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.
68.
Agoti, Charles N; Ochola-Oyier, Lynette Isabella; Dellicour, Simon; Mohammed, Khadija Said; Lambisia, Arnold W; de Laurent, Zaydah R; Morobe, John M; Mburu, Maureen W; Omuoyo, Donwilliams O; Ongera, Edidah M; Ndwiga, Leonard; Maitha, Eric; Kitole, Benson; Suleiman, Thani; Mwakinangu, Mohamed; Nyambu, John K; Otieno, John; Salim, Barke; Musyoki, Jennifer; Murunga, Nickson; Otieno, Edward; Kiiru, John N; Kasera, Kadondi; Amoth, Patrick; Mwangangi, Mercy; Aman, Rashid; Kinyanjui, Samson; Warimwe, George; Phan, My; Agweyu, Ambrose; Cotten, Matthew; Barasa, Edwine; Tsofa, Benjamin; Nokes, D James; Philip, Philip Bejon; Githinji, George
Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: A retrospective genomic study Journal Article
In: eLife, vol. 11, pp. e71703, 2022, ISSN: 2050-084X.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{10.7554/eLife.71703,
title = {Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: A retrospective genomic study},
author = {Charles N Agoti and Lynette Isabella Ochola-Oyier and Simon Dellicour and Khadija Said Mohammed and Arnold W Lambisia and Zaydah R de Laurent and John M Morobe and Maureen W Mburu and Donwilliams O Omuoyo and Edidah M Ongera and Leonard Ndwiga and Eric Maitha and Benson Kitole and Thani Suleiman and Mohamed Mwakinangu and John K Nyambu and John Otieno and Barke Salim and Jennifer Musyoki and Nickson Murunga and Edward Otieno and John N Kiiru and Kadondi Kasera and Patrick Amoth and Mercy Mwangangi and Rashid Aman and Samson Kinyanjui and George Warimwe and My Phan and Ambrose Agweyu and Matthew Cotten and Edwine Barasa and Benjamin Tsofa and D James Nokes and Philip Bejon Philip and George Githinji},
editor = {Grabowski, Mary Kate and van der Meer, Jos W},},
url = {https://doi.org/10.7554/eLife.71703},
doi = {10.7554/eLife.71703},
issn = {2050-084X},
year = {2022},
date = {2022-06-14},
urldate = {2022-06-14},
journal = {eLife},
volume = {11},
pages = {e71703},
abstract = {Detailed understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. textbf{Methods:} Here, we analysed 1139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River, and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction, and virus dispersal between counties was estimated using discrete phylogeographic analysis. textbf{Results:} During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; 9 of which occurred in both waves and 4 seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1, and N.8). Most of the sequenced infections belonged to lineage B.1 (n = 723, 63%), which predominated in both Wave 1 (73%, followed by lineages N.8 [6%] and B.1.1 [6%]) and Wave 2 (56%, followed by lineages B.1.549 [21%] and B.1.530 [5%]). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many Coronavirus Disease 2019 (COVID-19) government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. textbf{Conclusions:} Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission. textbf{Funding:} This work was funded by The Wellcome (grant numbers: 220985, 203077/Z/16/Z, 220977/Z/20/Z, and 222574/Z/21/Z) and the National Institute for Health and Care Research (NIHR), project references: 17/63/and 16/136/33 using UK Aid from the UK government to support global health research, The UK Foreign, Commonwealth and Development Office. The views expressed in this publication are those of the author(s) and not necessarily those of the funding agencies.},},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Detailed understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. textbf{Methods:} Here, we analysed 1139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River, and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction, and virus dispersal between counties was estimated using discrete phylogeographic analysis. textbf{Results:} During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; 9 of which occurred in both waves and 4 seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1, and N.8). Most of the sequenced infections belonged to lineage B.1 (n = 723, 63%), which predominated in both Wave 1 (73%, followed by lineages N.8 [6%] and B.1.1 [6%]) and Wave 2 (56%, followed by lineages B.1.549 [21%] and B.1.530 [5%]). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many Coronavirus Disease 2019 (COVID-19) government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. textbf{Conclusions:} Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission. textbf{Funding:} This work was funded by The Wellcome (grant numbers: 220985, 203077/Z/16/Z, 220977/Z/20/Z, and 222574/Z/21/Z) and the National Institute for Health and Care Research (NIHR), project references: 17/63/and 16/136/33 using UK Aid from the UK government to support global health research, The UK Foreign, Commonwealth and Development Office. The views expressed in this publication are those of the author(s) and not necessarily those of the funding agencies.},
67.
Moussaoui, Majdouline El; Maes, Nathalie; Hong, Samuel L.; Lambert, Nicolas; Gofflot, Stéphanie; Dellot, Patricia; Belhadj, Yasmine; Huynen, Pascale; Hayette, Marie-Pierre; Meex, Cécile; Bontems, Sébastien; Defêche, Justine; Godderis, Lode; Molenberghs, Geert; Meuris, Christelle; Artesi, Maria; Durkin, Keith; Rahmouni, Souad; Grégoire, Céline; Beguin, Yves; Moutschen, Michel; Dellicour, Simon; Darcis, Gilles
Evaluation of Screening Program and Phylogenetic Analysis of SARS-CoV-2 Infections among Hospital Healthcare Workers in Liège, Belgium Journal Article
In: MDPI, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {Evaluation of Screening Program and Phylogenetic Analysis of SARS-CoV-2 Infections among Hospital Healthcare Workers in Liège, Belgium},
author = {Majdouline El Moussaoui and Nathalie Maes and Samuel L. Hong and Nicolas Lambert and Stéphanie Gofflot and Patricia Dellot and Yasmine Belhadj and Pascale Huynen and Marie-Pierre Hayette and Cécile Meex and Sébastien Bontems and Justine Defêche and Lode Godderis and Geert Molenberghs and Christelle Meuris and Maria Artesi and Keith Durkin and Souad Rahmouni and Céline Grégoire and Yves Beguin and Michel Moutschen and Simon Dellicour and Gilles Darcis },
url = {https://www.mdpi.com/1999-4915/14/6/1302},
doi = {10.3390/v14061302 },
year = {2022},
date = {2022-06-09},
urldate = {2022-06-09},
journal = {MDPI},
abstract = {first_pagesettingsOrder Article Reprints
Open AccessArticle
Evaluation of Screening Program and Phylogenetic Analysis of SARS-CoV-2 Infections among Hospital Healthcare Workers in Liège, Belgium
by Majdouline El Moussaoui 1,*ORCID,Nathalie Maes 2ORCID,Samuel L. Hong 3ORCID,Nicolas Lambert 4,Stéphanie Gofflot 5,Patricia Dellot 1,Yasmine Belhadj 1ORCID,Pascale Huynen 6,Marie-Pierre Hayette 6ORCID,Cécile Meex 6,Sébastien Bontems 6,Justine Defêche 6,Lode Godderis 7ORCID,Geert Molenberghs 8,Christelle Meuris 1,Maria Artesi 9,Keith Durkin 9,Souad Rahmouni 10,Céline Grégoire 11,Yves Beguin 11ORCID,Michel Moutschen 1,Simon Dellicour 3,12ORCID andGilles Darcis 1ORCIDremove Hide full author list
1
Department of Infectious Diseases and General Internal Medicine, University Hospital of Liège, 4000 Liege, Belgium
2
Department of Biostatistics and Medico-Economic Information, University Hospital of Liège, 4000 Liege, Belgium
3
Department of Microbiology, Immunology and Transplantation, Rega Institute, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
4
Department of Neurology, University Hospital of Liège, 4000 Liege, Belgium
5
Department of Biothèque Hospitalo-Universitaire de Liège (BHUL), University Hospital of Liège, 4000 Liege, Belgium
6
Department of Clinical Microbiology, University Hospital of Liège, 4000 Liege, Belgium
7
Centre for Environment and Health, Department of Public Health and Primary Care, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
8
Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
9
Laboratory of Human Genetics, GIGA-Institute, University of Liège, 4000 Liege, Belgium
10
Laboratory of Animal Genomics, GIGA-Medical Genomics, GIGA-Institute, University of Liège, 4000 Liege, Belgium
add Show full affiliation list
*
Author to whom correspondence should be addressed.
