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8 Research products, page 1 of 1

  • 2012-2021
  • Preprint
  • FR
  • COVID-19
  • Digital Humanities and Cultural Heritage

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  • Open Access English
    Authors: 
    Cédric Gil-Jardiné; Gabrielle Chenais; Catherine Pradeau; Eric Tentillier; Philipe Revel; Xavier Combes; Michel Galinski; Eric Tellier; Emmanuel Lagarde;
    Publisher: HAL CCSD
    Country: 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.

  • Publication . Article . Preprint . Conference object . 2021
    Open Access English
    Authors: 
    Rr, Pranesh; Farokhnejad M; Shekhar A; Genoveva Vargas Solar;
    Publisher: HAL CCSD
    Country: France

    International audience; This paper presents the Multilingual COVID-19 Analysis Method (CMTA) for detecting and observing the spread of misinformation about this disease within texts. CMTA proposes a data science (DS) pipeline that applies machine learning models for processing, classifying (Dense-CNN) and analyzing (MBERT) multilingual (micro)-texts. DS pipeline data preparation tasks extract features from multilingual textual data and categorize it into specific information classes (i.e., 'false', 'partly false', 'misleading'). The CMTA pipeline has been experimented with multilingual micro-texts (tweets), showing misinformation spread across different languages. To assess the performance of CMTA and put it in perspective, we performed a comparative analysis of CMTA with eight monolingual models used for detecting misinformation. The comparison shows that CMTA has surpassed various monolingual models and suggests that it can be used as a general method for detecting misinformation in multilingual micro-texts. CMTA experimental results show misinformation trends about COVID-19 in different languages during the first pandemic months.

  • Publication . Preprint . Article . 2020
    Open Access English
    Authors: 
    Carletti, Timoteo; Fanelli, Duccio; Piazza, Francesco;
    Publisher: The Authors. Published by Elsevier Ltd.
    Country: Belgium

    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

  • Open Access English
    Authors: 
    Mazhar Mughal; Rashid Javed;
    Publisher: HAL CCSD
    Country: 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.

  • Open Access
    Authors: 
    André Constantinesco; Vincent Israel-Jost; Philippe Choquet;
    Publisher: Cold Spring Harbor Laboratory

    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.

  • English
    Authors: 
    Edmond, Jennifer; Basaraba, Nicole; Doran, Michelle; Garnett, Vicky; Grile, Courtney Helen; Papaki, Eliza; Tóth-Czifra, Erzsébet;
    Publisher: HAL CCSD
    Country: France
  • Open Access
    Authors: 
    B. Grecu; F. Borleanu; A. Tiganescu; A. Tiganescu; N. Poiata; N. Poiata; R. Dinescu; D. Tataru;
    Publisher: Copernicus GmbH

    After the World Health Organization declared COVID-19 a pandemic in March 2020, Romania followed the example of many other countries and imposed a series of restrictive measures, including restricting people's mobility and closing social, cultural, and industrial activities to prevent the spread of the disease. In this study, we analyze continuous vertical component recordings from the stations of the Romanian Seismic Network – one of the largest networks in Europe, consisting of 148 stations – to explore the seismic noise variation associated with the reduced human mobility and activity due to the Romanian measures against COVID-19 in detail. We focused our investigation on four frequency bands – 2–8, 4–14, 15–25 and 25–40 Hz – and found that the largest reductions in seismic noise associated with the lockdown correspond to the high-frequency range of 15–40 Hz. We found that all the stations with large reductions in seismic noise (>∼ 40 %) are located inside and near schools or in buildings, indicating that at these frequencies the drop is related to the drastic reduction of human activity in these edifices. In the lower-frequency range (2–8 and 4–14 Hz) the variability of the noise reduction among the stations is lower than in the high-frequency range, corresponding to about 35 % on average. This drop is due to reduced traffic during the lockdown, as most of the stations showing such changes in seismic noise in these bands are located within cities and near main or side streets. In addition to the noise reduction observed at stations located in populated areas, we also found seismic noise lockdown-related changes at several stations located far from urban areas, with movement of people in the vicinity of the station explaining the noise reductions.

  • Open Access English
    Authors: 
    Jocelyn Raude; Marion Debin; Cécile Souty; Caroline Guerris; Iclement Turbelin; Alessandra Falchi; Isabelle Bonmarin; Daniela Paolotti; Yamir Moreno; Chinelo Obi; +5 more
    Publisher: HAL CCSD
    Country: 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/

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