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ABSTRACTBackgroundThe weekend effect has been extensively observed for different diseases and countries and recognized as a fact but without obvious causes.ObjectivesIn this paper we first aimed at investigating the existence of a periodicity in the death count due to Covid-19, and second, at opening the discussion concerning the reality of this effect in this particular context.MethodsDaily statistics of deaths due to the Covid-19 pandemic were subjected to a discrete Fourier transform spectral analysis for France and the world, over the periods from March 29 to May 16, 2020 and from January 22 to May 18, 2020 respectively.ResultsIn both cases, a frequency peak of one harmonic corresponding to a period of 7.11 days was observed for France and the world. In France, this weekly frequency corresponds to a decrease in deaths every Sunday, whereas for the world the systematic decrease is shifted on average by 1.5 days and corresponds to Saturday or Friday.ConclusionAt the world scale and for the epidemic period we confirm the existence of a consecutive weekend effect in the context of the Covid-19 pandemic.

We thank the wet laboratory teams at MPI-SHH, the PalaeoBARN at the University of Oxford and the University of York. We thank David K. James and Lucia Hui of the Alameda County Vector Control Services District for procuring the rat used for the de novo genome. We are grateful to Sarah Nagel at Max Planck Institute for the Evolutionary Anthropology for the single-stranded library preparation, and Dovetail Genomics for the de novo genome assembly service. We thank Maria Spyrou for her suggestions and comments. We acknowledge Ewan Chipping and Helena England (University of York), Carl Phillips, Veronica Lindholm (Ålands Museum), Christine McDonnell and Nienke van Doorn (York Archaeological Trust), Emile Mittendorf (Gemeente Deventer), Inge Riemersma (Archaeological depot, Provincie Zuid-Holland), the Turkish Ministry of Culture & Tourism, Jan Frolík and Iva Herichová (Institute of Archaeology of the Czech Academy of Sciences, Prague), Franz Humer and Eduard Pollhammer (Archaeological Park Carnuntum), Dorottya B. Nyékhelyi and László Daróczi-Szabó (Budapest History Museum), Institut National du Patrimoine (Tunisia), University of Barcelona, Spanish Ministry of Science and Innovation (Project HUM2006-03432/HIST), Spanish Ministry of Culture (program of archaeological excavations abroad 2009); Spanish Agency of International Cooperation for the Development (2009), Catalan Institute of Classical Archaeology (ICAC), Vujadin Ivanisević, Nemanja Marković and Ivan Bugarski (Archaeological Institute 809 Belgrade), the Field Museum Chicago, the British National History Museum and the American Museum of Natural History for providing materials and support. G.L. and A.J. were supported by the ERC (grant ERC-2013-StG-337574-UNDEAD) and A.J. was supported by the Natural Environment Research Council Doctoral Training Program. D.O. was supported by Wellcome (Small Grant in Humanities and Social Science 209817/Z) and the British Academy / Leverhulme Trust (Small Research Grant SG170938). E.R. was supported by Estonian Research Council grant No PRG29. R.K. was supported by the Czech Academy of Sciences institutional support (RVO:67985912). S.V.-L. was supported by the ERC (grant ERC-StG- 716298 ZooMWest). H.E. was funded by an ERC grant (206148) through the Sealinks Project. A.H.B was funded by the Leverhulme Trust (ECF-2017-315). The de novo genome assembly, population genomics study, and radiocarbon dating were funded by the Max Planck Society. The distribution of the black rat (Rattus rattus) has been heavily influenced by its association with humans. The dispersal history of this non-native commensal rodent across Europe, however, remains poorly understood, and different introductions may have occurred during the Roman and medieval periods. Here, in order to reconstruct the population history of European black rats, we generated a de novo genome assembly of the black rat, 67 ancient black rat mitogenomes and 36 ancient nuclear genomes from sites spanning the 1st-17th centuries CE in Europe and North Africa. Analyses of mitochondrial DNA confirm that black rats were introduced into the Mediterranean and Europe from Southwest Asia. Genomic analyses of the ancient rats reveal a population turnover in temperate Europe between the 6th and 10th centuries CE, coincident with an archaeologically attested decline in the black rat population. The near disappearance and re-emergence of black rats in Europe may have been the result of the breakdown of the Roman Empire, the First Plague Pandemic, and/or post-Roman climatic cooling. Peer reviewed