Viruses 2022, 14(6), 1302; https://doi.org/10.3390/v14061302
Submission received: 16 April 2022 / Revised: 3 June 2022 / Accepted: 9 June 2022 / Published: 14 June 2022
(This article belongs to the Special Issue SARS-CoV-2 Research in Belgium)
Downloadkeyboard_arrow_down Browse Figures Review Reports Versions Notes
Abstract
Healthcare workers (HCWs) are known to be at higher risk of developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections although whether these risks are equal across all occupational roles is uncertain. Identifying these risk factors and understand SARS-CoV-2 transmission pathways in healthcare settings are of high importance to achieve optimal protection measures. We aimed to investigate the implementation of a voluntary screening program for SARS-CoV-2 infections among hospital HCWs and to elucidate potential transmission pathways though phylogenetic analysis before the vaccination era. HCWs of the University Hospital of Liège, Belgium, were invited to participate in voluntary reverse transcriptase-polymerase chain reaction (RT-PCR) assays performed every week from April to December 2020. Phylogenetic analysis of SARS-CoV-2 genomes were performed for a subgroup of 45 HCWs. 5095 samples were collected from 703 HCWs. 212 test results were positive, 15 were indeterminate, and 4868 returned negative. 156 HCWs (22.2%) tested positive at least once during the study period. All SARS-CoV-2 test results returned negative for 547 HCWs (77.8%). Nurses (p < 0.05), paramedics (p < 0.05), and laboratory staff handling respiratory samples (p < 0.01) were at higher risk for being infected compared to the control non-patient facing group. Our phylogenetic analysis revealed that most positive samples corresponded to independent introduction events into the hospital. Our findings add to the growing evidence of differential risks of being infected among HCWs and support the need to implement appropriate protection measures based on each individual’s risk profile to guarantee the protection of both HCWs and patients. Furthermore, our phylogenetic investigations highlight that most positive samples correspond to distinct introduction events into the hospital.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
first_pagesettingsOrder Article Reprints
Open AccessArticle
Evaluation of Screening Program and Phylogenetic Analysis of SARS-CoV-2 Infections among Hospital Healthcare Workers in Liège, Belgium
by Majdouline El Moussaoui 1,*ORCID,Nathalie Maes 2ORCID,Samuel L. Hong 3ORCID,Nicolas Lambert 4,Stéphanie Gofflot 5,Patricia Dellot 1,Yasmine Belhadj 1ORCID,Pascale Huynen 6,Marie-Pierre Hayette 6ORCID,Cécile Meex 6,Sébastien Bontems 6,Justine Defêche 6,Lode Godderis 7ORCID,Geert Molenberghs 8,Christelle Meuris 1,Maria Artesi 9,Keith Durkin 9,Souad Rahmouni 10,Céline Grégoire 11,Yves Beguin 11ORCID,Michel Moutschen 1,Simon Dellicour 3,12ORCID andGilles Darcis 1ORCIDremove Hide full author list
1
Department of Infectious Diseases and General Internal Medicine, University Hospital of Liège, 4000 Liege, Belgium
2
Department of Biostatistics and Medico-Economic Information, University Hospital of Liège, 4000 Liege, Belgium
3
Department of Microbiology, Immunology and Transplantation, Rega Institute, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
4
Department of Neurology, University Hospital of Liège, 4000 Liege, Belgium
5
Department of Biothèque Hospitalo-Universitaire de Liège (BHUL), University Hospital of Liège, 4000 Liege, Belgium
6
Department of Clinical Microbiology, University Hospital of Liège, 4000 Liege, Belgium
7
Centre for Environment and Health, Department of Public Health and Primary Care, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
8
Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
9
Laboratory of Human Genetics, GIGA-Institute, University of Liège, 4000 Liege, Belgium
10
Laboratory of Animal Genomics, GIGA-Medical Genomics, GIGA-Institute, University of Liège, 4000 Liege, Belgium
add Show full affiliation list
*
Author to whom correspondence should be addressed.
Viruses 2022, 14(6), 1302; https://doi.org/10.3390/v14061302
Submission received: 16 April 2022 / Revised: 3 June 2022 / Accepted: 9 June 2022 / Published: 14 June 2022
(This article belongs to the Special Issue SARS-CoV-2 Research in Belgium)
Downloadkeyboard_arrow_down Browse Figures Review Reports Versions Notes
Abstract
Healthcare workers (HCWs) are known to be at higher risk of developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections although whether these risks are equal across all occupational roles is uncertain. Identifying these risk factors and understand SARS-CoV-2 transmission pathways in healthcare settings are of high importance to achieve optimal protection measures. We aimed to investigate the implementation of a voluntary screening program for SARS-CoV-2 infections among hospital HCWs and to elucidate potential transmission pathways though phylogenetic analysis before the vaccination era. HCWs of the University Hospital of Liège, Belgium, were invited to participate in voluntary reverse transcriptase-polymerase chain reaction (RT-PCR) assays performed every week from April to December 2020. Phylogenetic analysis of SARS-CoV-2 genomes were performed for a subgroup of 45 HCWs. 5095 samples were collected from 703 HCWs. 212 test results were positive, 15 were indeterminate, and 4868 returned negative. 156 HCWs (22.2%) tested positive at least once during the study period. All SARS-CoV-2 test results returned negative for 547 HCWs (77.8%). Nurses (p < 0.05), paramedics (p < 0.05), and laboratory staff handling respiratory samples (p < 0.01) were at higher risk for being infected compared to the control non-patient facing group. Our phylogenetic analysis revealed that most positive samples corresponded to independent introduction events into the hospital. Our findings add to the growing evidence of differential risks of being infected among HCWs and support the need to implement appropriate protection measures based on each individual’s risk profile to guarantee the protection of both HCWs and patients. Furthermore, our phylogenetic investigations highlight that most positive samples correspond to distinct introduction events into the hospital.
Open AccessArticle
Evaluation of Screening Program and Phylogenetic Analysis of SARS-CoV-2 Infections among Hospital Healthcare Workers in Liège, Belgium
by Majdouline El Moussaoui 1,*ORCID,Nathalie Maes 2ORCID,Samuel L. Hong 3ORCID,Nicolas Lambert 4,Stéphanie Gofflot 5,Patricia Dellot 1,Yasmine Belhadj 1ORCID,Pascale Huynen 6,Marie-Pierre Hayette 6ORCID,Cécile Meex 6,Sébastien Bontems 6,Justine Defêche 6,Lode Godderis 7ORCID,Geert Molenberghs 8,Christelle Meuris 1,Maria Artesi 9,Keith Durkin 9,Souad Rahmouni 10,Céline Grégoire 11,Yves Beguin 11ORCID,Michel Moutschen 1,Simon Dellicour 3,12ORCID andGilles Darcis 1ORCIDremove Hide full author list
1
Department of Infectious Diseases and General Internal Medicine, University Hospital of Liège, 4000 Liege, Belgium
2
Department of Biostatistics and Medico-Economic Information, University Hospital of Liège, 4000 Liege, Belgium
3
Department of Microbiology, Immunology and Transplantation, Rega Institute, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
4
Department of Neurology, University Hospital of Liège, 4000 Liege, Belgium
5
Department of Biothèque Hospitalo-Universitaire de Liège (BHUL), University Hospital of Liège, 4000 Liege, Belgium
6
Department of Clinical Microbiology, University Hospital of Liège, 4000 Liege, Belgium
7
Centre for Environment and Health, Department of Public Health and Primary Care, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
8
Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
9
Laboratory of Human Genetics, GIGA-Institute, University of Liège, 4000 Liege, Belgium
10
Laboratory of Animal Genomics, GIGA-Medical Genomics, GIGA-Institute, University of Liège, 4000 Liege, Belgium
add Show full affiliation list
*
Author to whom correspondence should be addressed.
Viruses 2022, 14(6), 1302; https://doi.org/10.3390/v14061302
Submission received: 16 April 2022 / Revised: 3 June 2022 / Accepted: 9 June 2022 / Published: 14 June 2022
(This article belongs to the Special Issue SARS-CoV-2 Research in Belgium)
Downloadkeyboard_arrow_down Browse Figures Review Reports Versions Notes
Abstract
Healthcare workers (HCWs) are known to be at higher risk of developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections although whether these risks are equal across all occupational roles is uncertain. Identifying these risk factors and understand SARS-CoV-2 transmission pathways in healthcare settings are of high importance to achieve optimal protection measures. We aimed to investigate the implementation of a voluntary screening program for SARS-CoV-2 infections among hospital HCWs and to elucidate potential transmission pathways though phylogenetic analysis before the vaccination era. HCWs of the University Hospital of Liège, Belgium, were invited to participate in voluntary reverse transcriptase-polymerase chain reaction (RT-PCR) assays performed every week from April to December 2020. Phylogenetic analysis of SARS-CoV-2 genomes were performed for a subgroup of 45 HCWs. 5095 samples were collected from 703 HCWs. 212 test results were positive, 15 were indeterminate, and 4868 returned negative. 156 HCWs (22.2%) tested positive at least once during the study period. All SARS-CoV-2 test results returned negative for 547 HCWs (77.8%). Nurses (p < 0.05), paramedics (p < 0.05), and laboratory staff handling respiratory samples (p < 0.01) were at higher risk for being infected compared to the control non-patient facing group. Our phylogenetic analysis revealed that most positive samples corresponded to independent introduction events into the hospital. Our findings add to the growing evidence of differential risks of being infected among HCWs and support the need to implement appropriate protection measures based on each individual’s risk profile to guarantee the protection of both HCWs and patients. Furthermore, our phylogenetic investigations highlight that most positive samples correspond to distinct introduction events into the hospital.
