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.
19.
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, epidemiology, France, measures
@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},
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, epidemiology, France, measures},
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
18.
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, epidemiology, transmission
@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, epidemiology, transmission},
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).
17.
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.
16.
Domenico, Laura Di; Sabbatini, Chiara E.; Pullano, Giulia; Lévy-Bruhl, Daniel; Colizza, Vittoria
Impact of lockdown on COVID-19 epidemic in Ile-de-France and possible exit strategies Journal Article
In: medRxiv, no. 2, 2021.
Abstract | Links | BibTeX | Tags: COVID-19, epidemiology, Europe, Public Health
@article{,
title = {Impact of lockdown on COVID-19 epidemic in Ile-de-France and possible exit strategies},
author = {Laura Di Domenico and Chiara E. Sabbatini and Giulia Pullano and Daniel Lévy-Bruhl and Vittoria Colizza},
url = {https://www.medrxiv.org/content/10.1101/2021.02.14.21251708v2},
doi = { 10.2807/1560-7917.ES.2021.26.15.2100272},
year = {2021},
date = {2021-03-10},
urldate = {2021-03-10},
journal = {medRxiv},
number = {2},
publisher = {Cold Spring Harbor Laboratory Press},
abstract = {Facing B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a 2-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalizations to plateau, by decreasing transmission of the historical strain while B.1.1.7 continued to grow. School holidays appear to have further slowed down progression in February. Without progressively strengthened social distancing, a rapid surge of hospitalizations is expected, despite the foreseen increase in vaccination rhythm.},
keywords = {COVID-19, epidemiology, Europe, Public Health},
pubstate = {published},
tppubtype = {article}
}
Facing B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a 2-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalizations to plateau, by decreasing transmission of the historical strain while B.1.1.7 continued to grow. School holidays appear to have further slowed down progression in February. Without progressively strengthened social distancing, a rapid surge of hospitalizations is expected, despite the foreseen increase in vaccination rhythm.
15.
Huang, Bo; Wang, Jionghua; Cai, Jixuan; Yao, Shiqi; Chan, Paul Kay Sheung; Tam, Tony Hong-wing; Hong, Ying-Yi; Ruktanonchai, Corrine W.; Carioli, Alessandra; Floyd, Jessica R.; Ruktanonchai, Nick W.; Yang, Weizhong; Li, Zhongjie; Tatem, Andrew J.; Lai, Shengjie
Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities Journal Article
In: Nature Human Behaviour, vol. 5, pp. 695–705, 2021.
Abstract | Links | BibTeX | Tags: China, COVID-19, epidemiology, vaccine
@article{nokey,
title = {Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities},
author = {Bo Huang and Jionghua Wang and Jixuan Cai and Shiqi Yao and Paul Kay Sheung Chan and Tony Hong-wing Tam and Ying-Yi Hong and Corrine W. Ruktanonchai and Alessandra Carioli and Jessica R. Floyd and Nick W. Ruktanonchai and Weizhong Yang and Zhongjie Li and Andrew J. Tatem and Shengjie Lai },
doi = {https://doi.org/10.1038/s41562-021-01063-2},
year = {2021},
date = {2021-02-18},
journal = {Nature Human Behaviour},
volume = {5},
pages = {695–705},
abstract = {The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city’s population density and social contact patterns.},
keywords = {China, COVID-19, epidemiology, vaccine},
pubstate = {published},
tppubtype = {article}
}
The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city’s population density and social contact patterns.
14.
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.
13.
Ingelbeen, Brecht; Peckeu, Laur`ene; Laga, Marie; Hendrix, Ilona; Neven, Inge; Sande, Marianne AB; Kleef, Esther
Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium, August to November 2020 Journal Article
In: Eurosurveillance, vol. 26, no. 7, pp. 2100065, 2021.
