MOOD project is at the forefront of European research of infectious disease surveillance and modelling from a data science perspective, investigating the impact of global warming on disease outbreaks, and proposing innovations for building of One Health systems across Europe and the world.
In the table below all publications to which the MOOD project contributed are listed. Use the filter to select the most relevant articles.
63.
Camille, Schaeffer; Roberto, Interdonato; Lancelot, Renaud; Roche, Mathieu; Teisseire, Maguelonne.
Social network data and epidemiological intelligence: A case study of avian influenza Conference
vol. 116, 2021.
Abstract | BibTeX | Tags: HPAI (Avian Influenza)
@conference{nokey,
title = {Social network data and epidemiological intelligence: A case study of avian influenza},
author = {Schaeffer Camille and Interdonato Roberto and Lancelot, Renaud and Roche, Mathieu and Teisseire, Maguelonne.},
year = {2021},
date = {2021-11-06},
urldate = {2021-11-06},
journal = {International Journal of Infectious Diseases},
volume = {116},
pages = {99},
abstract = {Event Based Surveillance (EBS) systems detect and monitor diseases by analysing articles from online newspapers and reports from health organizations (e.g. FAO, OIE, etc.). However, they partially integrate data from social networks, even though these data are present in large quantities on the web. The purpose of this study is to exploit social network data, such as Twitter and YouTube, to provide epidemiological and additional information for Avian Influenza surveillance.},
keywords = {HPAI (Avian Influenza)},
pubstate = {published},
tppubtype = {conference}
}
Event Based Surveillance (EBS) systems detect and monitor diseases by analysing articles from online newspapers and reports from health organizations (e.g. FAO, OIE, etc.). However, they partially integrate data from social networks, even though these data are present in large quantities on the web. The purpose of this study is to exploit social network data, such as Twitter and YouTube, to provide epidemiological and additional information for Avian Influenza surveillance.
62.
Syed, Mehtab Alam; Decoupes, Remy; Arsevska, Elena; Roche, Mathieu; Teisseire, Maguelonne
Spatial opinion mining from COVID-19 twitter data Journal Article
In: International Journal of Infectious Diseases, vol. 116, iss. 549, pp. 527, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), Text mining
@article{nokey,
title = {Spatial opinion mining from COVID-19 twitter data},
author = {Mehtab Alam Syed and Remy Decoupes and Elena Arsevska and Mathieu Roche and Maguelonne Teisseire},
url = {https://www.ijidonline.com/article/S1201-9712(21)00957-7/pdf},
doi = {https://doi.org/10.1016/j.ijid.2021.12.065},
year = {2021},
date = {2021-11-06},
urldate = {2021-11-06},
journal = {International Journal of Infectious Diseases},
volume = {116},
issue = {549},
pages = {527},
abstract = {: In the first quarter of 2020, World Health Organization (WHO) declared COVID-19 as a public health emergency around the globe. Therefore, different users from all over the world shared their thoughts about COVID-19 on social media platforms i.e., Twitter, Facebook etc. So, it is important to analyze public opinions about COVID-19 from different regions over different period of time. To fulfill the spatial analysis issue, a previous work called H-TF-IDF (Hierarchy-based measure for tweet analysis) for term extraction from tweet data has been proposed. In this work, we focus on the sentiment analysis performed on terms selected by H-TFIDF for spatial tweets groups to know local situations during the ongoing epidemic COVID-19 over different time frames.},
keywords = {Covid-19 (Coronavirus), Text mining},
pubstate = {published},
tppubtype = {article}
}
: In the first quarter of 2020, World Health Organization (WHO) declared COVID-19 as a public health emergency around the globe. Therefore, different users from all over the world shared their thoughts about COVID-19 on social media platforms i.e., Twitter, Facebook etc. So, it is important to analyze public opinions about COVID-19 from different regions over different period of time. To fulfill the spatial analysis issue, a previous work called H-TF-IDF (Hierarchy-based measure for tweet analysis) for term extraction from tweet data has been proposed. In this work, we focus on the sentiment analysis performed on terms selected by H-TFIDF for spatial tweets groups to know local situations during the ongoing epidemic COVID-19 over different time frames.
61.
Faria, Nuno R.; Mellan, Thomas A.; Whittaker, Charles; Claro, Ingra M.; da S. Candido, Darlan; Mishra, Swapnil; Crispim, Myuki A. E.
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil Journal Article
In: Science, vol. 372, no. 6544, pp. 815-821, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil},
author = {Nuno R. Faria and Thomas A. Mellan and Charles Whittaker and Ingra M. Claro and Darlan da S. Candido and Swapnil Mishra and Myuki A. E. Crispim},
url = {https://www.science.org/doi/abs/10.1126/science.abh2644},
doi = {10.1126/science.abh2644},
year = {2021},
date = {2021-11-01},
urldate = {2021-11-01},
journal = {Science},
volume = {372},
number = {6544},
pages = {815-821},
abstract = {Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.
60.