When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the comprehensiveness of many widely established models, the official figures that recount the course of the outbreak still sketch a largely elusive and intimidating picture. Here we show unambiguously that the dynamics of the COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. Our analysis naturally leads us to establish that there exists a fundamental limitation to any theoretical approach, namely the unpredictable non-stationarity of the testing frames behind the reported figures. However, we show how such bias can be quantified self-consistently and employed to mine useful and accurate information from the data. In particular, we describe how the time evolution of the reporting rates controls the occurrence of the apparent epidemic peak, which typically follows the true one in countries that were not vigorous enough in their testing at the onset of the outbreak. The importance of testing early and resolutely appears as a natural corollary of our analysis, as countries that tested massively at the start clearly had their true peak earlier and less deaths overall. Comment: main paper + supplementary material

The recent emergence of the SARS-CoV-2 in China has raised the spectre of a novel, potentially catastrophic pandemic in both scientific and lay communities throughout the world. In this particular context, people have been accused of being excessively pessimistic regarding the future consequences of this emerging health threat. However, consistent with previous research in social psychology, a large survey conducted in Europe in the early stage of the COVID-19 epidemic shows that the majority of respondents was actually overly optimistic about the risk of infection. https://psyarxiv.com/364qj/

Abstract Objectives During periods such as the COVID-19 crisis, there is a need for responsive public health surveillance indicators related to the epidemic and to preventative measures such as lockdown. The automatic classification of the content of calls to emergency medical communication centers could provide relevant and responsive indicators. Methods We retrieved all 796,209 free-text call reports from the emergency medical communication center of the Gironde department, France, between 2018 and 2020. We trained a natural language processing neural network model with a mixed unsupervised/supervised method to classify all reasons for calls in 2020. Validation and parameter adjustment were performed using a sample of 20,000 manually-coded free-text reports. Results The number of daily calls for flu-like symptoms began to increase from February 21, 2020 and reached an unprecedented level by February 28, 2020 and peaked on March 14, 2020, 3 days before lockdown. It was strongly correlated with daily emergency room admissions, with a delay of 14 days. Calls for chest pain, stress, but also those mentioning dyspnea, ageusia and anosmia peaked 12 days later. Calls for malaises with loss of consciousness, non-voluntary injuries and alcohol intoxications sharply decreased, starting one month before lockdown. Discussion This example of the COVID-19 crisis shows how the availability of reliable and unbiased surveillance platforms can be useful for a timely and relevant monitoring of all events with public health consequences. The use of an automatic classification system using artificial intelligence makes it possible to free itself from the context that could influence a human coder, especially in a crisis situation. Conclusion The content of calls to emergency medical communication centers is an efficient epidemiological surveillance data source that provides insights into the societal upheavals induced by a health crisis.

COVID-19 mortality increases markedly with age and is also substantially higher among Black, Indigenous, and People of Color (BIPOC) populations in the United States. These two facts can have conflicting implications because BIPOC populations are younger than white populations. In analyses of California and Minnesota—demographically divergent states—we show that COVID vaccination schedules based solely on age benefit the older white populations at the expense of younger BIPOC populations with higher risk of death from COVID-19. We find that strategies that prioritize high-risk geographic areas for vaccination at all ages better target mortality risk than age-based strategies alone, although they do not always perform as well as direct prioritization of high-risk racial/ethnic groups. Vaccination schemas directly implicate equitability of access, both domestically and globally. Age-based COVID-19 vaccination prioritizes white people above higher-risk others; geographic prioritization improves equity. Description

Abstract The Covid-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides measures of subjective time and related processes from more than 2,800 participants (over 9 countries) tested on 14 questionnaires and 15 behavioral tasks during the Covid-19 pandemic. The easy-to-process database and all data collection tools are made fully accessible to researchers interested in studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception, and mindfulness. Blursday also includes vital quantitative statistics such as sleep patterns, personality traits, psychological well-being, and lockdown indices. Herein, we exemplify the use of the database with novel quantitative insights on the effects of lockdown (stringency, mobility) and subjective confinement on time perception (duration, passage of time, temporal distances). We show that new discoveries are possible as illustrated by an inter-individual central tendency effect in retrospective duration estimation.