Abstract | Links | BibTeX | Tags: Belgium, COVID-19, epidemiology, Model, school, transmission
@article{ingelbeen2021reducing,
title = {Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium, August to November 2020},
author = {Brecht Ingelbeen and Laur`ene Peckeu and Marie Laga and Ilona Hendrix and Inge Neven and Marianne AB Sande and Esther Kleef},
doi = {https://doi.org/10.1371/journal.pbio.3001115},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Eurosurveillance},
volume = {26},
number = {7},
pages = {2100065},
publisher = {European Centre for Disease Prevention and Control},
abstract = {To evaluate the effect of physical distancing and school reopening in Brussels between August and November 2020, we monitored changes in the number of reported contacts per SARS-CoV-2 case and associated SARS-CoV-2 transmission. The second COVID-19 pandemic wave in Brussels was the result of increased social contact across all ages following school reopening. Physical distancing measures including closure of bars and restaurants, and limiting close contacts, while primary and secondary schools remained open, reduced social mixing and controlled SARS-CoV-2 transmission.},
keywords = {Belgium, COVID-19, epidemiology, Model, school, transmission},
pubstate = {published},
tppubtype = {article}
}
To evaluate the effect of physical distancing and school reopening in Brussels between August and November 2020, we monitored changes in the number of reported contacts per SARS-CoV-2 case and associated SARS-CoV-2 transmission. The second COVID-19 pandemic wave in Brussels was the result of increased social contact across all ages following school reopening. Physical distancing measures including closure of bars and restaurants, and limiting close contacts, while primary and secondary schools remained open, reduced social mixing and controlled SARS-CoV-2 transmission.
12.
Oidtman, Rachel J; Omodei, Elisa; Kraemer, Moritz UG; Casteneda-Orjuela, Carlos A; Cruz-Rivera, Erica; Misnaza-Castrillon, Sandra; Cifuentes, Myriam Patricia; Rincon, Luz Emilse; Canon, Viviana; Alarcon, Pedro; others,
Trade-offs between individual and ensemble forecasts of an emerging infectious disease Journal Article
In: medRxiv, 2021.
Abstract | Links | BibTeX | Tags: epidemiology, infectious diseases, Model, Zika
@article{oidtman2021trade,
title = {Trade-offs between individual and ensemble forecasts of an emerging infectious disease},
author = {Rachel J Oidtman and Elisa Omodei and Moritz UG Kraemer and Carlos A Casteneda-Orjuela and Erica Cruz-Rivera and Sandra Misnaza-Castrillon and Myriam Patricia Cifuentes and Luz Emilse Rincon and Viviana Canon and Pedro Alarcon and others},
doi = {https://doi.org/10.1038/s41467-021-25695-0},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {medRxiv},
publisher = {Cold Spring Harbor Laboratory Press},
abstract = {Probabilistic forecasts play an indispensable role in answering questions about the spread of newly emerged pathogens. However, uncertainties about the epidemiology of emerging pathogens can make it difficult to choose among alternative model structures and assumptions. To assess the potential for uncertainties about emerging pathogens to affect forecasts of their spread, we evaluated the performance 16 forecasting models in the context of the 2015-2016 Zika epidemic in Colombia. Each model featured a different combination of assumptions about human mobility, spatiotemporal variation in transmission potential, and the number of virus introductions. We found that which model assumptions had the most ensemble weight changed through time. We additionally identified a trade-off whereby some individual models outperformed ensemble models early in the epidemic, but on average the ensembles outperformed all individual models. Our results suggest that multiple models spanning uncertainty across alternative assumptions are necessary to obtain robust forecasts for emerging infectious diseases.},
keywords = {epidemiology, infectious diseases, Model, Zika},
pubstate = {published},
tppubtype = {article}
}
Probabilistic forecasts play an indispensable role in answering questions about the spread of newly emerged pathogens. However, uncertainties about the epidemiology of emerging pathogens can make it difficult to choose among alternative model structures and assumptions. To assess the potential for uncertainties about emerging pathogens to affect forecasts of their spread, we evaluated the performance 16 forecasting models in the context of the 2015-2016 Zika epidemic in Colombia. Each model featured a different combination of assumptions about human mobility, spatiotemporal variation in transmission potential, and the number of virus introductions. We found that which model assumptions had the most ensemble weight changed through time. We additionally identified a trade-off whereby some individual models outperformed ensemble models early in the epidemic, but on average the ensembles outperformed all individual models. Our results suggest that multiple models spanning uncertainty across alternative assumptions are necessary to obtain robust forecasts for emerging infectious diseases.
