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- Publication . Preprint . Article . 2020Open Access EnglishAuthors:Cédric Gil-Jardiné; Gabrielle Chenais; Catherine Pradeau; Eric Tentillier; Philipe Revel; Xavier Combes; Michel Galinski; Eric Tellier; Emmanuel Lagarde;Cédric Gil-Jardiné; Gabrielle Chenais; Catherine Pradeau; Eric Tentillier; Philipe Revel; Xavier Combes; Michel Galinski; Eric Tellier; Emmanuel Lagarde;Publisher: HAL CCSDCountry: France
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.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Preprint . Article . 2020Open Access EnglishAuthors:Timoteo Carletti; Duccio Fanelli; Francesco Piazza;Timoteo Carletti; Duccio Fanelli; Francesco Piazza;
pmc: PMC7297692
Publisher: ElsevierCountry: BelgiumWhen 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. Highlights • COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. • The unpredictable non-stationarity of the testing frames behind the figures reported by national authorities sets a fundamental limitation to any theoretical approach. • 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.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Article . Preprint . 2021Open Access EnglishAuthors:Mazhar Mughal; Rashid Javed;Mazhar Mughal; Rashid Javed;Publisher: HAL CCSDCountry: France
An aspect of the Covid-19 pandemic that merits attention is its effects on marriage and childbirth. Although the direct fertility effects of people getting the virus may be minor, the impact of delayed marriages due to the first preventive lockdown, such as that imposed in Pakistan from March 14 to May 8 2020, and the closure of marriage halls that lasted till September 14 may be non-negligible. These demographic consequences are of particular import to developing countries such as Pakistan where birth rates remain high, marriage is nearly universal, and almost all child-bearing takes place within marriage. Based on historic marriage patterns, we estimate that the delay in nuptiality during the first wave of coronavirus outbreak may affect about half of the marriages that were to take place during the year. In Pakistan, childbearing begins soon after marriage, and about 37% of Pakistani married women give birth to their first child within twelve months of marriage. A sizeable number out of these around 400,000 annual births that occur within twelve months of the marriage may consequently be delayed. Postponement of marriages due to the accompanying difficult economic situation and employment precariousness should accentuate this fertility effect. The net fertility impact of the Covid-19 outbreak would ultimately depend not only on the delay in marriages but also on the reproductive behavior of existing couples.; Un aspect de la pandémie de Covid-19 qui mérite une attention particulière concerne ses effets sur le mariage et la naissance des enfants. Les conséquences démographiques sont particulièrement importantes pour les pays en développement tels que le Pakistan. Dans ce pays, le taux de natalité est élevé, le mariage est presque universel et la procréation se fait exclusivement dans le cadre dumariage. Bien que les effets directs du virus sur la fertilité des personnes infectées puissent être moins importants, l'impact des mariages retardés en raison des mesures de confinement tecomme celles qui avaient cours au Pakistan du 14 mars au 8 mai 2020, et de la fermeture des salles de mariage qui a duré jusqu'au 14 septembre peut être sérieux. Sur la base des modèles de mariage historiques, nous estimons que le retard de la nuptialité pendant la première vague de la pandémie de coronavirus pourrait affecter environ la moitié des mariages qui devaient avoir lieu pendant l'année. Au Pakistan, la réproduction commence peu après le mariage et environ 37 % des femmes mariées pakistanaises donnent naissance à leur premier enfant dans les douze mois suivant leur mariage. Un nombre non négligeable des 400 000 naissances annuelles qui surviennent dans les douze mois suivant le mariage pourrait donc être retardé. Le report des mariages en raison d'une situation économique difficile et de la précarité de l'emploi devrait accentuer cet effet sur la fécondité. En fin, l'impact net de l'épidémie de Covid-19 sur la fécondité dépendrait en fin de compte non seulement du report des mariages, mais aussi du comportementdes couples existants en matière de reproduction.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Other literature type . Preprint . Article . 