am J Phys Anthropol 57: 2013. V C 2013 Wiley Periodicals, Inc."The Bayesian approach can have a clarifying effect on one's thinking about evidence." (Koehler and Saks, 1991, p 364) Traditional training in statistical methods for those who go on to become practicing biological anthropologists has focused primarily on classical hypothesis testing. This is apparent in both textbooks geared toward anthropologists in general (Thomas, 1986;Madrigal, 1998;Bernard, 2011) and specialized texts for biological anthropologists (Slice, 2005;D'Aoãut and Vereecke, 2011). While Bayes' Theorem may be mentioned in passing in introductory statistics courses, this is typically restricted to examples of such limited interest that the student has little motivation to recall the theorem, and even less motivation to assume that there may be future value in having learned about Bayes' Theorem. In Bayesian terms, the prior probability that the student will retain Bayes' Theorem is quite low. In contrast, the student and eventual practitioner is likely to learn about confidence intervals, Type I and Type II errors in hypothesis testing, and P-values, and to blithely assume that what they have learned represents the near totality of what is available and useful within modern statistical practice. This represents an unfortunate omission of Ba...

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DNA analysis in disaster victim identification

Cited by 59 publications

References 38 publications

Secondary identifier for positive identification in DVI

Secondary identifier for positive identification in DVI

5. Forensic Identification

Bayes in biological anthropology

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