11.
Pullano, Giulia; Domenico, Laura Di; Sabbatini, Chiara E; Valdano, Eugenio; Turbelin, Clément; Debin, Marion; Guerrisi, Caroline; Kengne-Kuetche, Charly; Souty, Cécile; Hanslik, Thomas; others,
Underdetection of cases of COVID-19 in France threatens epidemic control Journal Article
In: Nature, vol. 590, no. 7844, pp. 134–139, 2021.
Abstract | Links | BibTeX | Tags: COVID-19, epidemiology, France, surveillance
@article{pullano2021underdetection,
title = {Underdetection of cases of COVID-19 in France threatens epidemic control},
author = {Giulia Pullano and Laura Di Domenico and Chiara E Sabbatini and Eugenio Valdano and Clément Turbelin and Marion Debin and Caroline Guerrisi and Charly Kengne-Kuetche and Cécile Souty and Thomas Hanslik and others},
doi = { https://doi.org/10.1038/s41586-020-03095-6},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Nature},
volume = {590},
number = {7844},
pages = {134--139},
publisher = {Nature Publishing Group},
abstract = {As countries in Europe gradually relaxed lockdown restrictions after the first wave, test–trace–isolate strategies became critical to maintain the incidence of coronavirus disease 2019 (COVID-19) at low levels1,2. Reviewing their shortcomings can provide elements to consider in light of the second wave that is currently underway in Europe. Here we estimate the rate of detection of symptomatic cases of COVID-19 in France after lockdown through the use of virological3 and participatory syndromic4 surveillance data coupled with mathematical transmission models calibrated to regional hospitalizations2. Our findings indicate that around 90,000 symptomatic infections, corresponding to 9 out 10 cases, were not ascertained by the surveillance system in the first 7 weeks after lockdown from 11 May to 28 June 2020, although the test positivity rate did not exceed the 5% recommendation of the World Health Organization (WHO)5. The median detection rate increased from 7% (95% confidence interval, 6–8%) to 38% (35–44%) over time, with large regional variations, owing to a strengthening of the system as well as a decrease in epidemic activity. According to participatory surveillance data, only 31% of individuals with COVID-19-like symptoms consulted a doctor in the study period. This suggests that large numbers of symptomatic cases of COVID-19 did not seek medical advice despite recommendations, as confirmed by serological studies6,7. Encouraging awareness and same-day healthcare-seeking behaviour of suspected cases of COVID-19 is critical to improve detection. However, the capacity of the system remained insufficient even at the low epidemic activity achieved after lockdown, and was predicted to deteriorate rapidly with increasing incidence of COVID-19 cases. Substantially more aggressive, targeted and efficient testing with easier access is required to act as a tool to control the COVID-19 pandemic. The testing strategy will be critical to enable partial lifting of the current restrictive measures in Europe and to avoid a third wave.},
keywords = {COVID-19, epidemiology, France, surveillance},
pubstate = {published},
tppubtype = {article}
}
As countries in Europe gradually relaxed lockdown restrictions after the first wave, test–trace–isolate strategies became critical to maintain the incidence of coronavirus disease 2019 (COVID-19) at low levels1,2. Reviewing their shortcomings can provide elements to consider in light of the second wave that is currently underway in Europe. Here we estimate the rate of detection of symptomatic cases of COVID-19 in France after lockdown through the use of virological3 and participatory syndromic4 surveillance data coupled with mathematical transmission models calibrated to regional hospitalizations2. Our findings indicate that around 90,000 symptomatic infections, corresponding to 9 out 10 cases, were not ascertained by the surveillance system in the first 7 weeks after lockdown from 11 May to 28 June 2020, although the test positivity rate did not exceed the 5% recommendation of the World Health Organization (WHO)5. The median detection rate increased from 7% (95% confidence interval, 6–8%) to 38% (35–44%) over time, with large regional variations, owing to a strengthening of the system as well as a decrease in epidemic activity. According to participatory surveillance data, only 31% of individuals with COVID-19-like symptoms consulted a doctor in the study period. This suggests that large numbers of symptomatic cases of COVID-19 did not seek medical advice despite recommendations, as confirmed by serological studies6,7. Encouraging awareness and same-day healthcare-seeking behaviour of suspected cases of COVID-19 is critical to improve detection. However, the capacity of the system remained insufficient even at the low epidemic activity achieved after lockdown, and was predicted to deteriorate rapidly with increasing incidence of COVID-19 cases. Substantially more aggressive, targeted and efficient testing with easier access is required to act as a tool to control the COVID-19 pandemic. The testing strategy will be critical to enable partial lifting of the current restrictive measures in Europe and to avoid a third wave.
