Learning from the COVID-19 pandemic: Concepts for good decision-making Aprendiendo de la pandemia COVID-19: Conceptos para una buena toma de decisionesTo the Editor: 1) Recognizing the enemyCOVID-19 is caused by the SARS-CoV-2 virus, which due to its phylogenetic relationships shows a clear relationship with SARS-CoV-1 (SARS agent) and therefore with a very probable origin in bat reservoir (Macrochiroptera) 1-3 . Bats have more than 76 viruses with human pathogenic potential, such as Rabia, Marburg, Hendra, Nipah, Menangle, Tioman, Ebola, and the SARS and MERS coronaviruses (4) . Therefore this is probably an emerging zoonosis as a consequence of the transgression of the specific barrier, a phenomenon known as spillover.After advanced studies on the subject, a case fatality of 1.38% (95% CrI: 1.23-1.53%) [5][6][7] has been determined, which is not so high compared to other diseases. Although it has caused a large number of deaths, it is not comparable to the number of deaths that TBC or
Este trabajo es una aproximación descriptiva, desde el punto de vista dinámico, a los procesos inferenciales sintéticos de pensamiento. Nosotros asumimos como hipótesis de trabajo que el pensamiento es un tipo particular de sistema dinámico no lineal y definimos esta conjeturas a través de un particular sistema de postulados. Basados en la psicología cognitiva de Piaget y en la teoría del caos y fractales, construimos un paradigma experimental concreto que permite estudiar la dinámica inferencial durante la solución de problemas (Un juego de estrategia conocido como el Combate Naval). El instrumento usado para describir la dinámica inferencial fue la dimensión fractal. La tarea problema fue presentada a los niños. Los resultados obtenidos, usando la dimensión fractal, han permitido a) describir la dinámica inferencial de los sujetos mientras resolvían el problema. b) caracterizar, a través de un modelo (en términos de una función matemática) la forma dinámica del proceder inferencial de cada sujeto de la muestra. Nuestro resultados sugieren que cada niño tiene una unidad dinámica personal y característica durante la generación de hipótesis.
Background: Environmental noise can cause auditory and non-auditory adverse effects. Aim: To identify daily environmental noise patterns in two urban sites of Metropolitan Santiago. Material and Methods: Continuous measurements of environmental noise in two sites of Metropolitan Santiago were analyzed by means of hierarchical cluster analysis. One site was a main street with heavy traffic and the second was a street from a neighborhood with intense nocturnal activity. The first phase of analysis consisted of clustering noise profiles with similar shapes according to the average linkage method, with correlation as the similarity measure. The second phase grouped the profiles with similar shapes into sub-clusters that also had similar absolute noise levels, using the complete linkage method, with absolute distance as the similarity measure. Results: Two noise patterns were identified for the first site, one for weekdays (Monday to Friday) and another for weekends (Saturday and Sunday). For the second site five different patterns were identified (Monday to Wednesday, Thursday, Friday, Saturday, and Sunday). Also different patterns appeared for summer compared to the rest of the year. The noise levels of both sites were high. Conclusions: The detected noise levels can be annoying, cause sleep disturbances and increase the risk for hypertension and cardiovascular diseases, among other effects.
There are four vector species of Chagas disease in Chile: Triatoma infestans, responsible for the domestic cycle; Mepraia spinolai, the main wild vector; and M. gajardoi and M. parapatrica, two coastal wild species whose importance as vectors is not well known. They are species of dry environments of the central-north region of Chile, whose best predictors of distribution are warm average temperatures and low rainfall. They are found in rock quarries, nests of birds, and small mammals, and T. infestans has sylvatic foci associated with a Bromeliaceae species. While human blood represents 70% of the diet of T. infestans, in M. spinolai this value is 7%, which means that a large part of Chagas disease in Chile is due to T. infestans. However, all species have high percentages of T. cruzi infection. Chagas disease in Chile follows the distribution of T. infestans, and although the cycle of domestic transmission by this vector is interrupted, there is still a constant prevalence and mortality and ascending incidences. Models predict that although climate change will not vary greatly the north-south distribution of vectors, it could increase the reproductive number of the disease, increasing risk areas of Chagas disease.
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