66.
Ge, Yong; Zhang, Wen-Bin; Wu, Xilin; amd Haiyan Liu, Corrine W Ruktanonchai; amd Yongze Song, Jianghao Wang; Liu, Mengxiao; Yan, Wei; Yang, Juan; amd Sarchil H Qader amd Fatumah Atuhaire, Eimear Cleary; amd Andrew J Tatem amd Shengjie Lai, Nick W Ruktanonchai
Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories Journal Article
In: Nature Commun, vol. 13, no. 3106, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories},
author = {Yong Ge and Wen-Bin Zhang and Xilin Wu and Corrine W Ruktanonchai amd Haiyan Liu and Jianghao Wang amd Yongze Song and Mengxiao Liu and Wei Yan and Juan Yang and Eimear Cleary amd Sarchil H Qader amd Fatumah Atuhaire and Nick W Ruktanonchai amd Andrew J Tatem amd Shengjie Lai},
url = {https://www.nature.com/articles/s41467-022-30897-1#citeas},
doi = {10.1038/s41467-022-30897-1},
year = {2022},
date = {2022-06-03},
urldate = {2022-06-03},
journal = {Nature Commun},
volume = {13},
number = {3106},
abstract = {Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants.
65.
Colosi, Elisabetta; Bassignana, Giulia; Barrat, Alain; Colizza, Vittoria
Modelling COVID-19 in school settings to evaluate prevention and control protocols Journal Article
In: Anaesthesia Critical Care & Pain Medicine, vol. 41, no. 2, pp. 101047, 2022, ISSN: 2352-5568.
Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{COLOSI2022101047,
title = {Modelling COVID-19 in school settings to evaluate prevention and control protocols},
author = {Elisabetta Colosi and Giulia Bassignana and Alain Barrat and Vittoria Colizza},
url = {https://www.sciencedirect.com/science/article/pii/S2352556822000285},
doi = {https://doi.org/10.1016/j.accpm.2022.101047},
issn = {2352-5568},
year = {2022},
date = {2022-04-01},
urldate = {2022-04-01},
journal = {Anaesthesia Critical Care & Pain Medicine},
volume = {41},
number = {2},
pages = {101047},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
64.
Colosi, Elisabetta; Bassignana, Giulia; Contreras, Diego Andrés; Poirier, Canelle; Boëlle, Pierre-Yves; Cauchemez, Simon; Yazdanpanah, Yazdan; Lina, Bruno; Fontanet, Arnaud; Barrat, Alain; others,
Screening and vaccination against COVID-19 to minimise school closure: a modelling study Journal Article
In: The Lancet Infectious Diseases, vol. 2, iss. 7, pp. Pages 977-989, 2022.
Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{colosi2022screening,,
title = {Screening and vaccination against COVID-19 to minimise school closure: a modelling study},
author = {Elisabetta Colosi and Giulia Bassignana and Diego Andrés Contreras and Canelle Poirier and Pierre-Yves Boëlle and Simon Cauchemez and Yazdan Yazdanpanah and Bruno Lina and Arnaud Fontanet and Alain Barrat and others},
url = {https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(22)00138-4/fulltext},
doi = {https://doi.org/10.1016/S1473-3099(22)00138-4},
year = {2022},
date = {2022-04-01},
urldate = {2022-04-01},
journal = {The Lancet Infectious Diseases},
volume = {2},
issue = {7},
pages = {Pages 977-989},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
63.
Bianco, Luca; Moser, Mirko; Silverjand, Andrea; Micheletti, Diego; Lorenzin, Giovanni; Collini, Lucia; Barbareschi, Mattia; Lanzafame, Paolo; Segata, Nicola; Pindo, Massimo; Franceschi, Pietro; Rota-Stabelli, Omar; Rizzoli, Annapaola; Fontana, Paolo; Donati, Claudio
On the Origin and Propagation of the COVID-19 Outbreak in the Italian Province of Trento, a Tourist Region of Northern Italy Journal Article
In: Viruses, vol. 14, iss. 3, no. 580, 2022, ISSN: 1999-4915.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {On the Origin and Propagation of the COVID-19 Outbreak in the Italian Province of Trento, a Tourist Region of Northern Italy},
author = {Luca Bianco and Mirko Moser and Andrea Silverjand and Diego Micheletti and Giovanni Lorenzin and Lucia Collini and Mattia Barbareschi and Paolo Lanzafame and Nicola Segata and Massimo Pindo and Pietro Franceschi and Omar Rota-Stabelli and Annapaola Rizzoli and Paolo Fontana and Claudio Donati},
url = {https://www.mdpi.com/1999-4915/14/3/580},
doi = {10.3390/v14030580},
issn = {1999-4915},
year = {2022},
date = {2022-03-11},
urldate = {2022-03-11},
journal = {Viruses},
volume = {14},
number = {580},
issue = {3},
abstract = {Background: Trentino is an Italian province with a tourism-based economy, bordering the regions of Lombardy and Veneto, where the two earliest and largest outbreaks of COVID-19 occurred in Italy. The earliest cases in Trentino were reported in the first week of March 2020, with most of the cases occurring in the winter sport areas in the Dolomites mountain range. The number of reported cases decreased over the summer months and was followed by a second wave in the autumn and winter of 2020. Methods: we performed high-coverage Oxford Nanopore sequencing of 253 positive SARS-CoV-2 swabs collected in Trentino between March and December 2020. Results: in this work, we analyzed genome sequences to trace the routes through which the virus entered the area, and assessed whether the autumnal resurgence could be attributed to lineages persisting undetected during summer, or as a consequence of new introductions. Conclusions: Comparing the draft genomes analyzed with a large selection of European sequences retrieved from GISAID we found that multiple introductions of the virus occurred at the early stage of the epidemics; the two epidemic waves were unrelated; the second wave was due to reintroductions of the virus in summer when traveling restrictions were uplifted.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Background: Trentino is an Italian province with a tourism-based economy, bordering the regions of Lombardy and Veneto, where the two earliest and largest outbreaks of COVID-19 occurred in Italy. The earliest cases in Trentino were reported in the first week of March 2020, with most of the cases occurring in the winter sport areas in the Dolomites mountain range. The number of reported cases decreased over the summer months and was followed by a second wave in the autumn and winter of 2020. Methods: we performed high-coverage Oxford Nanopore sequencing of 253 positive SARS-CoV-2 swabs collected in Trentino between March and December 2020. Results: in this work, we analyzed genome sequences to trace the routes through which the virus entered the area, and assessed whether the autumnal resurgence could be attributed to lineages persisting undetected during summer, or as a consequence of new introductions. Conclusions: Comparing the draft genomes analyzed with a large selection of European sequences retrieved from GISAID we found that multiple introductions of the virus occurred at the early stage of the epidemics; the two epidemic waves were unrelated; the second wave was due to reintroductions of the virus in summer when traveling restrictions were uplifted.
62.