10.
Lemey, Philippe; Ruktanonchai, Nick; Hong, Samuel L; Colizza, Vittoria; Poletto, Chiara; den Broeck, Frederik Van; Gill, Mandev S; Ji, Xiang; Levasseur, Anthony; Munnink, Bas B Oude; others,
Untangling introductions and persistence in COVID-19 resurgence in Europe Journal Article
In: Nature, vol. 595, no. 7869, pp. 713–717, 2021.
Abstract | Links | BibTeX | Tags: big data, COVID-19, epidemiology, Europe, measures, mobility
@article{lemey2021untangling,
title = {Untangling introductions and persistence in COVID-19 resurgence in Europe},
author = {Philippe Lemey and Nick Ruktanonchai and Samuel L Hong and Vittoria Colizza and Chiara Poletto and Frederik Van den Broeck and Mandev S Gill and Xiang Ji and Anthony Levasseur and Bas B Oude Munnink and others},
doi = {https://doi.org/10.1038/s41586-021-03754-2},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Nature},
volume = {595},
number = {7869},
pages = {713--717},
publisher = {Nature Publishing Group},
abstract = {After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.},
keywords = {big data, COVID-19, epidemiology, Europe, measures, mobility},
pubstate = {published},
tppubtype = {article}
}
After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.
9.
Trentini, Filippo; Marziano, Valentina; Guzzetta, Giorgio; Tirani, Marcello; Cereda, Danilo; Poletti, Piero; Piccarreta, Raffaella; Barone, Antonio; Preziosi, Giuseppe; Arduini, Fabio; Valle, Petra Giulia Della; Zanella, Alberto; Grosso, Francesca; Castillo, Gabriele; Castrofino, Ambra; Grasselli, Giacomo; Melegaro, Alessia; Piatti, Alessandra; Andreassi, Aida; Gramegna, Maria; Ajelli, Marco; Merler, Stefano
In: American Journal of Epidemiology, 2021, ISSN: 0002-9262, (kwab252).
Abstract | Links | BibTeX | Tags: big data, COVID-19, epidemiology, ICU, Italy, Public Health
@article{10.1093/aje/kwab252,
title = {The pressure on healthcare system and intensive care utilization during the COVID-19 outbreak in the Lombardy region: a retrospective observational study on 43,538 hospitalized patients},
author = {Filippo Trentini and Valentina Marziano and Giorgio Guzzetta and Marcello Tirani and Danilo Cereda and Piero Poletti and Raffaella Piccarreta and Antonio Barone and Giuseppe Preziosi and Fabio Arduini and Petra Giulia Della Valle and Alberto Zanella and Francesca Grosso and Gabriele Castillo and Ambra Castrofino and Giacomo Grasselli and Alessia Melegaro and Alessandra Piatti and Aida Andreassi and Maria Gramegna and Marco Ajelli and Stefano Merler},
url = {https://doi.org/10.1093/aje/kwab252},
doi = {10.1093/aje/kwab252},
issn = {0002-9262},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {American Journal of Epidemiology},
abstract = {During the spring of 2020, the COVID-19 epidemic caused an unprecedented demand for intensive care resources in Lombardy, Italy. Using data on 43,538 hospitalized patients admitted between February 21 and July 12, 2020, we evaluated variations in intensive care unit (ICU) admissions and mortality over three periods: the early phase (February 20-March 13), the period of highest pressure on healthcare (March 14-April 25, when COVID-19 patients exceeded the ICU pre-pandemic bed capacity), and the declining phase (April 26-July 12).Compared to the early phase, patients above 70 years of age were admitted less often to an ICU during highest pressure on healthcare (odds ratio OR 0.47, 95%CI: 0.41-0.54) with longer delays (incidence rate ratio IRR 1.82, 95%CI: 1.52-2.18), and