For SARS-CoV-2, R0 calculations report usually 2-3, biased by PCR testing increases. Covid-19-induced excess mortality is less biased.We used data from Robert Koch Institute on Covid incidence, deaths, and PCR tests and excess mortality to determine early, policy-free R0 estimates with a serial interval of 4.7 days.The PCR-based R0 value was 2.56 (95% CI 2.52-2.60) for Covid-19 cases and 2.03 (95%CI 1.96-2.10) for Covid-19-related deaths. As the number of PCR tests increased, R0 values were corrected accordingly, yielding 1.86 for Covid-19 cases and 1.47 for Covid-19 deaths, excess deaths were 1.34 (95% CI 1.32-1.37).R0 is much lower than previously thought. This fits the observed seasonal pattern of infection across Europe in 2020-2021, including emergence of more contagious escape variants such as delta.One-Sentence SummaryExcess mortality reveals infection speed in Covid-19 is surprisingly low with seasonal infection patterns and escape variants.

IntroductionAutism is a neurodevelopmental disorder characterized by alterations in the intellectual, social, communication, and behavioral capabilities of an individual, and is rarely detected in children before 24 months of age. Early diagnosis and intervention may be more effective at a younger age. Functional connectivity magnetic resonance imaging (fcMRI) of 6-month old infants may be able to identify brain connection patterns related to at least one of the characteristics of autism, which normally appear at 24 months of age, by using a mathematical model to analyze the neuroimaging data.MethodsClinical studies published up to December 2018 that used fcMRI to detect autism in infants were reviewed. The literature databases searched included PubMed, Web of Science, the Trip Database, DynaMed, the Cochrane Library, the International Clinical Trials Registry Platform, and ClinicalTrials.gov. Early assessments of fcMRI analysis were identified through the Early Awareness and Alert System of the Agencia de Evaluación de Tecnologías Sanitarias.ResultsOnly one prospective study of 59 infants at 6-months of age was retrieved. A fcMRI analysis was performed to identify 2,635 pairs of functional connections from 230 brain regions. The infants were subsequently assessed for autism at 24 months of age using gold standard tests. The functional connections correlated with at least one of the behaviors related to autism evaluated at 24 months of age. Eleven infants (19%) were diagnosed with autism at 24 months. Compared with the gold standard test results, the predictive model achieved the following: sensitivity 0.82 (95% confidence interval [CI]: 0.52 - 0.95); specificity 1.00 (95% CI: 0.93–1.00); positive predictive value 1.00 (95% CI: 0.70–1.00); negative predictive value 0.96 (95% CI: 0.87–0.99); and negative likelihood ratio 0.18 (95% CI: 0.05–0.64). Adverse effects were not reported in the study.ConclusionsThe fcMRI analysis could help in early detection of autism and the development of preventive interventions. However, the evidence is sparse and more well-designed studies are needed.

This paper presents a method to generate free-form branched structures from a small number of different constructive elements, based on the postulates of discrete or combinatorial design. The research is based on the study of fractal growth as a generator of complex tree-like structures, using references from other scientific approaches in which the possibilities of the DLA (diffusion-limited aggregation) model have been explored. The proposed method uses the Grasshopper visual programming language, and incorporates new topological strategies to improve the performance or robustness of the system through tree-tree (inosculation) and tree-soil (aerial roots) cooperations. The simulation demonstrates the effectiveness of the proposed method and its potential for the construction of structures with complex geometries from a discrete set of knots and bars and bioinspired strategies. The paper includes a review of the chosen design principles, the developed methodology and a recent physical test in Medellín (Colombia).

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