Incorporating Non-Genetic Evidence in Large Scale Missing Person Searches: A General Approach Beyond Filtering

Mársico, Franco; Caridi, Inés

doi:10.2139/ssrn.4331033

Cited by 2 publications

(17 citation statements)

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“…As described by Evett and Weir [8,36], a fundamental role of the forensic scientist is to provide a statistical weight of the evidence. This formalization, as previously demonstrated in [23], allows the incorporation of various phenomena such as typing errors and methodological inaccuracies, which, if not properly accounted for, could lead to misleading conclusions.…”

Section: Discussionmentioning

confidence: 91%

“…Nevertheless, knowing the error probability from the testimony of a missing person's relative may not be possible in many cases. We encourage forensic professionals to adopt a conservative approach in such cases, setting error rates that avoid over reliance on the source and thus not discounting the possibility of errors, as previously discussed in [23]. An important point is that adding phenotype information does not replace the DNA-based framework; moreover, it could be used as a complementary tool.…”

Section: Discussionmentioning

confidence: 99%

“…The models for biological sex and age have been elaborated in more detail in [23]. Also, a more general definition is available in the Appendix section.…”

Section: Biological Sexmentioning

confidence: 99%

“…As shown in Figure 1a, these data are used to compare MPs with UPs, occasionally through database search [33]. Here we performed an analysis based on previously developed LR models [23] for preliminary investigation data as an introduction to the results section. Figures 1 a-c show the expected distributions of the LR values for different variables such as biological sex (Figure 1a), hair color (Figure 1b) and age (Figure 1c) according to the hypotheses H 1 : UP is MP and H 2 : UP is not MP.…”

Section: Non-genetic Data Gatheringmentioning

confidence: 99%

“…This is common in multiples contexts; for example, when analyzing pigmentation traits such as eye color, hair color, and skin color, assuming independence is unrealistic [27]. This aspect has not been considered by previous approaches [23]. In this work, we also measure the impact of considering these pigmentation traits in combination with genetic information when searching for missing persons.…”

Section: Introductionmentioning

confidence: 99%

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Likelihood Ratios for physical traits in forensic investigations

Marsico,

Egeland

2024

Preprint

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Recent years have seen significant advances in DNA phenotyping, which predicts the physical traits of an unknown person, such as hair, eyes, and skin color, using DNA data. This technique is increasingly used in forensic investigations to identify missing persons, disaster victims, and suspects of crimes. A key contribution of DNA phenotyping is that it allows researchers to search through lists of individuals with similar characteristics, often gathered from testimonies, photographs, and social media data. However, despite their growing relevance, current methods lack comprehensive mathematical models to calculate likelihood ratios that accurately assess the statistical weight of evidence. Our work bridges this gap by developing new likelihood ratio models, validated through computational simulations. In addition, we demonstrate the ability of these models to improve forensic investigations in real-world scenarios. Furthermore, we introduce the R package forensicolors , freely available on CRAN, to facilitate the application of the methodologies developed.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

“…The models for biological sex and age have been elaborated in more detail in [23]. Also, a more general definition is available in the Appendix section.…”

Section: Biological Sexmentioning

confidence: 99%

Section: Non-genetic Data Gatheringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Likelihood Ratios for physical traits in forensic investigations

Marsico,

Egeland

2024

Preprint

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Estimation of Abortions in the Province of Buenos Aires, Argentina: a Bayesian Approach

Paz,

Josid,

Rodríguez

et al. 2023

Preprint

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Abortion is one of the reasons for hospital discharge among women of fertile age in Argentina. The criminalization of abortion prior to the enactment of the Voluntary Interruption of Pregnancy Act (IVE), coupled with the fragmentation of the health system, has hindered the availability of reliable records to quantify induced abortions in the country. Given the lack of information reflecting the magnitude of these practices, it is necessary to perform an accurate estimation to characterize abortion access within the healthcare system. Using a Bayesian approach and abortion records in the province of Buenos Aires in 2021, the incidence of abortions per thousand women of fertile age was estimated. This study, based on a direct case count methodology, is the first of its kind in Argentina. The method used allows for the correction of bias caused by underreporting of practices. An incidence of 29.92 (Credibility Interval, CI95: [29.38; 30.47]) abortions per thousand women of fertile age was obtained during 2021. The results are consistent with previous national research and agree with estimates made for the region. In conclusion, the estimates of abortion incidence highlight its frequency in the lives of people with gestational capacity, underlining the importance of fully guaranteeing the right to comprehensive sexual health through a wide network of abortion access.

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Incorporating Non-Genetic Evidence in Large Scale Missing Person Searches: A General Approach Beyond Filtering

Cited by 2 publications

References 0 publications

Likelihood Ratios for physical traits in forensic investigations

Likelihood Ratios for physical traits in forensic investigations

Estimation of Abortions in the Province of Buenos Aires, Argentina: a Bayesian Approach

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