lower chances of death in ICU (OR 0.47, 95%CI: 0.34-0.64). Patients under 56 years of age reported more limited changes in the probability (OR 0.65, 95%CI: 0.56-0.76) and delay to ICU admission (IRR 1.16, 95%CI: 0.95-1.42) and an increased mortality (OR 1.43, 95%CI: 1.00-2.07). In the declining phase, all quantities decreased for all age groups.These patterns may suggest that limited healthcare resources during the peak epidemic phase in Lombardy forced a shift in ICU admission criteria to prioritize patients with higher chances of survival.},
note = {kwab252},
keywords = {big data, COVID-19, epidemiology, ICU, Italy, Public Health},
pubstate = {published},
tppubtype = {article}
}
During the spring of 2020, the COVID-19 epidemic caused an unprecedented demand for intensive care resources in Lombardy, Italy. Using data on 43,538 hospitalized patients admitted between February 21 and July 12, 2020, we evaluated variations in intensive care unit (ICU) admissions and mortality over three periods: the early phase (February 20-March 13), the period of highest pressure on healthcare (March 14-April 25, when COVID-19 patients exceeded the ICU pre-pandemic bed capacity), and the declining phase (April 26-July 12).Compared to the early phase, patients above 70 years of age were admitted less often to an ICU during highest pressure on healthcare (odds ratio OR 0.47, 95%CI: 0.41-0.54) with longer delays (incidence rate ratio IRR 1.82, 95%CI: 1.52-2.18), and lower chances of death in ICU (OR 0.47, 95%CI: 0.34-0.64). Patients under 56 years of age reported more limited changes in the probability (OR 0.65, 95%CI: 0.56-0.76) and delay to ICU admission (IRR 1.16, 95%CI: 0.95-1.42) and an increased mortality (OR 1.43, 95%CI: 1.00-2.07). In the declining phase, all quantities decreased for all age groups.These patterns may suggest that limited healthcare resources during the peak epidemic phase in Lombardy forced a shift in ICU admission criteria to prioritize patients with higher chances of survival.
8.
Rader, Benjamin; Scarpino, Samuel V; Nande, Anjalika; Hill, Alison L; Adlam, Ben; Reiner, Robert C; Pigott, David M; Gutierrez, Bernardo; Zarebski, Alexander E; Shrestha, Munik; others,
Crowding and the shape of COVID-19 epidemics Journal Article
In: Nature medicine, vol. 26, no. 12, pp. 1829–1834, 2020.
Abstract | Links | BibTeX | Tags: COVID-19, epidemiology, population dynamics
@article{rader2020crowding,
title = {Crowding and the shape of COVID-19 epidemics},
author = {Benjamin Rader and Samuel V Scarpino and Anjalika Nande and Alison L Hill and Ben Adlam and Robert C Reiner and David M Pigott and Bernardo Gutierrez and Alexander E Zarebski and Munik Shrestha and others},
doi = {https://doi.org/10.1038/s41591-020-1104-0},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Nature medicine},
volume = {26},
number = {12},
pages = {1829--1834},
publisher = {Nature Publishing Group},
abstract = {The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.},
keywords = {COVID-19, epidemiology, population dynamics},
pubstate = {published},
tppubtype = {article}
}
The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.
7.
Lai, Shengjie; Ruktanonchai, Nick W; Zhou, Liangcai; Prosper, Olivia; Luo, Wei; Floyd, Jessica R; Wesolowski, Amy; Santillana, Mauricio; Zhang, Chi; Du, Xiangjun; others,
Effect of non-pharmaceutical interventions to contain COVID-19 in China Journal Article
In: nature, vol. 585, no. 7825, pp. 410–413, 2020.