Hu, Maogui
Risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission Among Air Passengers in China Journal Article
In: Clinical Infectious Diseases, vol. 75, iss. 1, pp. e234–e240, 2021, ISSN: 1058-4838.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{10.1093/cid/ciab836,,
title = {Risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission Among Air Passengers in China },
author = {Maogui Hu et al.},
url = {https://academic.oup.com/cid/article/75/1/e234/6373518},
doi = {https://doi.org/10.1093/cid/ciab836},
issn = {1058-4838},
year = {2021},
date = {2021-09-21},
urldate = {2021-09-21},
journal = {Clinical Infectious Diseases},
volume = {75},
issue = {1},
pages = {e234–e240},
abstract = {Modern transportation plays a key role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and new variants. However, little is known about the exact transmission risk of the virus on airplanes.Using the itinerary and epidemiological data of coronavirus disease 2019 (COVID-19) cases and close contacts on domestic airplanes departing from Wuhan city in China before the lockdown on 23 January 2020, we estimated the upper and lower bounds of overall transmission risk of COVID-19 among travelers.In total, 175 index cases were identified among 5797 passengers on 177 airplanes. The upper and lower attack rates (ARs) of a seat were 0.60% (34/5622, 95% confidence interval [CI] .43–.84%) and 0.33% (18/5400, 95% CI .21–.53%), respectively. In the upper- and lower-bound risk estimates, each index case infected 0.19 (SD 0.45) and 0.10 (SD 0.32) cases, respectively. The seats immediately adjacent to the index cases had an AR of 9.2% (95% CI 5.7–14.4%), with a relative risk 27.8 (95% CI 14.4–53.7) compared to other seats in the upper limit estimation. The middle seat had the highest AR (0.7%, 95% CI .4%–1.2%). The upper-bound AR increased from 0.7% (95% CI 0.5%–1.0%) to 1.2% (95% CI .4–3.3%) when the co-travel time increased from 2.0 hours to 3.3 hours.The ARs among travelers varied by seat distance from the index case and joint travel time, but the variation was not significant between the types of aircraft. The overall risk of SARS-CoV-2 transmission during domestic travel on planes was relatively low. These findings can improve our understanding of COVID-19 spread during travel and inform response efforts in the pandemic.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Modern transportation plays a key role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and new variants. However, little is known about the exact transmission risk of the virus on airplanes.Using the itinerary and epidemiological data of coronavirus disease 2019 (COVID-19) cases and close contacts on domestic airplanes departing from Wuhan city in China before the lockdown on 23 January 2020, we estimated the upper and lower bounds of overall transmission risk of COVID-19 among travelers.In total, 175 index cases were identified among 5797 passengers on 177 airplanes. The upper and lower attack rates (ARs) of a seat were 0.60% (34/5622, 95% confidence interval [CI] .43–.84%) and 0.33% (18/5400, 95% CI .21–.53%), respectively. In the upper- and lower-bound risk estimates, each index case infected 0.19 (SD 0.45) and 0.10 (SD 0.32) cases, respectively. The seats immediately adjacent to the index cases had an AR of 9.2% (95% CI 5.7–14.4%), with a relative risk 27.8 (95% CI 14.4–53.7) compared to other seats in the upper limit estimation. The middle seat had the highest AR (0.7%, 95% CI .4%–1.2%). The upper-bound AR increased from 0.7% (95% CI 0.5%–1.0%) to 1.2% (95% CI .4–3.3%) when the co-travel time increased from 2.0 hours to 3.3 hours.The ARs among travelers varied by seat distance from the index case and joint travel time, but the variation was not significant between the types of aircraft. The overall risk of SARS-CoV-2 transmission during domestic travel on planes was relatively low. These findings can improve our understanding of COVID-19 spread during travel and inform response efforts in the pandemic.
59.
Martin, Darren P; Weaver, Steven; Tegally, Houryiah; San, Emmanuel James; Shank, Stephen D; Wilkinson, Eduan; Giandhari, Jennifer; Naidoo, Sureshnee; Pillay, Yeshnee; Singh, Lavanya; Lessells, Richard J; NGS-SA,; (COG-UK), COVID-19 Genomics UK; Gupta, Ravindra K; Wertheim, Joel O; Nekturenko, Anton; Murrell, Ben; Harkins, Gordon W; Lemey, Philippe; MacLean, Oscar A; Robertson, David L; de Oliveira, Tulio; Pond, Sergei L Kosakovsky
The emergence and ongoing convergent evolution of the SARS-CoV-2 N501Y lineages Bachelor Thesis
2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@bachelorthesis{nokey,
title = {The emergence and ongoing convergent evolution of the SARS-CoV-2 N501Y lineages},
author = {Darren P Martin and Steven Weaver and Houryiah Tegally and Emmanuel James San and Stephen D Shank and Eduan Wilkinson and Jennifer Giandhari and Sureshnee Naidoo and Yeshnee Pillay and Lavanya Singh and Richard J Lessells and NGS-SA and COVID-19 Genomics UK (COG-UK) and Ravindra K Gupta and Joel O Wertheim and Anton Nekturenko and Ben Murrell and Gordon W Harkins and Philippe Lemey and Oscar A MacLean and David L Robertson and Tulio de Oliveira and Sergei L Kosakovsky Pond},
