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 are listed all MOOD publications. Use the filter to select the most relevant articles.
5.
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: Brazil, COVID-19, epidemiology, phylogenetic
@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},
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 = {Brazil, COVID-19, epidemiology, phylogenetic},
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.
4.
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, epidemiology, genome, phylogenetic, travel, United Kingdom
@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, epidemiology, genome, phylogenetic, travel, United Kingdom},
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.
3.
Kraemer, MUG; Hill, V; Ruis, C; Dellicour, S; Bajaj, S; McCrone, JT; Baele, G; Parag, KV; Battle, AL; Gutierrez, B; Jackson, B; Colquhoun, R; O'Toole, A; Klein, B; Vespignani, A; Consortium, COVID-19 Genomics UK (COG-UK); Volz, E; Faria, NR; Aanensen, DM; NJ, NJ Loman; du Plessis, L; Cauchemez, S; A, A Rambaut; SV, SV Scarpino; Pybus, OG
Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence Journal Article
In: Science, vol. 373, no. 6557, pp. 889-895, 2021.
Abstract | Links | BibTeX | Tags: big data, COVID-19, genome, mobility, phylogenetic, United Kingdom, variants
@article{doi:10.1126/science.abj0113,
title = {Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence},
author = {MUG Kraemer and V Hill and C Ruis and S Dellicour and S Bajaj and JT McCrone and G Baele and KV Parag and AL Battle and B Gutierrez and B Jackson and R Colquhoun and A O'Toole and B Klein and A Vespignani and COVID-19 Genomics UK (COG-UK) Consortium and E Volz and NR Faria and DM Aanensen and NJ Loman NJ and L du Plessis and S Cauchemez and A Rambaut A and SV Scarpino SV and OG Pybus },
url = {https://www.science.org/doi/abs/10.1126/science.abj0113},
doi = {10.1126/science.abj0113},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Science},
volume = {373},
number = {6557},
pages = {889-895},
abstract = {The B.1.1.7 lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused fast-spreading outbreaks globally. Intrinsically, this variant has greater transmissibility than its predecessors, but this capacity has been amplified in some circumstances to tragic effect by a combination of human behavior and local immunity. What are the extrinsic factors that help or hinder the rapid dissemination of variants? Kraemer et al. explored the invasion dynamics of B.1.1.7. in fine detail, from its location of origin in Kent, UK, to its heterogenous spread around the country. A combination of mobile phone and virus data including more than 17,000 genomes shows how distinct phases of dispersal were related to intensity of mobility and the timing of lockdowns. As the local outbreaks grew, importation from the London source area became less important. Had B.1.1.7. emerged at a slightly different time of year, its impact might have been different. Disentangling the factors that contribute to the rapid spread of virus variants is essential for understanding their epidemiological consequences. Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.},
keywords = {big data, COVID-19, genome, mobility, phylogenetic, United Kingdom, variants},
pubstate = {published},
tppubtype = {article}
}
The B.1.1.7 lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused fast-spreading outbreaks globally. Intrinsically, this variant has greater transmissibility than its predecessors, but this capacity has been amplified in some circumstances to tragic effect by a combination of human behavior and local immunity. What are the extrinsic factors that help or hinder the rapid dissemination of variants? Kraemer et al. explored the invasion dynamics of B.1.1.7. in fine detail, from its location of origin in Kent, UK, to its heterogenous spread around the country. A combination of mobile phone and virus data including more than 17,000 genomes shows how distinct phases of dispersal were related to intensity of mobility and the timing of lockdowns. As the local outbreaks grew, importation from the London source area became less important. Had B.1.1.7. emerged at a slightly different time of year, its impact might have been different. Disentangling the factors that contribute to the rapid spread of virus variants is essential for understanding their epidemiological consequences. Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.
2.
Lemey, Philippe; Hong, Samuel L; Hill, Verity; Baele, Guy; Poletto, Chiara; Colizza, Vittoria; O’Toole, Áine; McCrone, John T.; Andersen, Kristian G.; Worobey, Michael; Nelson, Martha I.; Rambaut, Andrew; Suchard, Marc A.
Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2 Journal Article
In: Nature Communications, vol. 11, no. 5110, 2020.
Abstract | Links | BibTeX | Tags: COVID-19, Ecological epidemiology, phylogenetic
@article{nokey,
title = {Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2},
author = {Philippe Lemey and Samuel L Hong and Verity Hill and Guy Baele and Chiara Poletto and Vittoria Colizza and Áine O’Toole and John T. McCrone and Kristian G. Andersen and Michael Worobey and Martha I. Nelson and Andrew Rambaut and Marc A. Suchard },
doi = {https://doi.org/10.1038/s41467-020-18877-9},
year = {2020},
date = {2020-10-09},
journal = {Nature Communications},
volume = {11},
number = {5110},
abstract = {Spatiotemporal bias in genome sampling can severely confound discrete trait phylogeographic inference. This has impeded our ability to accurately track the spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, despite the availability of unprecedented numbers of SARS-CoV-2 genomes. Here, we present an approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2. We demonstrate that including travel history data yields i) more realistic hypotheses of virus spread and ii) higher posterior predictive accuracy compared to including only sampling location. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts.},
keywords = {COVID-19, Ecological epidemiology, phylogenetic},
pubstate = {published},
tppubtype = {article}
}
Spatiotemporal bias in genome sampling can severely confound discrete trait phylogeographic inference. This has impeded our ability to accurately track the spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, despite the availability of unprecedented numbers of SARS-CoV-2 genomes. Here, we present an approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2. We demonstrate that including travel history data yields i) more realistic hypotheses of virus spread and ii) higher posterior predictive accuracy compared to including only sampling location. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts.
1.
Dellicour, Simon; Lequime, Sebastian; Vrancken, Bram; Gill, Mandev S; Bastide, Paul; Gangavarapu, Karthik; Matteson, Nathaniel L; Tan, Yi; Plessis, Louis Du; Fisher, Alexander A; others,
Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework Journal Article
In: Nature communications, vol. 11, no. 1, pp. 1–11, 2020.
Abstract | Links | BibTeX | Tags: Ecological epidemiology, Molecular ecology, phylogenetic, West Nile Virus
@article{dellicour2020epidemiological,
title = {Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework},
author = {Simon Dellicour and Sebastian Lequime and Bram Vrancken and Mandev S Gill and Paul Bastide and Karthik Gangavarapu and Nathaniel L Matteson and Yi Tan and Louis Du Plessis and Alexander A Fisher and others},
doi = { https://doi.org/10.1038/s41467-020-19122-z},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Nature communications},
volume = {11},
number = {1},
pages = {1--11},
publisher = {Nature Publishing Group},
abstract = {Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.},
keywords = {Ecological epidemiology, Molecular ecology, phylogenetic, West Nile Virus},
pubstate = {published},
tppubtype = {article}
}
Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.