2022Open Access EnglishAuthors:He Yu; Alexandra Jamieson; Ardern Hulme-Beaman; Chris J. Conroy; Becky Knight; Camilla Speller; Hiba Al-Jarah; Heidi Eager; Alexandra Trinks; G. Adikari; +49 moreHe Yu; Alexandra Jamieson; Ardern Hulme-Beaman; Chris J. Conroy; Becky Knight; Camilla Speller; Hiba Al-Jarah; Heidi Eager; Alexandra Trinks; G. Adikari; Henriette Baron; Beate Böhlendorf-Arslan; Wijerathne Bohingamuwa; Alison Crowther; Thomas Cucchi; Kinie Esser; Jeffrey Fleisher; Louisa Gidney; E. V. Gladilina; Pavel Gol'din; Steven M. Goodman; Sheila Hamilton-Dyer; Richard F. Helm; Chris Hillman; Nabil Kallala; Hanna Kivikero; Zsófia E. Kovács; Günther Karl Kunst; René Kyselý; Anna Linderholm; Bouthéina Maraoui-Telmini; Arturo Morales-Muñiz; Mariana Nabais; Terry O'Connor; Tarek Oueslati; Quintana Morales; Eréndira M.; Kerstin Pasda; Jude Perera; Nimal Perera; Silvia Radbauer; Joan Ramon; Eve Rannamäe; Joan Sanmartí Grego; Edward R. Treasure; Silvia Valenzuela-Lamas; Inge van der Jagt; Wim Van Neer; Jean-Denis Vigne; Thomas Walker; Stephanie Wynne-Jones; Jørn Zeiler; Keith Dobney; Nicole Boivin; Jeremy B. Searle; Ben Krause-Kyora; Johannes Krause; Greger Larson; David Orton;Countries: United Kingdom, France, Belgium, Spain, Australia
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
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Other literature type . Preprint . 2020EnglishAuthors:Edmond, Jennifer; Basaraba, Nicole; Doran, Michelle; Garnett, Vicky; Grile, Courtney Helen; Papaki, Eliza; Tóth-Czifra, Erzsébet;Edmond, Jennifer; Basaraba, Nicole; Doran, Michelle; Garnett, Vicky; Grile, Courtney Helen; Papaki, Eliza; Tóth-Czifra, Erzsébet;Publisher: HAL CCSDCountry: France
- Publication . Preprint . 2020Open Access EnglishAuthors:Jocelyn Raude; Marion Debin; Cécile Souty; Caroline Guerris; Iclement Turbelin; Alessandra Falchi; Isabelle Bonmarin; Daniela Paolotti; Yamir Moreno; Chinelo Obi; +5 moreJocelyn Raude; Marion Debin; Cécile Souty; Caroline Guerris; Iclement Turbelin; Alessandra Falchi; Isabelle Bonmarin; Daniela Paolotti; Yamir Moreno; Chinelo Obi; Jim Duggan; Ania Wisnia; Antoine Flahault; Thierry Blanchon; Vittoria Colizza;Publisher: HAL CCSDCountry: France
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/
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.
6 Research products, page 1 of 1
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- Publication . Preprint . Article . 2020Open Access EnglishAuthors:Cédric Gil-Jardiné; Gabrielle Chenais; Catherine Pradeau; Eric Tentillier; Philipe Revel; Xavier Combes; Michel Galinski; Eric Tellier; Emmanuel Lagarde;Cédric Gil-Jardiné; Gabrielle Chenais; Catherine Pradeau; Eric Tentillier; Philipe Revel; Xavier Combes; Michel Galinski; Eric Tellier; Emmanuel Lagarde;Publisher: HAL CCSDCountry: France
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.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Preprint . Article . 2020Open Access EnglishAuthors:Timoteo Carletti; Duccio Fanelli; Francesco Piazza;Timoteo Carletti; Duccio Fanelli; Francesco Piazza;
pmc: PMC7297692
Publisher: ElsevierCountry: BelgiumWhen 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. Highlights • COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. • The unpredictable non-stationarity of the testing frames behind the figures reported by national authorities sets a fundamental limitation to any theoretical approach. • 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.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Article . Preprint . 2021Open Access EnglishAuthors:Mazhar Mughal; Rashid Javed;Mazhar Mughal; Rashid Javed;Publisher: HAL CCSDCountry: France
An aspect of the Covid-19 pandemic that merits attention is its effects on marriage and childbirth. Although the direct fertility effects of people getting the virus may be minor, the impact of delayed marriages due to the first preventive lockdown, such as that imposed in Pakistan from March 14 to May 8 2020, and the closure of marriage halls that lasted till September 14 may be non-negligible. These demographic consequences are of particular import to developing countries such as Pakistan where birth rates remain high, marriage is nearly universal, and almost all child-bearing takes place within marriage. Based on historic marriage patterns, we estimate that the delay in nuptiality during the first wave of coronavirus outbreak may affect about half of the marriages that were to take place during the year. In Pakistan, childbearing begins soon after marriage, and about 37% of Pakistani married women give birth to their first child within