url = {https://doi.org/10.1016/j.cell.2021.09.003},
doi = {10.1016/j.cell.2021.09.003},
year = {2021},
date = {2021-09-06},
urldate = {2021-09-06},
journal = {Cell},
volume = {184},
issue = {20},
abstract = {The independent emergence late in 2020 of the B.1.1.7, B.1.351, and P.1 lineages of SARS-CoV-2 prompted renewed concerns about the evolutionary capacity of this virus to overcome public health interventions and rising population immunity. Here, by examining patterns of synonymous and non-synonymous mutations that have accumulated in SARS-CoV-2 genomes since the pandemic began, we find that the emergence of these three “501Y lineages” coincided with a major global shift in the selective forces acting on various SARS-CoV-2 genes. Following their emergence, the adaptive evolution of 501Y lineage viruses has involved repeated selectively favored convergent mutations at 35 genome sites, mutations we refer to as the 501Y meta-signature. The ongoing convergence of viruses in many other lineages on this meta-signature suggests that it includes multiple mutation combinations capable of promoting the persistence of diverse SARS-CoV-2 lineages in the face of mounting host immune recognition.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {bachelorthesis}
}
The independent emergence late in 2020 of the B.1.1.7, B.1.351, and P.1 lineages of SARS-CoV-2 prompted renewed concerns about the evolutionary capacity of this virus to overcome public health interventions and rising population immunity. Here, by examining patterns of synonymous and non-synonymous mutations that have accumulated in SARS-CoV-2 genomes since the pandemic began, we find that the emergence of these three “501Y lineages” coincided with a major global shift in the selective forces acting on various SARS-CoV-2 genes. Following their emergence, the adaptive evolution of 501Y lineage viruses has involved repeated selectively favored convergent mutations at 35 genome sites, mutations we refer to as the 501Y meta-signature. The ongoing convergence of viruses in many other lineages on this meta-signature suggests that it includes multiple mutation combinations capable of promoting the persistence of diverse SARS-CoV-2 lineages in the face of mounting host immune recognition.
58.
Mazzoli, Mattia; Valdano, Eugenio; Colizza, Vittoria
Projecting the COVID-19 epidemic risk in France for the summer 2021 Journal Article
In: Journal of Travel Medicine, vol. 28, no. 7, 2021, ISSN: 1708-8305.
Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{10.1093/jtm/taab129,
title = {Projecting the COVID-19 epidemic risk in France for the summer 2021},
author = {Mattia Mazzoli and Eugenio Valdano and Vittoria Colizza},
url = {https://academic.oup.com/jtm/article-pdf/28/7/taab129/41784325/taab129.pdf},
doi = {https://doi.org/10.1093/jtm/taab129},
issn = {1708-8305},
year = {2021},
date = {2021-08-19},
urldate = {2021-08-19},
journal = {Journal of Travel Medicine},
volume = {28},
number = {7},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
57.
Domenico, Laura Di; Colizza, Vittoria
Epidemic scenarios of Delta variant in France in the summer 2021 Technical Report
2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@techreport{nokey,
title = {Epidemic scenarios of Delta variant in France in the summer 2021},
author = {Laura Di Domenico and Vittoria Colizza},
url = {https://www.epicx-lab.com/uploads/9/6/9/4/9694133/inserm-covid-19-delta_projections_summer-20210710.pdf},
year = {2021},
date = {2021-07-10},
urldate = {2021-07-10},
abstract = {As the Delta variant rapidly progresses in France, with an estimated 43.2% of detected cases attributed to the L452R mutation in the week 26, concerns arise on the upcoming summer epidemic situation, also given the reported slowdown of vaccinations. This short report aims at presenting a range of possible epidemic scenarios, according to different hypotheses on vaccine administration rollout in the summer, conditions of mixing, seasonality and preventive measures, and considering different estimates for the transmissibility advantages of the circulating variants of concern. },
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {techreport}
}
As the Delta variant rapidly progresses in France, with an estimated 43.2% of detected cases attributed to the L452R mutation in the week 26, concerns arise on the upcoming summer epidemic situation, also given the reported slowdown of vaccinations. This short report aims at presenting a range of possible epidemic scenarios, according to different hypotheses on vaccine administration rollout in the summer, conditions of mixing, seasonality and preventive measures, and considering different estimates for the transmissibility advantages of the circulating variants of concern.
56.
