Commit a2a89d14 authored by qlobbe's avatar qlobbe

Quentin's first modifications

parent dff1a7c0
@article{foster_phylogenetic_2020,
author = {Peter Forster and Lucy Forster and Colin Renfrew and Michael Forster },
title = {Phylogenetic network analysis of SARS-CoV-2 genomes},
journal = {Proceedings of the National Academy of Sciences},
volume = {117},
number = {17},
pages = {9241-9243},
year = {2020},
doi = {10.1073/pnas.2004999117},
URL = {https://www.pnas.org/doi/abs/10.1073/pnas.2004999117},
eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.2004999117}
,
abstract = { This is a phylogenetic network of SARS-CoV-2 genomes sampled from across the world. These genomes are closely related and under evolutionary selection in their human hosts, sometimes with parallel evolution events, that is, the same virus mutation emerges in two different human hosts. This makes character-based phylogenetic networks the method of choice for reconstructing their evolutionary paths and their ancestral genome in the human host. The network method has been used in around 10,000 phylogenetic studies of diverse organisms, and is mostly known for reconstructing the prehistoric population movements of humans and for ecological studies, but is less commonly employed in the field of virology. In a phylogenetic network analysis of 160 complete human severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) genomes, we find three central variants distinguished by amino acid changes, which we have named A, B, and C, with A being the ancestral type according to the bat outgroup coronavirus. The A and C types are found in significant proportions outside East Asia, that is, in Europeans and Americans. In contrast, the B type is the most common type in East Asia, and its ancestral genome appears not to have spread outside East Asia without first mutating into derived B types, pointing to founder effects or immunological or environmental resistance against this type outside Asia. The network faithfully traces routes of infections for documented coronavirus disease 2019 (COVID-19) cases, indicating that phylogenetic networks can likewise be successfully used to help trace undocumented COVID-19 infection sources, which can then be quarantined to prevent recurrent spread of the disease worldwide. }
}
@article{aphp_indicators_2020,
doi = {10.1371/journal.pone.0241406},
author = {By the COVID-19 APHP-Universities-INRIA-INSERM Group},
journal = {PLOS ONE},
publisher = {Public Library of Science},
title = {Early indicators of intensive care unit bed requirement during the COVID-19 epidemic: A retrospective study in Ile-de-France region, France},
year = {2020},
month = {11},
volume = {15},
url = {https://doi.org/10.1371/journal.pone.0241406},
pages = {1-12},
abstract = {The aim of our retrospective study was to evaluate the earliest COVID19-related signal to anticipate requirements of intensive care unit (ICU) beds. Although the number of ICU beds is crucial during the COVID-19 epidemic, there is no recognized early indicator to anticipate it. In the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient, depending on the number of days the indicator has been shifted. Primary endpoint was the number of ICU patients. EMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated (R2 ranging between 0.79 to 0.99, all P<0.001) with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement. A qualitative analysis of the onset of the second wave period of the epidemic (August 1 to September 15, 2020) in the same region provided similar results. The daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19, or decide additional social measures.},
number = {11},
}
@article{chavalarias_phylomemetic_2013,
title = {Phylomemetic patterns in science evolution—the rise and fall of scientific fields},
volume = {8},
......
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......@@ -115,6 +115,18 @@
\DOIprefix\doi{10.1073/pnas.2101718118},
\href{http://arxiv.org/abs/https://www.pnas.org/content/118/21/e2101718118.full.pdf}{\tt
arXiv:https://www.pnas.org/content/118/21/e2101718118.full.pdf}.
%Type = Article
\bibitem[{the COVID-19
APHP-Universities-INRIA-INSERM~Group(2020)}]{aphp_indicators_2020}
\bibinfo{author}{the COVID-19 APHP-Universities-INRIA-INSERM~Group, B.},
\bibinfo{year}{2020}.
\newblock \bibinfo{title}{Early indicators of intensive care unit bed
requirement during the covid-19 epidemic: A retrospective study in
ile-de-france region, france}.
\newblock \bibinfo{journal}{PLOS ONE} \bibinfo{volume}{15},
\bibinfo{pages}{1--12}.
\newblock \URLprefix \url{https://doi.org/10.1371/journal.pone.0241406},
\DOIprefix\doi{10.1371/journal.pone.0241406}.
%Type = Unpublished
\bibitem[{Delanoë and Chavalarias(forthcoming 2021)}]{delanoe_mining_2021}
\bibinfo{author}{Delanoë, A.}, \bibinfo{author}{Chavalarias, D.},
......@@ -130,6 +142,20 @@
Conference on Knowledge Engineering and Knowledge Management},
\bibinfo{organization}{Springer}. pp. \bibinfo{pages}{198--212}.
%Type = Article
\bibitem[{Forster et~al.(2020)Forster, Forster, Renfrew and
Forster}]{foster_phylogenetic_2020}
\bibinfo{author}{Forster, P.}, \bibinfo{author}{Forster, L.},
\bibinfo{author}{Renfrew, C.}, \bibinfo{author}{Forster, M.},
\bibinfo{year}{2020}.
\newblock \bibinfo{title}{Phylogenetic network analysis of sars-cov-2 genomes}.
\newblock \bibinfo{journal}{Proceedings of the National Academy of Sciences}
\bibinfo{volume}{117}, \bibinfo{pages}{9241--9243}.
\newblock \URLprefix
\url{https://www.pnas.org/doi/abs/10.1073/pnas.2004999117},
\DOIprefix\doi{10.1073/pnas.2004999117},
\href{http://arxiv.org/abs/https://www.pnas.org/doi/pdf/10.1073/pnas.2004999117}{\tt
arXiv:https://www.pnas.org/doi/pdf/10.1073/pnas.2004999117}.
%Type = Article
\bibitem[{Krause et~al.(2021)Krause, Fleming, Peto, Longini, Figueroa, Sterne,
Cravioto, Rees, Higgins, Boutron, Pan, Gruber, Arora, Kazi, Gaspar,
Swaminathan, Ryan and Henao-Restrepo}]{krause_considerations_2021}
......
......@@ -6,45 +6,45 @@ Database file #1: references.bib
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