Manica, Mattia; Litvinova, Maria; Bellis, Alfredo De; Guzzetta, Giorgio; Mancuso, Pamela; Vicentini, Massimo; Venturelli, Francesco; Bisaccia, Eufemia; Bento, Ana I.; Poletti, Piero; Marziano, Valentina; Zardini, Agnese; d'Andrea, Valeria; Trentini, Filippo; Bella, Antonino; Riccardo, Flavia; Pezzotti, Patrizio; Ajelli, Marco; Rossi, Paolo Giorgi; Merler, Stefano; the Reggio Emilia COVID-19 Working Group,
Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data Journal Article
In: arXiv, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data},
author = {Mattia Manica and Maria Litvinova and Alfredo De Bellis and Giorgio Guzzetta and Pamela Mancuso and Massimo Vicentini and Francesco Venturelli and Eufemia Bisaccia and Ana I. Bento and Piero Poletti and Valentina Marziano and Agnese Zardini and Valeria d'Andrea and Filippo Trentini and Antonino Bella and Flavia Riccardo and Patrizio Pezzotti and Marco Ajelli and Paolo Giorgi Rossi and Stefano Merler and the Reggio Emilia COVID-19 Working Group},
url = {https://arxiv.org/abs/2203.07063},
doi = {https://doi.org/10.48550/arXiv.2203.07063},
year = {2022},
date = {2022-03-11},
urldate = {2022-03-11},
journal = {arXiv},
abstract = {Background. During 2021, the COVID-19 pandemic was characterized by the emergence of lineages with increased fitness. For most of these variants, quantitative information is scarce on epidemiological quantities such as the incubation period and generation time, which are critical for both public health decisions and scientific research. Method. We analyzed a dataset collected during contact tracing activities in the province of Reggio Emilia, Italy, throughout 2021. We determined the distributions of the incubation period using information on negative PCR tests and the date of last exposure from 282 symptomatic cases. We estimated the distributions of the intrinsic generation time (the time between the infection dates of an infector and its secondary cases under a fully susceptible population) using a Bayesian inference approach applied to 4,435 SARS-CoV-2 cases clustered in 1,430 households where at least one secondary case was recorded. Results. We estimated a mean incubation period of 4.9 days (95% credible intervals, CrI, 4.4-5.4; 95 percentile of the mean distribution: 1-12) for Alpha and 4.5 days (95%CrI 4.0-5.0; 95 percentile: 1-10) for Delta. The intrinsic generation time was estimated to have a mean of 6.0 days (95% CrI 5.6-6.4; 95 percentile: 1-15) for Alpha and of 6.6 days (95%CrI 6.0-7.3; 95 percentile: 1-18) for Delta. The household serial interval was 2.6 days (95%CrI 2.4-2.7) for Alpha and 2.4 days (95%CrI 2.2-2.6) for Delta, and the estimated proportion of pre-symptomatic transmission was 54-55% for both variants. Conclusions. These results indicate limited differences in the incubation period and intrinsic generation time of SARS-CoV-2 variants Alpha and Delta compared to ancestral lineages. Funding. EU grant 874850 MOOD },
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
Background. During 2021, the COVID-19 pandemic was characterized by the emergence of lineages with increased fitness. For most of these variants, quantitative information is scarce on epidemiological quantities such as the incubation period and generation time, which are critical for both public health decisions and scientific research. Method. We analyzed a dataset collected during contact tracing activities in the province of Reggio Emilia, Italy, throughout 2021. We determined the distributions of the incubation period using information on negative PCR tests and the date of last exposure from 282 symptomatic cases. We estimated the distributions of the intrinsic generation time (the time between the infection dates of an infector and its secondary cases under a fully susceptible population) using a Bayesian inference approach applied to 4,435 SARS-CoV-2 cases clustered in 1,430 households where at least one secondary case was recorded. Results. We estimated a mean incubation period of 4.9 days (95% credible intervals, CrI, 4.4-5.4; 95 percentile of the mean distribution: 1-12) for Alpha and 4.5 days (95%CrI 4.0-5.0; 95 percentile: 1-10) for Delta. The intrinsic generation time was estimated to have a mean of 6.0 days (95% CrI 5.6-6.4; 95 percentile: 1-15) for Alpha and of 6.6 days (95%CrI 6.0-7.3; 95 percentile: 1-18) for Delta. The household serial interval was 2.6 days (95%CrI 2.4-2.7) for Alpha and 2.4 days (95%CrI 2.2-2.6) for Delta, and the estimated proportion of pre-symptomatic transmission was 54-55% for both variants. Conclusions. These results indicate limited differences in the incubation period and intrinsic generation time of SARS-CoV-2 variants Alpha and Delta compared to ancestral lineages. Funding. EU grant 874850 MOOD
61.
Stefanelli, Paola; Group, COVID-19 National Microbiology Surveillance Study
Co-circulation of SARS-CoV-2 Alpha and Gamma variants in Italy, February and March 2021 Journal Article
In: Eurosurveillance, vol. 27, no. 5, pp. 2100429, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {Co-circulation of SARS-CoV-2 Alpha and Gamma variants in Italy, February and March 2021},
author = {Paola Stefanelli et al. and COVID-19 National Microbiology Surveillance Study Group},
url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2022.27.5.2100429},
doi = {10.2807/1560-7917.ES.2022.27.5.2100429},
year = {2022},
date = {2022-02-03},
urldate = {2022-02-03},
journal = {Eurosurveillance},
volume = {27},
number = {5},
pages = {2100429},
abstract = {Background
Several SARS-CoV-2 variants of concern (VOC) have emerged through 2020 and 2021. There is need for tools to estimate the relative transmissibility of emerging variants of SARS-CoV-2 with respect to circulating strains.
Aim
We aimed to assess the prevalence of co-circulating VOC in Italy and estimate their relative transmissibility.
Methods
We conducted two genomic surveillance surveys on 18 February and 18 March 2021 across the whole Italian territory covering 3,243 clinical samples and developed a mathematical model that describes the dynamics of co-circulating strains.
Results
The Alpha variant was already dominant on 18 February in a majority of regions/autonomous provinces (national prevalence: 54%) and almost completely replaced historical lineages by 18 March (dominant across Italy, national prevalence: 86%). We found a substantial proportion of the Gamma variant on 18 February, almost exclusively in central Italy (prevalence: 19%), which remained similar on 18 March. Nationally, the mean relative transmissibility of Alpha ranged at 1.55–1.57 times the level of historical lineages (95% CrI: 1.45–1.66). The relative transmissibility of Gamma varied according to the assumed degree of cross-protection from infection with other lineages and ranged from 1.12 (95% CrI: 1.03–1.23) with complete immune evasion to 1.39 (95% CrI: 1.26–1.56) for complete cross-protection.
Conclusion
We assessed the relative advantage of competing viral strains, using a mathematical model assuming different degrees of cross-protection. We found substantial co-circulation of Alpha and Gamma in Italy. Gamma was not able to outcompete Alpha, probably because of its lower transmissibility.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
Background
Several SARS-CoV-2 variants of concern (VOC) have emerged through 2020 and 2021. There is need for tools to estimate the relative transmissibility of emerging variants of SARS-CoV-2 with respect to circulating strains.
Aim
We aimed to assess the prevalence of co-circulating VOC in Italy and estimate their relative transmissibility.
Methods
We conducted two genomic surveillance surveys on 18 February and 18 March 2021 across the whole Italian territory covering 3,243 clinical samples and developed a mathematical model that describes the dynamics of co-circulating strains.
Results
The Alpha variant was already dominant on 18 February in a majority of regions/autonomous provinces (national prevalence: 54%) and almost completely replaced historical lineages by 18 March (dominant across Italy, national prevalence: 86%). We found a substantial proportion of the Gamma variant on 18 February, almost exclusively in central Italy (prevalence: 19%), which remained similar on 18 March. Nationally, the mean relative transmissibility of Alpha ranged at 1.55–1.57 times the level of historical lineages (95% CrI: 1.45–1.66). The relative transmissibility of Gamma varied according to the assumed degree of cross-protection from infection with other lineages and ranged from 1.12 (95% CrI: 1.03–1.23) with complete immune evasion to 1.39 (95% CrI: 1.26–1.56) for complete cross-protection.
Conclusion
We assessed the relative advantage of competing viral strains, using a mathematical model assuming different degrees of cross-protection. We found substantial co-circulation of Alpha and Gamma in Italy. Gamma was not able to outcompete Alpha, probably because of its lower transmissibility.
Several SARS-CoV-2 variants of concern (VOC) have emerged through 2020 and 2021. There is need for tools to estimate the relative transmissibility of emerging variants of SARS-CoV-2 with respect to circulating strains.
Aim
We aimed to assess the prevalence of co-circulating VOC in Italy and estimate their relative transmissibility.
Methods
We conducted two genomic surveillance surveys on 18 February and 18 March 2021 across the whole Italian territory covering 3,243 clinical samples and developed a mathematical model that describes the dynamics of co-circulating strains.
Results
The Alpha variant was already dominant on 18 February in a majority of regions/autonomous provinces (national prevalence: 54%) and almost completely replaced historical lineages by 18 March (dominant across Italy, national prevalence: 86%). We found a substantial proportion of the Gamma variant on 18 February, almost exclusively in central Italy (prevalence: 19%), which remained similar on 18 March. Nationally, the mean relative transmissibility of Alpha ranged at 1.55–1.57 times the level of historical lineages (95% CrI: 1.45–1.66). The relative transmissibility of Gamma varied according to the assumed degree of cross-protection from infection with other lineages and ranged from 1.12 (95% CrI: 1.03–1.23) with complete immune evasion to 1.39 (95% CrI: 1.26–1.56) for complete cross-protection.
Conclusion
We assessed the relative advantage of competing viral strains, using a mathematical model assuming different degrees of cross-protection. We found substantial co-circulation of Alpha and Gamma in Italy. Gamma was not able to outcompete Alpha, probably because of its lower transmissibility.
60.
Liu, Quan-Hui; Zhang, Juanjuan; Peng, Cheng; Litvinova, Maria; Huang, Shudong; Poletti, Piero; Trentini, Filippo; Guzzetta, Giorgio; Marziano, Valentina; Zhou, Tao; Viboud, Cecile; Bento, Ana I.; Lv, Jiancheng; Vespignani, Alessandro; Merler, Stefano; Yu, Hongjie; Ajelli, Marco
Model-based evaluation of alternative reactive class closure strategies against COVID-19. Journal Article
In: 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Model-based evaluation of alternative reactive class closure strategies against COVID-19.},
author = {Quan-Hui Liu and Juanjuan Zhang and Cheng Peng and Maria Litvinova and Shudong Huang and Piero Poletti and Filippo Trentini and Giorgio Guzzetta and Valentina Marziano and Tao Zhou and Cecile Viboud and Ana I. Bento and Jiancheng Lv and Alessandro Vespignani and Stefano Merler and Hongjie Yu and Marco Ajelli
},
url = {https://www.nature.com/articles/s41467-021-27939-5#article-info},
doi = {10.1038/s41467-021-27939-5},
year = {2022},
date = {2022-01-14},
urldate = {2022-01-14},
abstract = {There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, we developed a data-driven computational model of SARS-CoV-2 transmission. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 17.3% (95%CI: 8.0–26.8%), due to the low probability of timely identification of infections in the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Depending on the contribution of schools to transmission, this strategy can greatly reduce COVID-19 burden even when school contribution to transmission and immunity in the population is low. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to be rolled out.