Manica, Mattia; Pancheri, Serena; Poletti, Piero; Giovanazzi, Giulia; Guzzetta, Giorgio; Trentini, Filippo; Marziano, Valentina; Ajelli, Marco; Zuccali, Maria Grazia; Benetollo, Pier Paolo; Merler, Stefano; Ferro, Antonio
In: Clinical Infectious Diseases, vol. 74, no. 5, pp. 893-896, 2021, ISSN: 1058-4838.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {Risk of Symptomatic Infection During a Second Coronavirus Disease 2019 Wave in Severe Acute Respiratory Syndrome Coronavirus 2–Seropositive Individuals },
author = {Mattia Manica and Serena Pancheri and Piero Poletti and Giulia Giovanazzi and Giorgio Guzzetta and Filippo Trentini and Valentina Marziano and Marco Ajelli and Maria Grazia Zuccali and Pier Paolo Benetollo and Stefano Merler and Antonio Ferro},
url = {https://academic.oup.com/cid/article/74/5/893/6301134},
doi = {10.1093/cid/ciab556},
issn = {1058-4838},
year = {2021},
date = {2021-06-16},
urldate = {2021-06-16},
journal = {Clinical Infectious Diseases},
volume = {74},
number = {5},
pages = {893-896},
abstract = {We analyzed 221 coronavirus disease 2019 cases identified between June 2020 and January 2021 in 6074 individuals screened for immunoglobulin G antibodies in May 2020, representing 77% of residents of 5 Italian municipalities. The relative risk of developing symptomatic infection in seropositive participants was 0.055 (95% confidence interval, .014–.220)},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
We analyzed 221 coronavirus disease 2019 cases identified between June 2020 and January 2021 in 6074 individuals screened for immunoglobulin G antibodies in May 2020, representing 77% of residents of 5 Italian municipalities. The relative risk of developing symptomatic infection in seropositive participants was 0.055 (95% confidence interval, .014–.220)
55.
Dellicour, Simon; Linard, Catherine; Goethem, Nina Van; Re, Daniele Da; Artois, Jean; Bihin, Jérémie; Schaus, Pierre; Massonnet, François; Oyen, Herman Van; Vanwambeke, Sophie O.; Speybroeck, Niko; Gilbert, Marius
Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence—Belgium as a study case Journal Article
In: International Journal of Health Geographics, iss. 20, no. 29, 2021, ISSN: 1476-072X.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence—Belgium as a study case},
author = {Simon Dellicour and Catherine Linard and Nina Van Goethem and Daniele Da Re and Jean Artois and Jérémie Bihin and Pierre Schaus and François Massonnet and Herman Van Oyen and Sophie O. Vanwambeke and Niko Speybroeck and Marius Gilbert },
url = {https://ij-healthgeographics.biomedcentral.com/articles/10.1186/s12942-021-00281-1},
doi = {https://doi.org/10.1186/s12942-021-00281-1},
issn = {1476-072X},
year = {2021},
date = {2021-06-14},
urldate = {2021-06-14},
journal = {International Journal of Health Geographics},
number = {29},
issue = {20},
abstract = {Background
The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection.
Methods
To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio–temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence.
Results
Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence.
Conclusion
Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Background
The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection.
Methods
To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio–temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence.
Results
Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence.
Conclusion
Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.
The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection.
Methods
To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio–temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence.
Results
Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence.
Conclusion
Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.
54.
Decoupes, Rémy; Rodrique, Kafando; Roche, Mathieu; Teisseire, Maguelonne
H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic? Journal Article
In: AGILE: GIScience Series, vol. 2, no. 4, pp. 1-8, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{,
title = {H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?},
author = {Rémy Decoupes and Kafando Rodrique and Mathieu Roche and Maguelonne Teisseire },
doi = {10.5194/agile-giss-2-2-2021},
year = {2021},
date = {2021-06-01},
urldate = {2021-06-01},
journal = {AGILE: GIScience Series},
volume = {2},
number = {4},
pages = {1-8},
publisher = {European Centre for Disease Prevention and Control},
abstract = {Data produced by social networks may contain weak signals of possible epidemic outbreaks. In this paper, we focus on Twitter data during the waiting period before the appearance of COVID-19 first cases outside China. Among the huge flow of tweets that reflects a global growing concern in all countries, we propose to analyze such data with an adaptation of the TF-IDF measure. It allows the users to extract the discriminant vocabularies used across time and space. The results are then discussed to show how the specific spatio-temporal anchoring of the extracted terms make it possible to follow the crisis dynamics on different scales of time and space.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Data produced by social networks may contain weak signals of possible epidemic outbreaks. In this paper, we focus on Twitter data during the waiting period before the appearance of COVID-19 first cases outside China. Among the huge flow of tweets that reflects a global growing concern in all countries, we propose to analyze such data with an adaptation of the TF-IDF measure. It allows the users to extract the discriminant vocabularies used across time and space. The results are then discussed to show how the specific spatio-temporal anchoring of the extracted terms make it possible to follow the crisis dynamics on different scales of time and space.
53.
Domenico, Laura Di; Sabbatini, Chiara E.; Pullano, Giulia; Lévy-Bruhl, Daniel; Colizza, Vittoria
Impact of January 2021 curfew measures on SARS-CoV-2 B.1.1.7 circulation in France Journal Article
In: Eurosurveillance, vol. 26, iss. 15, no. 2, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{,
title = {Impact of January 2021 curfew measures on SARS-CoV-2 B.1.1.7 circulation in France},
author = {Laura Di Domenico and Chiara E. Sabbatini and Giulia Pullano and Daniel Lévy-Bruhl and Vittoria Colizza},
url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2021.26.15.2100272},
doi = { 10.2807/1560-7917.ES.2021.26.15.2100272},
year = {2021},
date = {2021-04-15},
urldate = {2021-04-15},
journal = {Eurosurveillance},
volume = {26},
number = {2},
issue = {15},
publisher = {Cold Spring Harbor Laboratory Press},
abstract = {Facing B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a 2-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalizations to plateau, by decreasing transmission of the historical strain while B.1.1.7 continued to grow. School holidays appear to have further slowed down progression in February. Without progressively strengthened social distancing, a rapid surge of hospitalizations is expected, despite the foreseen increase in vaccination rhythm.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Facing B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a 2-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalizations to plateau, by decreasing transmission of the historical strain while B.1.1.7 continued to grow. School holidays appear to have further slowed down progression in February. Without progressively strengthened social distancing, a rapid surge of hospitalizations is expected, despite the foreseen increase in vaccination rhythm.
