Incorporating non-genetic evidence in large scale missing person searches: A general approach beyond filtering.

The search for missing persons implies several steps, from the preliminary investigation that involves collecting background data related to the case to the genetic kinship testing. Despite its crucial importance in identifications, only some approaches mathematically formalize the possibility of using preliminary investigation data. In some cases, a filtering strategy is applied, which implies selecting a subset of possible victims where some non-genetic variables perfectly match those of the missing. Through a Bayesian approach, we propose a mathematical model for computing the prior odds based on non-genetic variables usually collected during the preliminary investigation, such as biological sex, hair colour, and age. We use computational simulations to show how to incorporate these prior odds in DNA-database searches. Importantly, our results suggest that applying the proposed model leads to better search performance in underpowered cases from the genetic point of view, where few or distant relatives of the missing person are available for genotyping. Furthermore, the results are also helpful when using non-genetic data for prior odds in well-powered cases, where genetic data are enough to reach a reliable conclusion. It performs better than other approaches, such as using non-genetic data for filtering. The software mispitools, freely available on CRAN, implements all described methods (https://CRAN.R-project.org/package=mispitools).

Exposure to parks through the lens of urban mobility.

This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city's information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities' distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities' tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city. Supplementary Information: The online version contains supplementary material available at 10.1140/epjds/s13688-022-00351-9.

Hospitalized population diagnosed with Covid-19 in public health centers in the southeastern region of Greater Buenos Aires / [Población hospitalizada con diagnóstico de Covid-19 en los centros de salud públicos de la región sudeste del Gran Buenos Aires]

Introduction: The present work describes the clinical characteristics and interventions to minimize morbidity and mortality in hospitalized patients diagnosed with COVID-19. Methods: It is a prospective cohort investigation of patients who received a response from the Health Centers in the southeast region (RS) of the metropolitan area (AMBA) from April 8 to September 30, 2020. A Situation Room was used epidemiological with two monitoring and follow-up boards, one for bed management and the other for patient management. Results: During the analyzed period, 2,588 patients with confirmed COVID-19 diagnosis were admitted, 1,943 with suspected COVID-19 pathology, and 1,464 subjects with other pathologies. 55% of the patients were men and the mean age was 51 years. There were 82.8% patients with pre-existing diseases, hypertension and diabetes were the most frequent. 14% were hospitalized in the Intensive Care Unit. The mortality of the cohort was 15.05%, mortality was higher for men, with a mean age of 60 years, 92.65% had some pre-existing disease. Conclusion: Our cohort is younger than other published works. Older people, men, and people with comorbidities are at increased risk for COVID-19-related mortality. The public health system was able to respond to the demand without collapsing the hospital institutions.

Introducción: En el presente trabajo se describen las características clínicas y las intervenciones para minimizar la morbimortalidad en pacientes hospitalizados con diagnóstico de COVID-19. Métodos: Es una investigación de cohorte prospectiva de pacientes que recibieron respuesta de los Centros de Salud en la región sudeste (RS) del área metropolitana (AMBA) desde el 8 de abril hasta el 30 de septiembre de 2020. Se utilizó una Sala de Situación epidemiológica con dos tableros de monitoreo y seguimiento, uno de gestión de camas y otro de gestión de pacientes. Resultados: Durante el periodo analizado se internaron2.588pacientes con diagnóstico COVID-19 confirmados, 1.943 con sospecha de patología COVID-19, y 1.464sujetos con otras patologías. El 55% de los pacientes eran hombres y la edad media fue de 51 años. Hubo 82,8% pacientes con enfermedades preexistentes, hipertensión y diabetes fueron las más frecuentes. El 14% fue hospitalizado en la Unidad de Terapia Intensiva. La mortalidad de la cohorte fue del 15,05%, la mortalidad fue mayor para los hombres, con una edad media de 60 años, el 92,65% tenía alguna enfermedad preexistente. Conclusión: Nuestra cohorte es más joven que otros trabajos publicados. Las personas mayores, los hombres y las personas con comorbilidades tienen mayor riesgo de mortalidad relacionada con COVID-19. El sistema de salud público pudo responder a la demanda sin llegar a colapsar las instituciones hospitalarias.

Using already-solved cases of a mass disaster event for prioritizing the search among remaining victims: a Bayesian approach.

This work presents a new method for assisting in the identification process of missing persons in several contexts, such as enforced disappearances. We apply a Bayesian technique to incorporate non-genetic variables in the construction of prior information. In that way, we can learn from the already-solved cases of a particular mass event of death, and use that information to guide the search among remaining victims. This paper describes a particular application to the proposed method to the identification of human remains of the so-called disappeared during the last dictatorship in Argentina, which lasted from 1976 until 1983. Potential applications of the techniques presented hereby, however, are much wider. The central idea of our work is to take advantage of the already-solved cases within a certain event to use the gathered knowledge to assist in the investigation process, enabling the construction of prioritized rankings of victims that could correspond to each certain unidentified human remains.

Properties of interaction networks underlying the minority game.

The minority game is a well-known agent-based model with no explicit interaction among its agents. However, it is known that they interact through the global magnitudes of the model and through their strategies. In this work we have attempted to formalize the implicit interactions among minority game agents as if they were links on a complex network. We have defined the link between two agents by quantifying the similarity between them. This link definition is based on the information of the instance of the game (the set of strategies assigned to each agent at the beginning) without any dynamic information on the game and brings about a static, unweighed and undirected network. We have analyzed the structure of the resulting network for different parameters, such as the number of agents (N) and the agent's capacity to process information (m), always taking into account games with two strategies per agent. In the region of crowd effects of the model, the resulting networks structure is a small-world network, whereas in the region where the behavior of the minority game is the same as in a game of random decisions, networks become a random network of Erdos-Renyi. The transition between these two types of networks is slow, without any peculiar feature of the network in the region of the coordination among agents. Finally, we have studied the resulting static networks for the full strategy minority game model, a maximal instance of the minority game in which all possible agents take part in the game. We have explicitly calculated the degree distribution of the full strategy minority game network and, on the basis of this analytical result, we have estimated the degree distribution of the minority game network, which is in accordance with computational results.