},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, we developed a data-driven computational model of SARS-CoV-2 transmission. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 17.3% (95%CI: 8.0–26.8%), due to the low probability of timely identification of infections in the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Depending on the contribution of schools to transmission, this strategy can greatly reduce COVID-19 burden even when school contribution to transmission and immunity in the population is low. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to be rolled out.
59.
Viana, Raquel; Moyo, Sikhulile; Amoako, Daniel G; Tegally, Houriiyah; Scheepers, Cathrine; Althaus, Christian L; Anyaneji, Ugochukwu J; Bester, Phillip A; Boni, Maciej F; Chand, Mohammed; others,
Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa Journal Article
In: Nature, vol. 603, no. 7902, pp. 679-686, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa},
author = {Raquel Viana and Sikhulile Moyo and Daniel G Amoako and Houriiyah Tegally and Cathrine Scheepers and Christian L Althaus and Ugochukwu J Anyaneji and Phillip A Bester and Maciej F Boni and Mohammed Chand and others},
url = {https://www.nature.com/articles/s41586-022-04411-y#citeas},
doi = {10.1038/s41586-022-04411-y},
year = {2022},
date = {2022-01-07},
urldate = {2022-01-07},
journal = {Nature},
volume = {603},
number = {7902},
pages = {679-686},
abstract = {The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) variants, respectively1,2,3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron, B.1.1.529) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, which are predicted to influence antibody neutralization and spike function4. Here we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) variants, respectively1,2,3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron, B.1.1.529) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, which are predicted to influence antibody neutralization and spike function4. Here we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.
58.
Syed, Mehtab; Arsevska, Elena; Roche, Mathieu; Teisseire, Maguelonne
Feature Selection for Sentiment Classification of COVID-19 Tweets: H-TFIDF Featuring BERT Proceedings Article
In: SciTePress, (Ed.): pp. 648-656, 2022, ISBN: 978-989-758-552-4.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet, Text mining
@inproceedings{@conference{healthinf22,,
title = {Feature Selection for Sentiment Classification of COVID-19 Tweets: H-TFIDF Featuring BERT},
author = {Mehtab Syed and Elena Arsevska and Mathieu Roche and Maguelonne Teisseire},
editor = {SciTePress},
url = {https://www.scitepress.org/Link.aspx?doi=10.5220/0010887800003123},
doi = {10.5220/0010887800003123},
isbn = {978-989-758-552-4},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF},
pages = {648-656},
abstract = {In the first quarter of 2020, the World Health Organization (WHO) declared COVID-19 a public health emergency around the globe. Different users from all over the world shared their opinions about COVID-19 on social media platforms such as Twitter and Facebook. At the beginning of the pandemic, it became relevant to assess public opinions regarding COVID-19 using data available on social media. We used a recently proposed hierarchy-based measure for tweet analysis (H-TFIDF) for feature extraction over sentiment classification of tweets. We assessed how H-TFIDF and concatenation of H-TFIDF with bidirectional encoder representations from transformers (BH-TFIDF) perform over state-of-the-art bag-of-words (BOW) and term frequency-inverse document frequency (TF-IDF) features for sentiment classification of COVID-19 tweets. A uniform experimental setup of the training-test (90% and 10%) split scheme was used to train the classifier. Moreover, evaluation was performed with the gold standard expert labeled dataset to measure precision for each binary classified class. },
keywords = {Covid-19 (Coronavirus), OpenDataSet, Text mining},
pubstate = {published},
tppubtype = {inproceedings}
}
In the first quarter of 2020, the World Health Organization (WHO) declared COVID-19 a public health emergency around the globe. Different users from all over the world shared their opinions about COVID-19 on social media platforms such as Twitter and Facebook. At the beginning of the pandemic, it became relevant to assess public opinions regarding COVID-19 using data available on social media. We used a recently proposed hierarchy-based measure for tweet analysis (H-TFIDF) for feature extraction over sentiment classification of tweets. We assessed how H-TFIDF and concatenation of H-TFIDF with bidirectional encoder representations from transformers (BH-TFIDF) perform over state-of-the-art bag-of-words (BOW) and term frequency-inverse document frequency (TF-IDF) features for sentiment classification of COVID-19 tweets. A uniform experimental setup of the training-test (90% and 10%) split scheme was used to train the classifier. Moreover, evaluation was performed with the gold standard expert labeled dataset to measure precision for each binary classified class.
57.
Planas, Delphine; Saunders, Nell; Maes, Piet; Guivel-Benhassine, Florence; Planchais, Cyril; Buchrieser, Julian; Bolland, William-Henry; Porrot, Françoise; Staropoli, Isabelle; Lemoine, Frederic; Péré, Hélène; Veyer, David; Puech, Julien; Rodary, Julien; Baele, Guy; Dellicour, Simon; Raymenants, Joren; Gorissen, Sarah; Geenen, Caspar; Vanmechelen, Bert; Wawina-Bokalanga, Tony; Martí-Carreras, Joan; Cuypers, Lize; Sève, Aymeric; Hocqueloux, Laurent; Prazuck, Thierry; Rey, Félix A.; Simon-Loriere, Etienne; Bruel, Timothée; Mouquet, Hugo; André, Emmanuel; Schwart, Olivier
Considerable escape of SARS-CoV-2 Omicron to antibody neutralization Journal Article
In: Nature, vol. 602, pp. 671–675, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Considerable escape of SARS-CoV-2 Omicron to antibody neutralization},
author = {Delphine Planas and Nell Saunders and Piet Maes and Florence Guivel-Benhassine and Cyril Planchais and Julian Buchrieser and William-Henry Bolland and Françoise Porrot and Isabelle Staropoli and Frederic Lemoine and Hélène Péré and David Veyer and Julien Puech and Julien Rodary and Guy Baele and Simon Dellicour and Joren Raymenants and Sarah Gorissen and Caspar Geenen and Bert Vanmechelen and Tony Wawina-Bokalanga and Joan Martí-Carreras and Lize Cuypers and Aymeric Sève and Laurent Hocqueloux and Thierry Prazuck and Félix A. Rey and Etienne Simon-Loriere and Timothée Bruel and Hugo Mouquet and Emmanuel André and Olivier Schwart },
url = {https://www.nature.com/articles/s41586-021-04389-z#citeas},
doi = {https://doi.org/10.1038/s41586-021-04389-z},
year = {2021},
date = {2021-12-23},
urldate = {2021-12-23},
journal = {Nature},
volume = {602},
pages = {671–675},
abstract = {The SARS-CoV-2 Omicron variant was first identified in November 2021 in Botswana and South Africa1,2,3. It has since spread to many countries and is expected to rapidly become dominant worldwide. The lineage is characterized by the presence of around 32 mutations in spike—located mostly in the N-terminal domain and the receptor-binding domain—that may enhance viral fitness and enable antibody evasion. Here we isolated an infectious Omicron virus in Belgium from a traveller returning from Egypt. We examined its sensitivity to nine monoclonal antibodies that have been clinically approved or are in development4, and to antibodies present in 115 serum samples from COVID-19 vaccine recipients or individuals who have recovered from COVID-19. Omicron was completely or partially resistant to neutralization by all monoclonal antibodies tested. Sera from recipients of the Pfizer or AstraZeneca vaccine, sampled five months after complete vaccination, barely inhibited Omicron. Sera from COVID-19-convalescent patients collected 6 or 12 months after symptoms displayed low or no neutralizing activity against Omicron. Administration of a booster Pfizer dose as well as vaccination of previously infected individuals generated an anti-Omicron neutralizing response, with titres 6-fold to 23-fold lower against Omicron compared with those against Delta. Thus, Omicron escapes most therapeutic monoclonal antibodies and, to a large extent, vaccine-elicited antibodies. However, Omicron is neutralized by antibodies generated by a booster vaccine dose.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The SARS-CoV-2 Omicron variant was first identified in November 2021 in Botswana and South Africa1,2,3. It has since spread to many countries and is expected to rapidly become dominant worldwide. The lineage is characterized by the presence of around 32 mutations in spike—located mostly in the N-terminal domain and the receptor-binding domain—that may enhance viral fitness and enable antibody evasion. Here we isolated an infectious Omicron virus in Belgium from a traveller returning from Egypt. We examined its sensitivity to nine monoclonal antibodies that have been clinically approved or are in development4, and to antibodies present in 115 serum samples from COVID-19 vaccine recipients or individuals who have recovered from COVID-19. Omicron was completely or partially resistant to neutralization by all monoclonal antibodies tested. Sera from recipients of the Pfizer or AstraZeneca vaccine, sampled five months after complete vaccination, barely inhibited Omicron. Sera from COVID-19-convalescent patients collected 6 or 12 months after symptoms displayed low or no neutralizing activity against Omicron. Administration of a booster Pfizer dose as well as vaccination of previously infected individuals generated an anti-Omicron neutralizing response, with titres 6-fold to 23-fold lower against Omicron compared with those against Delta. Thus, Omicron escapes most therapeutic monoclonal antibodies and, to a large extent, vaccine-elicited antibodies. However, Omicron is neutralized by antibodies generated by a booster vaccine dose.