52.
Huang, Bo; Wang, Jionghua; Cai, Jixuan; Yao, Shiqi; Chan, Paul Kay Sheung; Tam, Tony Hong-wing; Hong, Ying-Yi; Ruktanonchai, Corrine W.; Carioli, Alessandra; Floyd, Jessica R.; Ruktanonchai, Nick W.; Yang, Weizhong; Li, Zhongjie; Tatem, Andrew J.; Lai, Shengjie
Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities Journal Article
In: Nature Human Behaviour, vol. 5, pp. 695–705, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities},
author = {Bo Huang and Jionghua Wang and Jixuan Cai and Shiqi Yao and Paul Kay Sheung Chan and Tony Hong-wing Tam and Ying-Yi Hong and Corrine W. Ruktanonchai and Alessandra Carioli and Jessica R. Floyd and Nick W. Ruktanonchai and Weizhong Yang and Zhongjie Li and Andrew J. Tatem and Shengjie Lai },
doi = {https://doi.org/10.1038/s41562-021-01063-2},
year = {2021},
date = {2021-02-18},
urldate = {2021-02-18},
journal = {Nature Human Behaviour},
volume = {5},
pages = {695–705},
abstract = {The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city’s population density and social contact patterns.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city’s population density and social contact patterns.
51.
Dellicour, Simon; Gill, Mandev S; Faria, Nuno R; Rambaut, Andrew; Pybus, Oliver G; Suchard, Marc A; Lemey, Philippe
Relax, Keep Walking — A Practical Guide to Continuous Phylogeographic Inference with BEAST Journal Article
In: Molecular Biology and Evolution, vol. 38, iss. 8, 2021, ISSN: 1537-1719.
Abstract | Links | BibTeX | Tags: OpenDataSet
@article{10.1093/molbev/msab031,
title = {Relax, Keep Walking — A Practical Guide to Continuous Phylogeographic Inference with BEAST},
author = {Simon Dellicour and Mandev S Gill and Nuno R Faria and Andrew Rambaut and Oliver G Pybus and Marc A Suchard and Philippe Lemey},
editor = {Rasmus Nielsen},
url = {https://doi.org/10.1093/molbev/msab031},
doi = {10.1093/molbev/msab031},
issn = {1537-1719},
year = {2021},
date = {2021-02-02},
urldate = {2021-02-02},
journal = {Molecular Biology and Evolution},
volume = {38},
issue = {8},
abstract = {Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.},
keywords = {OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.
50.
Marini, Giovanni; Manica, Mattia; Delucchi, Luca; Pugliese, Andrea; Ros`a, Roberto
Spring temperature shapes West Nile virus transmission in Europe Journal Article
In: Acta Tropica, vol. 215, pp. 105796, 2021.
Abstract | Links | BibTeX | Tags: WNV (West Nile Virus)
@article{marini2021spring,
title = {Spring temperature shapes West Nile virus transmission in Europe},
author = {Giovanni Marini and Mattia Manica and Luca Delucchi and Andrea Pugliese and Roberto Ros`a},
doi = {https://doi.org/10.1016/j.actatropica.2020.105796},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Acta Tropica},
volume = {215},
pages = {105796},
publisher = {Elsevier},
abstract = {West Nile Virus (WNV) is now endemic in many European countries, causing hundreds of human cases every year, with a high spatial and temporal heterogeneity. Previous studies have suggested that spring temperature might play a key role at shaping WNV transmission. Specifically, warmer temperatures in April-May might amplify WNV circulation, thus increasing the risk for human transmission later in the year. To test this hypothesis, we collated publicly available data on the number of human infections recorded in Europe between 2011 and 2019. We then applied generalized linear models to quantify the relationship between human cases and spring temperature, considering both average conditions (over years 2003-2010) and deviations from the average for subsequent years (2011-2019). We found a significant positive association both spatial (average conditions) and temporal (deviations). The former indicates that WNV circulation is higher in usually warmer regions while the latter implies a predictive value of spring conditions over the coming season. We also found a positive association with WNV detection during the previous year, which can be interpreted as an indication of the reliability of the surveillance system but also of WNV overwintering capacity. Weather anomalies at the beginning of the mosquito breeding season might act as an early warning signal for public health authorities, enabling them to strengthen in advance ongoing surveillance and prevention strategies.},
keywords = {WNV (West Nile Virus)},
pubstate = {published},
tppubtype = {article}
}
West Nile Virus (WNV) is now endemic in many European countries, causing hundreds of human cases every year, with a high spatial and temporal heterogeneity. Previous studies have suggested that spring temperature might play a key role at shaping WNV transmission. Specifically, warmer temperatures in April-May might amplify WNV circulation, thus increasing the risk for human transmission later in the year. To test this hypothesis, we collated publicly available data on the number of human infections recorded in Europe between 2011 and 2019. We then applied generalized linear models to quantify the relationship between human cases and spring temperature, considering both average conditions (over years 2003-2010) and deviations from the average for subsequent years (2011-2019). We found a significant positive association both spatial (average conditions) and temporal (deviations). The former indicates that WNV circulation is higher in usually warmer regions while the latter implies a predictive value of spring conditions over the coming season. We also found a positive association with WNV detection during the previous year, which can be interpreted as an indication of the reliability of the surveillance system but also of WNV overwintering capacity. Weather anomalies at the beginning of the mosquito breeding season might act as an early warning signal for public health authorities, enabling them to strengthen in advance ongoing surveillance and prevention strategies.
