Memory-based meso-scale modeling of Covid-19

Abstract The COVID-19 pandemic has led to an unprecedented world-wide effort to gather data, model, and understand the viral spread. Entire societies and economies are desperate to recover and get back to normality. However, to this end accurate models are of essence that capture both the viral spread and the courses of disease in space and time at reasonable resolution. Here, we combine a spatially resolved county-level infection model for Germany with a memory-based integro-differential approach capable of directly including medical data on the course of disease, which is not possible when using traditional SIR-type models. We calibrate our model with data on cumulative detected infections and deaths from the Robert-Koch Institute and demonstrate how the model can be used to obtain county- or even city-level estimates on the number of new infections, hospitality rates and demands on intensive care units. We believe that the present work may help guide decision makers to locally fine-tune their expedient response to potential new outbreaks in the near future

Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany

The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come

Herkunftsvergleich Karpfen: Vergleich der Eignung verschiedener Gebrauchskarpfenbestände (Cyprinus carpio L.) zur Teichaufzucht unter Verwendung des „Communal testings“ und Zuordnung von Herkünften über Mikrosatellitenmarkeranalysen

Die Leistung sächsischer Teichkarpfen wurde mit genetisch und räumlich weit entfernten europäischen Zuchtlinien verglichen. Zwischen den ausgewählten Herkünften des Karpfens konnten deutliche Leistungsunterschiede festgestellt werden. Es gab jedoch keine Herkunft, die in allen geprüften Belangen den anderen deutlich überlegen war. Herausragend positive Ergebnisse hinsichtlich ihrer Eignung für die Teichaufzucht erreichten Schuppenkarpfen einer tschechischen Herkunft. Im Ergebnis der Untersuchungen werden Empfehlungen für die praktische Zuchtarbeit in Karpfenvermehrungsbetrieben gegeben

Synchronous and proportional deglacial changes in Atlantic meridional overturning and northeast Brazilian precipitation

Changes in heat transport associated with fluctuations in the strength of the Atlantic meridional overturning circulation (AMOC) are widely considered to affect the position of the Intertropical Convergence Zone (ITCZ), but the temporal immediacy of this teleconnection has to date not been resolved. Based on a high-resolution marine sediment sequence over the last deglaciation, we provide evidence for a synchronous and near-linear link between changes in the Atlantic interhemispheric sea surface temperature difference and continental precipitation over northeast Brazil. The tight coupling between AMOC strength, sea surface temperature difference, and precipitation changes over northeast Brazil unambiguously points to a rapid and proportional adjustment of the ITCZ location to past changes in the Atlantic meridional heat transport

Quantifying sources of variability in infancy research using the infant-directed-speech preference

Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult in North American English were created using seminaturalistic laboratory-based audio recordings. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three common methods for measuring infants’ discrimination (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s d) was 0.35, 95% confidence interval = [0.29, 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together, these findings replicate the IDS preference but suggest that its magnitude is modulated by development, native-language experience, and testing procedure. (This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 798658.

The benefit of collaboration: Disentangling the sources of synergy in group judgments

The performance of groups is often seen skeptical because in many tasks, groups seem to be unable to reach their full potential. However, recent research points to one task domain, where the implementation of groups might be beneficial: quantitative judgments. Accordingly, this current work investigates the group performance in quantitative judgments tasks by disentangling the underlining judgment error structures and group mechanisms. While the first manuscript investigates group-to-individual transfer (G-I transfer), the improvement of the members’ individual performance due to their prior participation in a group, the second manuscript takes on a meta-analytic approach on group judgments. The findings show that group judgments can be highly accurate and that group members do benefit from the group work by improving their individual accuracy.2022-02-1