56.
Mazzoli, Mattia; Domenico, Laura Di; Consortium, EMERGEN; Colizza, Vittoria
Early assessment of the Omicron variant’s presence and growth rate in regions of France Technical Report
2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@techreport{nokey,
title = {Early assessment of the Omicron variant’s presence and growth rate in regions of France },
author = { Mattia Mazzoli and Laura Di Domenico and EMERGEN Consortium and Vittoria Colizza},
url = {https://www.epicx-lab.com/uploads/9/6/9/4/9694133/inserm_omicron_frequency_20211222.pdf},
year = {2021},
date = {2021-12-22},
urldate = {2021-12-22},
abstract = {Using genomic surveillance data from Flash surveys up to December 20, we estimate the doubling time of Omicron growth at the national level to be in the range between 1.8 and 2.2 days, confirming the rapid growth that was already observed in other countries. Omicron is predicted to become dominant in France by the end of week 51 (i.e. current week, starting December 20). Flash data suggest a higher prevalence 2 epicx-lab.com of the new variant concentrated in the Île-de-France (IDF) and Centre Val de Loire (CVL) regions compared to the rest of the country, whereas screening data adjusted with genomic data indicate a larger and more uniform expansion on the national territory. Only two regions (Île-de-France and Centre-Val de Loire) reported exploitable Omicron frequencies to assess the variant dynamics in time within the region, showing already a substantial spread in the community. Using Flash data, we estimate short doubling times, 1.8 days in Île-de-France and 2.5 days in Centre-Val de Loire, in agreement with national estimates. This indicates that Omicron has likely become dominant last week in Île-de-France (week 50, starting December 13), and it is passing the 50% threshold in current week in Centre-Val de Loire (week 51, starting December 20). Slower dynamics are predicted by the adjusted screening data. Additional data will be needed to consolidate results, reduce uncertainties, and provide estimates for the other regions. The epidemic situation is expected to accelerate considerably in the upcoming days and weeks. },
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {techreport}
}
Using genomic surveillance data from Flash surveys up to December 20, we estimate the doubling time of Omicron growth at the national level to be in the range between 1.8 and 2.2 days, confirming the rapid growth that was already observed in other countries. Omicron is predicted to become dominant in France by the end of week 51 (i.e. current week, starting December 20). Flash data suggest a higher prevalence 2 epicx-lab.com of the new variant concentrated in the Île-de-France (IDF) and Centre Val de Loire (CVL) regions compared to the rest of the country, whereas screening data adjusted with genomic data indicate a larger and more uniform expansion on the national territory. Only two regions (Île-de-France and Centre-Val de Loire) reported exploitable Omicron frequencies to assess the variant dynamics in time within the region, showing already a substantial spread in the community. Using Flash data, we estimate short doubling times, 1.8 days in Île-de-France and 2.5 days in Centre-Val de Loire, in agreement with national estimates. This indicates that Omicron has likely become dominant last week in Île-de-France (week 50, starting December 13), and it is passing the 50% threshold in current week in Centre-Val de Loire (week 51, starting December 20). Slower dynamics are predicted by the adjusted screening data. Additional data will be needed to consolidate results, reduce uncertainties, and provide estimates for the other regions. The epidemic situation is expected to accelerate considerably in the upcoming days and weeks.
55.
Marziano, Valentina; al.,
The effect of COVID-19 vaccination in Italy and perspectives for living with the virus Journal Article
In: Nature Communications, vol. 12, no. 7272, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {The effect of COVID-19 vaccination in Italy and perspectives for living with the virus},
author = {Valentina Marziano and al.},
url = {https://www.nature.com/articles/s41467-021-27532-w#citeas},
doi = {10.1038/s41467-021-27532-w},
year = {2021},
date = {2021-12-14},
urldate = {2021-12-14},
journal = {Nature Communications},
volume = {12},
number = {7272},
abstract = {COVID-19 vaccination is allowing a progressive release of restrictions worldwide. Using a mathematical model, we assess the impact of vaccination in Italy since December 27, 2020 and evaluate prospects for societal reopening after emergence of the Delta variant. We estimate that by June 30, 2021, COVID-19 vaccination allowed the resumption of about half of pre-pandemic social contacts. In absence of vaccination, the same number of cases is obtained by resuming only about one third of pre-pandemic contacts, with about 12,100 (95% CI: 6,600-21,000) extra deaths (+27%; 95% CI: 15–47%). Vaccination offset the effect of the Delta variant in summer 2021. The future epidemic trend is surrounded by substantial uncertainty. Should a pediatric vaccine (for ages 5 and older) be licensed and a coverage >90% be achieved in all age classes, a return to pre-pandemic society could be envisioned. Increasing vaccination coverage will allow further reopening even in absence of a pediatric vaccine.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
COVID-19 vaccination is allowing a progressive release of restrictions worldwide. Using a mathematical model, we assess the impact of vaccination in Italy since December 27, 2020 and evaluate prospects for societal reopening after emergence of the Delta variant. We estimate that by June 30, 2021, COVID-19 vaccination allowed the resumption of about half of pre-pandemic social contacts. In absence of vaccination, the same number of cases is obtained by resuming only about one third of pre-pandemic contacts, with about 12,100 (95% CI: 6,600-21,000) extra deaths (+27%; 95% CI: 15–47%). Vaccination offset the effect of the Delta variant in summer 2021. The future epidemic trend is surrounded by substantial uncertainty. Should a pediatric vaccine (for ages 5 and older) be licensed and a coverage >90% be achieved in all age classes, a return to pre-pandemic society could be envisioned. Increasing vaccination coverage will allow further reopening even in absence of a pediatric vaccine.
54.
Valdano, Eugenio; Lee, Jonggul; Rubrichi, Stefania; Colizza, Vittoria
Mobility during the first week of the second lockdown in France Technical Report
2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@techreport{nokey,
title = {Mobility during the first week of the second lockdown in France},
author = {Eugenio Valdano and Jonggul Lee and Stefania Rubrichi and Vittoria Colizza},
url = {http://www.epicx-lab.com/uploads/9/6/9/4/9694133/inserm_covid-19-lockdown2-mobility_20201112.pdf},
year = {2021},
date = {2021-12-11},
urldate = {2021-12-11},
abstract = {France is on a second lockdown to stop the second wave of COVID-19. Closures and restrictions are
impacting mobility at different spatial and temporal scales. We use mobile phone data to analyze mobility
patterns during the first full working week of the current lockdown (Nov 2-6, 2020). We break down our
analysis by space (country-level, regional, local mobility), by time (weekly, daily, hourly), and by age class
(young, adults, seniors). We compare mobility patterns with the ones registered during the first full
working week of the first lockdown (Mar 23-27, 2020). Current mobility is down 33% below prepandemic levels, achieving a much smaller reduction than the 1st lockdown (67% below pre-pandemic
levels). Daytime mobility reductions follow daily averages, but modest reductions are observed during
morning rush hours – a key feature of the current lockdown, not shared by the previous one, and likely
due to keeping school opens and larger number of productive sectors open. An analysis of regional
mobility highlightsa split between most regions reaching below-average mobility reductions, and Île-deFrance reaching a markedly above-average reduction. Regional variations in this 2ndlockdown are
correlated with what measured in the 1st, but more pronounced. Analysis at a finer spatial scale shows
that higher-than-average reductions are concentrated in the Paris area, and close to the mountains. We
also measure a strong association between mobility reduction and socioeconomic indicators, indicating
that mobility restrictions are most effective among wealthier population strata, confirming results
already found during the 1st lockdown. Finally, we measure trafficamong France’s largest cities, and find
it to be consistently higher than during the 1st lockdown, when it all but stopped. Our analysis provides a
first quantitative assessment of the ongoing lockdown on population mobility patterns, comparing them
to the 1st lockdown. It helps evaluate the performance of current policies, and inform future possible
adjustments.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {techreport}
}
France is on a second lockdown to stop the second wave of COVID-19. Closures and restrictions are
impacting mobility at different spatial and temporal scales. We use mobile phone data to analyze mobility
patterns during the first full working week of the current lockdown (Nov 2-6, 2020). We break down our
analysis by space (country-level, regional, local mobility), by time (weekly, daily, hourly), and by age class
(young, adults, seniors). We compare mobility patterns with the ones registered during the first full
working week of the first lockdown (Mar 23-27, 2020). Current mobility is down 33% below prepandemic levels, achieving a much smaller reduction than the 1st lockdown (67% below pre-pandemic
levels). Daytime mobility reductions follow daily averages, but modest reductions are observed during
morning rush hours – a key feature of the current lockdown, not shared by the previous one, and likely
due to keeping school opens and larger number of productive sectors open. An analysis of regional
mobility highlightsa split between most regions reaching below-average mobility reductions, and Île-deFrance reaching a markedly above-average reduction. Regional variations in this 2ndlockdown are
correlated with what measured in the 1st, but more pronounced. Analysis at a finer spatial scale shows
that higher-than-average reductions are concentrated in the Paris area, and close to the mountains. We
also measure a strong association between mobility reduction and socioeconomic indicators, indicating
that mobility restrictions are most effective among wealthier population strata, confirming results
already found during the 1st lockdown. Finally, we measure trafficamong France’s largest cities, and find
it to be consistently higher than during the 1st lockdown, when it all but stopped. Our analysis provides a
first quantitative assessment of the ongoing lockdown on population mobility patterns, comparing them
to the 1st lockdown. It helps evaluate the performance of current policies, and inform future possible
adjustments.