49.
Ingelbeen, Brecht; Peckeu, Laur`ene; Laga, Marie; Hendrix, Ilona; Neven, Inge; Sande, Marianne AB; Kleef, Esther
Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium, August to November 2020 Journal Article
In: Eurosurveillance, vol. 26, no. 7, pp. 2100065, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{ingelbeen2021reducing,
title = {Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium, August to November 2020},
author = {Brecht Ingelbeen and Laur`ene Peckeu and Marie Laga and Ilona Hendrix and Inge Neven and Marianne AB Sande and Esther Kleef},
doi = {https://doi.org/10.1371/journal.pbio.3001115},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Eurosurveillance},
volume = {26},
number = {7},
pages = {2100065},
publisher = {European Centre for Disease Prevention and Control},
abstract = {To evaluate the effect of physical distancing and school reopening in Brussels between August and November 2020, we monitored changes in the number of reported contacts per SARS-CoV-2 case and associated SARS-CoV-2 transmission. The second COVID-19 pandemic wave in Brussels was the result of increased social contact across all ages following school reopening. Physical distancing measures including closure of bars and restaurants, and limiting close contacts, while primary and secondary schools remained open, reduced social mixing and controlled SARS-CoV-2 transmission.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
To evaluate the effect of physical distancing and school reopening in Brussels between August and November 2020, we monitored changes in the number of reported contacts per SARS-CoV-2 case and associated SARS-CoV-2 transmission. The second COVID-19 pandemic wave in Brussels was the result of increased social contact across all ages following school reopening. Physical distancing measures including closure of bars and restaurants, and limiting close contacts, while primary and secondary schools remained open, reduced social mixing and controlled SARS-CoV-2 transmission.
48.
Valentin, Sarah; Lancelot, Renaud; Roche, Mathieu
Identifying associations between epidemiological entities in news data for animal disease surveillance Journal Article
In: Artificial Intelligence in Agriculture, vol. 5, pp. 163-174, 2021, ISSN: 2589-7217.
Abstract | Links | BibTeX | Tags: Text mining
@article{VALENTIN2021163,
title = {Identifying associations between epidemiological entities in news data for animal disease surveillance},
author = {Sarah Valentin and Renaud Lancelot and Mathieu Roche},
url = {https://www.sciencedirect.com/science/article/pii/S2589721721000246},
doi = {https://doi.org/10.1016/j.aiia.2021.07.003},
issn = {2589-7217},
year = {2021},
date = {2021-01-01},
journal = {Artificial Intelligence in Agriculture},
volume = {5},
pages = {163-174},
abstract = {Event-based surveillance systems are at the crossroads of human and animal (and plant and ecosystem) health, epidemiology, statistics, and informatics. Thus, their deployment faces many challenges specific to each domain and their intersections, such as relations among automation, artificial intelligence, and expertise. In this context, our work pertins to the extraction of epidemiological events in textual data (i.e. news) by unsupervised methods. We define the event extraction task as detecting pairs of epidemiological entities (e.g. a disease name and location). The quality of the ranked lists of pairs was evaluated using specific ranking evaluation metrics. We used a publicly available annotated corpus of 438 documents (i.e. news articles) related to animal disease events. The statistical approach was able to detect event-related pairs of epidemiological features with a good trade-off between precision and recall. Our results showed that using a window of words outperformed document-based and sentence-based approaches, while reducing the probability of detecting false pairs. Our results indicated that Mutual Information was less adapted than the Dice coefficient for ranking pairs of features in the event extraction framework. We believe that Mutual Information would be more relevant for rare pair detection (i.e. weak signals), but requires higher manual curation to avoid false positive extraction pairs. Moreover, generalising the country-level spatial features enabled better discrimination (i.e. ranking) of relevant disease-location pairs for event extraction.},
keywords = {Text mining},
pubstate = {published},
tppubtype = {article}
}
Event-based surveillance systems are at the crossroads of human and animal (and plant and ecosystem) health, epidemiology, statistics, and informatics. Thus, their deployment faces many challenges specific to each domain and their intersections, such as relations among automation, artificial intelligence, and expertise. In this context, our work pertins to the extraction of epidemiological events in textual data (i.e. news) by unsupervised methods. We define the event extraction task as detecting pairs of epidemiological entities (e.g. a disease name and location). The quality of the ranked lists of pairs was evaluated using specific ranking evaluation metrics. We used a publicly available annotated corpus of 438 documents (i.e. news articles) related to animal disease events. The statistical approach was able to detect event-related pairs of epidemiological features with a good trade-off between precision and recall. Our results showed that using a window of words outperformed document-based and sentence-based approaches, while reducing the probability of detecting false pairs. Our results indicated that Mutual Information was less adapted than the Dice coefficient for ranking pairs of features in the event extraction framework. We believe that Mutual Information would be more relevant for rare pair detection (i.e. weak signals), but requires higher manual curation to avoid false positive extraction pairs. Moreover, generalising the country-level spatial features enabled better discrimination (i.e. ranking) of relevant disease-location pairs for event extraction.