twelve months of marriage. A sizeable number out of these around 400,000 annual births that occur within twelve months of the marriage may consequently be delayed. Postponement of marriages due to the accompanying difficult economic situation and employment precariousness should accentuate this fertility effect. The net fertility impact of the Covid-19 outbreak would ultimately depend not only on the delay in marriages but also on the reproductive behavior of existing couples.; Un aspect de la pandémie de Covid-19 qui mérite une attention particulière concerne ses effets sur le mariage et la naissance des enfants. Les conséquences démographiques sont particulièrement importantes pour les pays en développement tels que le Pakistan. Dans ce pays, le taux de natalité est élevé, le mariage est presque universel et la procréation se fait exclusivement dans le cadre dumariage. Bien que les effets directs du virus sur la fertilité des personnes infectées puissent être moins importants, l'impact des mariages retardés en raison des mesures de confinement tecomme celles qui avaient cours au Pakistan du 14 mars au 8 mai 2020, et de la fermeture des salles de mariage qui a duré jusqu'au 14 septembre peut être sérieux. Sur la base des modèles de mariage historiques, nous estimons que le retard de la nuptialité pendant la première vague de la pandémie de coronavirus pourrait affecter environ la moitié des mariages qui devaient avoir lieu pendant l'année. Au Pakistan, la réproduction commence peu après le mariage et environ 37 % des femmes mariées pakistanaises donnent naissance à leur premier enfant dans les douze mois suivant leur mariage. Un nombre non négligeable des 400 000 naissances annuelles qui surviennent dans les douze mois suivant le mariage pourrait donc être retardé. Le report des mariages en raison d'une situation économique difficile et de la précarité de l'emploi devrait accentuer cet effet sur la fécondité. En fin, l'impact net de l'épidémie de Covid-19 sur la fécondité dépendrait en fin de compte non seulement du report des mariages, mais aussi du comportementdes couples existants en matière de reproduction.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Other literature type . Preprint . Article . 2022Open Access EnglishAuthors:He Yu; Alexandra Jamieson; Ardern Hulme-Beaman; Chris J. Conroy; Becky Knight; Camilla Speller; Hiba Al-Jarah; Heidi Eager; Alexandra Trinks; G. Adikari; +49 moreHe Yu; Alexandra Jamieson; Ardern Hulme-Beaman; Chris J. Conroy; Becky Knight; Camilla Speller; Hiba Al-Jarah; Heidi Eager; Alexandra Trinks; G. Adikari; Henriette Baron; Beate Böhlendorf-Arslan; Wijerathne Bohingamuwa; Alison Crowther; Thomas Cucchi; Kinie Esser; Jeffrey Fleisher; Louisa Gidney; E. V. Gladilina; Pavel Gol'din; Steven M. Goodman; Sheila Hamilton-Dyer; Richard F. Helm; Chris Hillman; Nabil Kallala; Hanna Kivikero; Zsófia E. Kovács; Günther Karl Kunst; René Kyselý; Anna Linderholm; Bouthéina Maraoui-Telmini; Arturo Morales-Muñiz; Mariana Nabais; Terry O'Connor; Tarek Oueslati; Quintana Morales; Eréndira M.; Kerstin Pasda; Jude Perera; Nimal Perera; Silvia Radbauer; Joan Ramon; Eve Rannamäe; Joan Sanmartí Grego; Edward R. Treasure; Silvia Valenzuela-Lamas; Inge van der Jagt; Wim Van Neer; Jean-Denis Vigne; Thomas Walker; Stephanie Wynne-Jones; Jørn Zeiler; Keith Dobney; Nicole Boivin; Jeremy B. Searle; Ben Krause-Kyora; Johannes Krause; Greger Larson; David Orton;Countries: United Kingdom, France, Belgium, Spain, Australia
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
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Publication . Other literature type . Preprint . 2020EnglishAuthors:Edmond, Jennifer; Basaraba, Nicole; Doran, Michelle; Garnett, Vicky; Grile, Courtney Helen; Papaki, Eliza; Tóth-Czifra, Erzsébet;Edmond, Jennifer; Basaraba, Nicole; Doran, Michelle; Garnett, Vicky; Grile, Courtney Helen; Papaki, Eliza; Tóth-Czifra, Erzsébet;Publisher: HAL CCSDCountry: France
- Publication . Preprint . 2020Open Access EnglishAuthors:Jocelyn Raude; Marion Debin; Cécile Souty; Caroline Guerris; Iclement Turbelin; Alessandra Falchi; Isabelle Bonmarin; Daniela Paolotti; Yamir Moreno; Chinelo Obi; +5 moreJocelyn Raude; Marion Debin; Cécile Souty; Caroline Guerris; Iclement Turbelin; Alessandra Falchi; Isabelle Bonmarin; Daniela Paolotti; Yamir Moreno; Chinelo Obi; Jim Duggan; Ania Wisnia; Antoine Flahault; Thierry Blanchon; Vittoria Colizza;Publisher: HAL CCSDCountry: France
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/
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.