impacting mobility at different spatial and temporal scales. We use mobile phone data to analyze mobility
patterns during the first full working week of the current lockdown (Nov 2-6, 2020). We break down our
analysis by space (country-level, regional, local mobility), by time (weekly, daily, hourly), and by age class
(young, adults, seniors). We compare mobility patterns with the ones registered during the first full
working week of the first lockdown (Mar 23-27, 2020). Current mobility is down 33% below prepandemic levels, achieving a much smaller reduction than the 1st lockdown (67% below pre-pandemic
levels). Daytime mobility reductions follow daily averages, but modest reductions are observed during
morning rush hours – a key feature of the current lockdown, not shared by the previous one, and likely
due to keeping school opens and larger number of productive sectors open. An analysis of regional
mobility highlightsa split between most regions reaching below-average mobility reductions, and Île-deFrance reaching a markedly above-average reduction. Regional variations in this 2ndlockdown are
correlated with what measured in the 1st, but more pronounced. Analysis at a finer spatial scale shows
that higher-than-average reductions are concentrated in the Paris area, and close to the mountains. We
also measure a strong association between mobility reduction and socioeconomic indicators, indicating
that mobility restrictions are most effective among wealthier population strata, confirming results
already found during the 1st lockdown. Finally, we measure trafficamong France’s largest cities, and find
it to be consistently higher than during the 1st lockdown, when it all but stopped. Our analysis provides a
first quantitative assessment of the ongoing lockdown on population mobility patterns, comparing them
to the 1st lockdown. It helps evaluate the performance of current policies, and inform future possible
adjustments.
53.
Domenico, Laura Di
Adherence and sustainability of interventions informing optimal control against the COVID-19 pandemic Journal Article
In: Nature Communications, vol. 1, no. 57, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Adherence and sustainability of interventions informing optimal control against the COVID-19 pandemic},
author = {Laura Di Domenico et al.},
url = {https://www.nature.com/articles/s43856-021-00057-5},
doi = {10.1038/s43856-021-00057-5},
year = {2021},
date = {2021-12-06},
urldate = {2021-12-06},
journal = {Nature Communications},
volume = {1},
number = {57},
abstract = {After one year of stop-and-go COVID-19 mitigation, in the spring of 2021 European countries still experienced sustained viral circulation due to the Alpha variant. As the prospect of entering a new pandemic phase through vaccination was drawing closer, a key challenge remained on how to balance the efficacy of long-lasting interventions and their impact on the quality of life.
We show that moderate interventions would require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Shorter strict lockdowns are largely more effective than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
After one year of stop-and-go COVID-19 mitigation, in the spring of 2021 European countries still experienced sustained viral circulation due to the Alpha variant. As the prospect of entering a new pandemic phase through vaccination was drawing closer, a key challenge remained on how to balance the efficacy of long-lasting interventions and their impact on the quality of life.
We show that moderate interventions would require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Shorter strict lockdowns are largely more effective than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom.
We show that moderate interventions would require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Shorter strict lockdowns are largely more effective than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom.
52.
Cereda, Danilo; Manica, Mattia; Tirani, Marcello; Rovida, Francesca; Demicheli, Vittorio; Ajelli, Marco; Poletti, Piero; Trentini, Filippo; Guzzetta, Giorgio; Marziano, Valentina; Piccarreta, Raffaella; Barone, Antonio; Magoni, Michele; Deandrea, Silvia; Diurno, Giulio; Lombardo, Massimo; Faccini, Marino; Pan, Angelo; Bruno, Raffaele; Pariani, Elena; Grasselli, Giacomo; Piatti, Alessandra; Gramegna, Maria; Baldanti, Fausto; Melegaro, Alessia; Merler, Stefano
The early phase of the COVID-19 epidemic in Lombardy, Italy Journal Article
In: Epidemics, vol. 37, pp. 100528, 2021, ISSN: 1755-4365.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{CEREDA2021100528,,
title = {The early phase of the COVID-19 epidemic in Lombardy, Italy},
author = {Danilo Cereda and Mattia Manica and Marcello Tirani and Francesca Rovida and Vittorio Demicheli and Marco Ajelli and Piero Poletti and Filippo Trentini and Giorgio Guzzetta and Valentina Marziano and Raffaella Piccarreta and Antonio Barone and Michele Magoni and Silvia Deandrea and Giulio Diurno and Massimo Lombardo and Marino Faccini and Angelo Pan and Raffaele Bruno and Elena Pariani and Giacomo Grasselli and Alessandra Piatti and Maria Gramegna and Fausto Baldanti and Alessia Melegaro and Stefano Merler},
url = {https://www.sciencedirect.com/science/article/pii/S1755436521000724},
doi = {https://doi.org/10.1016/j.epidem.2021.100528},
issn = {1755-4365},
year = {2021},
date = {2021-12-01},
urldate = {2021-12-01},
journal = {Epidemics},
volume = {37},
pages = {100528},
abstract = {Background
In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread.
Methods
We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARS-CoV-2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2.
Results
Epidemiological investigations detected over 500 cases (median age: 69, IQR: 57–78) before the first COVID-19 diagnosed patient (February 20, 2020), and suggested that SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities with sustained transmission across all the Lombardy provinces. We estimated the mean serial interval to be 6.6 days (95% CrI, 0.7–19). Our estimates of the basic reproduction number range from 2.6 in Pavia (95% CI, 2.1–3.2) to 3.3 in Milan (95% CI, 2.9–3.8). A decreasing trend in the net reproduction number was observed following the detection of the first case.
Conclusions
At the time of first case notification, COVID-19 was already widespread in the entire Lombardy region. This may explain the large number of critical cases experienced by this region in a very short timeframe. The slight decrease of the reproduction number observed in the early days after February 20, 2020 might be due to increased population awareness and early interventions implemented before the regional lockdown imposed on March 8, 2020.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Background
In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread.
Methods
We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARS-CoV-2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2.
Results
Epidemiological investigations detected over 500 cases (median age: 69, IQR: 57–78) before the first COVID-19 diagnosed patient (February 20, 2020), and suggested that SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities with sustained transmission across all the Lombardy provinces. We estimated the mean serial interval to be 6.6 days (95% CrI, 0.7–19). Our estimates of the basic reproduction number range from 2.6 in Pavia (95% CI, 2.1–3.2) to 3.3 in Milan (95% CI, 2.9–3.8). A decreasing trend in the net reproduction number was observed following the detection of the first case.
Conclusions
At the time of first case notification, COVID-19 was already widespread in the entire Lombardy region. This may explain the large number of critical cases experienced by this region in a very short timeframe. The slight decrease of the reproduction number observed in the early days after February 20, 2020 might be due to increased population awareness and early interventions implemented before the regional lockdown imposed on March 8, 2020.
In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread.
Methods
We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARS-CoV-2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2.
Results
Epidemiological investigations detected over 500 cases (median age: 69, IQR: 57–78) before the first COVID-19 diagnosed patient (February 20, 2020), and suggested that SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities with sustained transmission across all the Lombardy provinces. We estimated the mean serial interval to be 6.6 days (95% CrI, 0.7–19). Our estimates of the basic reproduction number range from 2.6 in Pavia (95% CI, 2.1–3.2) to 3.3 in Milan (95% CI, 2.9–3.8). A decreasing trend in the net reproduction number was observed following the detection of the first case.