47.
Li, Sabrina L; Messina, Jane P; Pybus, Oliver G; Kraemer, Moritz U G; Gardner, Lauren
A review of models applied to the geographic spread of Zika virus Journal Article
In: Transactions of The Royal Society of Tropical Medicine and Hygiene, vol. 115, no. 9, pp. 956-964, 2021, ISSN: 0035-9203.
Abstract | Links | BibTeX | Tags: Text mining, Zika
@article{10.1093/trstmh/trab009,
title = {A review of models applied to the geographic spread of Zika virus},
author = {Sabrina L Li and Jane P Messina and Oliver G Pybus and Moritz U G Kraemer and Lauren Gardner},
url = {https://doi.org/10.1093/trstmh/trab009},
doi = {10.1093/trstmh/trab009},
issn = {0035-9203},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Transactions of The Royal Society of Tropical Medicine and Hygiene},
volume = {115},
number = {9},
pages = {956-964},
abstract = {In recent years, Zika virus (ZIKV) has expanded its geographic range and in 2015–2016 caused a substantial epidemic linked to a surge in developmental and neurological complications in newborns. Mathematical models are powerful tools for assessing ZIKV spread and can reveal important information for preventing future outbreaks. We reviewed the literature and retrieved modelling studies that were developed to understand the spatial epidemiology of ZIKV spread and risk. We classified studies by type, scale, aim and applications and discussed their characteristics, strengths and limitations. We examined the main objectives of these models and evaluated the effectiveness of integrating epidemiological and phylogeographic data, along with socioenvironmental risk factors that are known to contribute to vector–human transmission. We also assessed the promising application of human mobility data as a real-time indicator of ZIKV spread. Lastly, we summarised model validation methods used in studies to ensure accuracy in models and modelled outcomes. Models are helpful for understanding ZIKV spread and their characteristics should be carefully considered when developing future modelling studies to improve arbovirus surveillance.},
keywords = {Text mining, Zika},
pubstate = {published},
tppubtype = {article}
}
In recent years, Zika virus (ZIKV) has expanded its geographic range and in 2015–2016 caused a substantial epidemic linked to a surge in developmental and neurological complications in newborns. Mathematical models are powerful tools for assessing ZIKV spread and can reveal important information for preventing future outbreaks. We reviewed the literature and retrieved modelling studies that were developed to understand the spatial epidemiology of ZIKV spread and risk. We classified studies by type, scale, aim and applications and discussed their characteristics, strengths and limitations. We examined the main objectives of these models and evaluated the effectiveness of integrating epidemiological and phylogeographic data, along with socioenvironmental risk factors that are known to contribute to vector–human transmission. We also assessed the promising application of human mobility data as a real-time indicator of ZIKV spread. Lastly, we summarised model validation methods used in studies to ensure accuracy in models and modelled outcomes. Models are helpful for understanding ZIKV spread and their characteristics should be carefully considered when developing future modelling studies to improve arbovirus surveillance.
46.
Rodrique, Kafando; Decoupes, Rémy; Valentin, Sarah; Sautot, Lucile; Teisseire, Maguelonne; Roche, Mathieu
ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis Journal Article
In: Health Information Science and Systems, vol. 9, 2021.
Abstract | Links | BibTeX | Tags:
@article{article,
title = {ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis},
author = {Kafando Rodrique and Rémy Decoupes and Sarah Valentin and Lucile Sautot and Maguelonne Teisseire and Mathieu Roche},
doi = {10.1007/s13755-021-00156-6},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Health Information Science and Systems},
volume = {9},
abstract = {Here, we introduce ITEXT-BIO, an intelligent process for biomedical domain terminology extraction from textual documents and subsequent analysis. The proposed methodology consists of two complementary approaches, including free and driven term extraction. The first is based on term extraction with statistical measures, while the second considers morphosyntactic variation rules to extract term variants from the corpus. The combination of two term extraction and analysis strategies is the keystone of ITEXT-BIO. These include combined intra-corpus strategies that enable term extraction and analysis either from a single corpus (intra), or from corpora (inter). We assessed the two approaches, the corpus or corpora to be analysed and the type of statistical measures used. Our experimental findings revealed that the proposed methodology could be used: (1) to efficiently extract representative, discriminant and new terms from a given corpus or corpora, and (2) to provide quantitative and qualitative analyses on these terms regarding the study domain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Here, we introduce ITEXT-BIO, an intelligent process for biomedical domain terminology extraction from textual documents and subsequent analysis. The proposed methodology consists of two complementary approaches, including free and driven term extraction. The first is based on term extraction with statistical measures, while the second considers morphosyntactic variation rules to extract term variants from the corpus. The combination of two term extraction and analysis strategies is the keystone of ITEXT-BIO. These include combined intra-corpus strategies that enable term extraction and analysis either from a single corpus (intra), or from corpora (inter). We assessed the two approaches, the corpus or corpora to be analysed and the type of statistical measures used. Our experimental findings revealed that the proposed methodology could be used: (1) to efficiently extract representative, discriminant and new terms from a given corpus or corpora, and (2) to provide quantitative and qualitative analyses on these terms regarding the study domain.
45.
Poletti, Piero; Tirani, Marcello; Cereda, Danilo; Trentini, Filippo; Guzzetta, Giorgio; Sabatino, Giuliana; Marziano, Valentina; Castrofino, Ambra; Grosso, Francesca; Castillo, Gabriele Del; others,
In: JAMA network open, vol. 4, no. 3, pp. e211085–e211085, 2021.
Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{poletti2021association,
title = {Association of age with likelihood of developing symptoms and critical disease among close contacts exposed to patients with confirmed sars-cov-2 infection in italy},
author = {Piero Poletti and Marcello Tirani and Danilo Cereda and Filippo Trentini and Giorgio Guzzetta and Giuliana Sabatino and Valentina Marziano and Ambra Castrofino and Francesca Grosso and Gabriele Del Castillo and others},
doi = {doi:10.1001/jamanetworkopen.2021.1085},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {JAMA network open},
volume = {4},
number = {3},
pages = {e211085--e211085},
publisher = {American Medical Association},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
44.
Plessis, Louis; McCrone, John T.; Zarebski, Alexander E.; Hill, Verity; Ruis, Christopher; Gutierrez, Bernardo; Raghwani, Jayna; Ashworth, Jordan; Colquhoun, Rachel; Connor, Thomas R.; Faria, Nuno R.; Jackson, Ben; Loman, Nicholas J.; O’Toole, Ãine; Nicholls, Samuel M.; Parag, Kris V.; Scher, Emily; Vasylyeva, Tetyana I.; Volz, Erik M.; Watts, Alexander; Bogoch, Isaac I.; Khan, Kamran; null,; Aanensen, David M.; Kraemer, Moritz U. G.; Rambaut, Andrew; Pybus, Oliver G.
Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK Journal Article
In: Science, vol. 371, no. 6530, pp. 708-712, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{doi:10.1126/science.abf2946,
title = {Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK},
author = {Louis Plessis and John T. McCrone and Alexander E. Zarebski and Verity Hill and Christopher Ruis and Bernardo Gutierrez and Jayna Raghwani and Jordan Ashworth and Rachel Colquhoun and Thomas R. Connor and Nuno R. Faria and Ben Jackson and Nicholas J. Loman and Ãine O’Toole and Samuel M. Nicholls and Kris V. Parag and Emily Scher and Tetyana I. Vasylyeva and Erik M. Volz and Alexander Watts and Isaac I. Bogoch and Kamran Khan and null and David M. Aanensen and Moritz U. G. Kraemer and Andrew Rambaut and Oliver G. Pybus},
doi = {10.1126/science.abf2946 URL = https://www.science.org/doi/abs/10.1126/science.abf2946},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Science},
volume = {371},
number = {6530},
pages = {708-712},
abstract = {The scale of genome-sequencing efforts for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unprecedented. The United Kingdom has contributed more than 26,000 sequences to this effort. This volume of data allowed du Plessis et al. to develop a detailed picture of the influxes of virus reaching U.K. shores as the pandemic developed during the first months of 2020 (see the Perspective by Nelson). Before lockdown, high travel volumes and few restrictions on international travel allowed more than 1000 lineages to become established. This accelerated local epidemic growth and exceeded contact tracing capacity. The authors were able to quantify the abundance, size distribution, and spatial range of the lineages that were transmitted. Transmission was highly heterogeneous, favoring some lineages that became widespread and subsequently harder to eliminate. This dire history indicates that rapid or even preemptive responses should have been used as they were elsewhere where containment was successful. Science, this issue p. 708; see also p. 680 Large-scale virus genome sequencing reveals the genetic structure and importation dynamics of a national COVID-19 epidemic. The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in 1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The scale of genome-sequencing efforts for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unprecedented. The United Kingdom has contributed more than 26,000 sequences to this effort. This volume of data allowed du Plessis et al. to develop a detailed picture of the influxes of virus reaching U.K. shores as the pandemic developed during the first months of 2020 (see the Perspective by Nelson). Before lockdown, high travel volumes and few restrictions on international travel allowed more than 1000 lineages to become established. This accelerated local epidemic growth and exceeded contact tracing capacity. The authors were able to quantify the abundance, size distribution, and spatial range of the lineages that were transmitted. Transmission was highly heterogeneous, favoring some lineages that became widespread and subsequently harder to eliminate. This dire history indicates that rapid or even preemptive responses should have been used as they were elsewhere where containment was successful. Science, this issue p. 708; see also p. 680 Large-scale virus genome sequencing reveals the genetic structure and importation dynamics of a national COVID-19 epidemic. The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in 1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.