Conclusions
At the time of first case notification, COVID-19 was already widespread in the entire Lombardy region. This may explain the large number of critical cases experienced by this region in a very short timeframe. The slight decrease of the reproduction number observed in the early days after February 20, 2020 might be due to increased population awareness and early interventions implemented before the regional lockdown imposed on March 8, 2020.
51.
Pullano, Giulia; Domenico, Laura Di; Colizza, Vittoria
Telework and other measures reducing the presence at work to slow down COVID-19pdm in France (Sept 2020) Technical Report
2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@techreport{nokey,
title = {Telework and other measures reducing the presence at work to slow down COVID-19pdm in France (Sept 2020)},
author = {Giulia Pullano and Laura Di Domenico and Vittoria Colizza},
url = {http://www.epicx-lab.com/uploads/9/6/9/4/9694133/inserm_covid-19-telework.pdf},
year = {2021},
date = {2021-11-28},
urldate = {2021-11-28},
abstract = {COVID-19 pandemic shows a clear and substantial increase of activity in France since summer 2020.
Certain regions are in highly vulnerable situations, with large number of hospitalizations per day,
important fraction of ICU beds occupied, and short doubling times (<2 weeks). At the same time,
activities are increasing since the beginning of September, with the reopening of schools and the return
to work after summer holidays (not yet reaching pre-pandemic levels), leaving further opportunities for
the virus to spread. Using mathematical models calibrated to the observed epidemic trajectory in each
region, this report analyzes possible scenarios of telework and other means to reduce the presence at
work, and assesses their impact on the epidemic trajectory in the following weeks. Numerical results
confirm that telework and other measures reducing the presence at work under realistic assumptions
may decelerate the epidemic curve gaining few weeks of time, but would not be enough to revert the
increasing tendency of the curve, unless coupled with other contact reduction measures. The situation is
particularly critical in IDF. In these conditions, if nothing changes, the level of hospitalizations of the peak
of the first wave is expected to be reached in IDF in about a month from now (earlier, if return to work
increases in the following weeks as suggested by the trend in the data and if not contrasted by telework).
Explicit guidance on telework and interventions to facilitate its application to all professional categories
who can adopt it should be urgently provided. This standard should be kept as a routine measure of
epidemic control for several months. More restrictive measures involving the closure of certain activities
to reduce avoidable contacts are urgently needed to slow down the epidemic increase to levels that are
manageable by the healthcare system. This analysis cannot account for the effect of the measures
implemented today},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {techreport}
}
COVID-19 pandemic shows a clear and substantial increase of activity in France since summer 2020.
Certain regions are in highly vulnerable situations, with large number of hospitalizations per day,
important fraction of ICU beds occupied, and short doubling times (<2 weeks). At the same time,
activities are increasing since the beginning of September, with the reopening of schools and the return
to work after summer holidays (not yet reaching pre-pandemic levels), leaving further opportunities for
the virus to spread. Using mathematical models calibrated to the observed epidemic trajectory in each
region, this report analyzes possible scenarios of telework and other means to reduce the presence at
work, and assesses their impact on the epidemic trajectory in the following weeks. Numerical results
confirm that telework and other measures reducing the presence at work under realistic assumptions
may decelerate the epidemic curve gaining few weeks of time, but would not be enough to revert the
increasing tendency of the curve, unless coupled with other contact reduction measures. The situation is
particularly critical in IDF. In these conditions, if nothing changes, the level of hospitalizations of the peak
of the first wave is expected to be reached in IDF in about a month from now (earlier, if return to work
increases in the following weeks as suggested by the trend in the data and if not contrasted by telework).
Explicit guidance on telework and interventions to facilitate its application to all professional categories
who can adopt it should be urgently provided. This standard should be kept as a routine measure of
epidemic control for several months. More restrictive measures involving the closure of certain activities
to reduce avoidable contacts are urgently needed to slow down the epidemic increase to levels that are
manageable by the healthcare system. This analysis cannot account for the effect of the measures
implemented today
Certain regions are in highly vulnerable situations, with large number of hospitalizations per day,
important fraction of ICU beds occupied, and short doubling times (<2 weeks). At the same time,
activities are increasing since the beginning of September, with the reopening of schools and the return
to work after summer holidays (not yet reaching pre-pandemic levels), leaving further opportunities for
the virus to spread. Using mathematical models calibrated to the observed epidemic trajectory in each
region, this report analyzes possible scenarios of telework and other means to reduce the presence at
work, and assesses their impact on the epidemic trajectory in the following weeks. Numerical results
confirm that telework and other measures reducing the presence at work under realistic assumptions
may decelerate the epidemic curve gaining few weeks of time, but would not be enough to revert the
increasing tendency of the curve, unless coupled with other contact reduction measures. The situation is
particularly critical in IDF. In these conditions, if nothing changes, the level of hospitalizations of the peak
of the first wave is expected to be reached in IDF in about a month from now (earlier, if return to work
increases in the following weeks as suggested by the trend in the data and if not contrasted by telework).
Explicit guidance on telework and interventions to facilitate its application to all professional categories
who can adopt it should be urgently provided. This standard should be kept as a routine measure of
epidemic control for several months. More restrictive measures involving the closure of certain activities
to reduce avoidable contacts are urgently needed to slow down the epidemic increase to levels that are
manageable by the healthcare system. This analysis cannot account for the effect of the measures
implemented today
50.
Pullano, Giulia; Domenico, Laura Di; Sabbatini, Chiara E.; Colizza, Vittoria
Expected impact of exit strategies after the second lockdown - France, Nov 2020 Technical Report
2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@techreport{nokey,
title = {Expected impact of exit strategies after the second lockdown - France, Nov 2020},
author = {Giulia Pullano and Laura Di Domenico and Chiara E. Sabbatini and Vittoria Colizza},
url = {https://www.epicx-lab.com/uploads/9/6/9/4/9694133/inserm_covid-19-lockdown_schools_open-20201117.pdf},
year = {2021},
date = {2021-11-17},
urldate = {2021-11-17},
abstract = {This report is an update of previous reports (Report #19, Report #21) on the expected impact of the
second lockdown implemented in France on Friday, October 30 to suppress the second wave of COVID-19
epidemic. We provide updated projections simulating a mild lockdown with schools open informed on the
estimates on mobility reduction recorded during the first week of lockdown from mobile phone data
(Report #22), and explore different exit strategies. The current report focuses on Île-de-France; analyses
for other regions will follow. },
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {techreport}
}
This report is an update of previous reports (Report #19, Report #21) on the expected impact of the
second lockdown implemented in France on Friday, October 30 to suppress the second wave of COVID-19
epidemic. We provide updated projections simulating a mild lockdown with schools open informed on the
estimates on mobility reduction recorded during the first week of lockdown from mobile phone data
(Report #22), and explore different exit strategies. The current report focuses on Île-de-France; analyses
for other regions will follow.
second lockdown implemented in France on Friday, October 30 to suppress the second wave of COVID-19
epidemic. We provide updated projections simulating a mild lockdown with schools open informed on the
estimates on mobility reduction recorded during the first week of lockdown from mobile phone data
(Report #22), and explore different exit strategies. The current report focuses on Île-de-France; analyses
for other regions will follow.
49.
Kraemer, Moritz U. G.; Fraser, Oliver G. Pybusand; Cauchemez, Christophe; Rambaut, Simon; Cowling, Andrew; Benjamin, J.
Monitoring key epidemiological parameters of SARS-CoV-2 transmission Journal Article
In: Nature Medicine, vol. 27, no. 1854–1855 , pp. 1–2, 2021.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{kraemer2021monitoring,
title = {Monitoring key epidemiological parameters of SARS-CoV-2 transmission},
author = {Moritz U.G. Kraemer and Oliver G. Pybusand Fraser and Christophe Cauchemez and Simon Rambaut and Andrew Cowling and J. Benjamin},
doi = {https://doi.org/10.1038/s41591-021-01545-w},
year = {2021},
date = {2021-11-08},
urldate = {2021-11-08},
journal = {Nature Medicine},
volume = {27},
number = {1854–1855 },
pages = {1--2},
abstract = {Control of the SARS-CoV-2 pandemic requires targeted interventions, which in turn require precise estimates of quantities that describe transmission. Per-capita transmission rates are influenced by four quantities: (1) the latent period (time from infection to becoming infectious); (2) individual variability in infectiousness (defined by variation in intrinsic transmissibility and contact rate); (3) the incubation period (time from infection to symptom onset); and (4) the serial interval (time between symptom onset of an infector and an infected) (Fig. 1).},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
Control of the SARS-CoV-2 pandemic requires targeted interventions, which in turn require precise estimates of quantities that describe transmission. Per-capita transmission rates are influenced by four quantities: (1) the latent period (time from infection to becoming infectious); (2) individual variability in infectiousness (defined by variation in intrinsic transmissibility and contact rate); (3) the incubation period (time from infection to symptom onset); and (4) the serial interval (time between symptom onset of an infector and an infected) (Fig. 1).