Abstract | Links | BibTeX | Tags: COVID-19, epidemiology, health policy, Model
@article{lai2020effect,
title = {Effect of non-pharmaceutical interventions to contain COVID-19 in China},
author = {Shengjie Lai and Nick W Ruktanonchai and Liangcai Zhou and Olivia Prosper and Wei Luo and Jessica R Floyd and Amy Wesolowski and Mauricio Santillana and Chi Zhang and Xiangjun Du and others},
doi = {https://doi.org/10.1038/s41586-020-2293-x},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {nature},
volume = {585},
number = {7825},
pages = {410--413},
publisher = {Nature Publishing Group},
abstract = {On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings3. Here, using epidemiological data on COVID-19 and anonymized data on human movement, we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimate that there were a total of 114,325 cases of COVID-19 (interquartile range 76,776–164,576) in mainland China as of 29 February 2020. Without non-pharmaceutical interventions, we predict that the number of cases would have been 67-fold higher (interquartile range 44–94-fold) by 29 February 2020, and we find that the effectiveness of different interventions varied. We estimate that early detection and isolation of cases prevented more infections than did travel restrictions and contact reductions, but that a combination of non-pharmaceutical interventions achieved the strongest and most rapid effect. According to our model, the lifting of travel restrictions from 17 February 2020 does not lead to an increase in cases across China if social distancing interventions can be maintained, even at a limited level of an on average 25% reduction in contact between individuals that continues until late April. These findings improve our understanding of the effects of non-pharmaceutical interventions on COVID-19, and will inform response efforts across the world.},
keywords = {COVID-19, epidemiology, health policy, Model},
pubstate = {published},
tppubtype = {article}
}
On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings3. Here, using epidemiological data on COVID-19 and anonymized data on human movement, we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimate that there were a total of 114,325 cases of COVID-19 (interquartile range 76,776–164,576) in mainland China as of 29 February 2020. Without non-pharmaceutical interventions, we predict that the number of cases would have been 67-fold higher (interquartile range 44–94-fold) by 29 February 2020, and we find that the effectiveness of different interventions varied. We estimate that early detection and isolation of cases prevented more infections than did travel restrictions and contact reductions, but that a combination of non-pharmaceutical interventions achieved the strongest and most rapid effect. According to our model, the lifting of travel restrictions from 17 February 2020 does not lead to an increase in cases across China if social distancing interventions can be maintained, even at a limited level of an on average 25% reduction in contact between individuals that continues until late April. These findings improve our understanding of the effects of non-pharmaceutical interventions on COVID-19, and will inform response efforts across the world.
6.
Pullano, Giulia; Valdano, Eugenio; Scarpa, Nicola; Rubrichi, Stefania; Colizza, Vittoria
In: The Lancet Digital Health, vol. 2, no. 12, pp. e638–e649, 2020.
Abstract | Links | BibTeX | Tags: big data, contac tracing, COVID-19, epidemiology, France, measures, mobility, transmission
@article{pullano2020evaluating,
title = {Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: a population-based study},
author = {Giulia Pullano and Eugenio Valdano and Nicola Scarpa and Stefania Rubrichi and Vittoria Colizza},
doi = {10.1016/S2589-7500(20)30243-0 },
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {The Lancet Digital Health},
volume = {2},
number = {12},
pages = {e638--e649},
publisher = {Elsevier},
abstract = {Background: On March 17, 2020, French authorities implemented a nationwide lockdown to respond to the COVID-19 epidemic and curb the surge of patients requiring critical care. Assessing the effect of lockdown on individual displacements is essential to quantify achievable mobility reductions and identify the factors driving the changes in social dynamics that affected viral diffusion. We aimed to use mobile phone data to study how mobility in France changed before and during the lockdown, breaking down our findings by trip distance, user age and residency, and time of day, and analysing regional data and spatial heterogeneities. For this population-based study, we used temporally resolved travel flows among 1436 administrative areas of mainland France reconstructed from mobile phone trajectories. Data were stratified by age class (younger than 18 years, 18-64 years, and 65 years or older). We distinguished between residents and non-residents and used population data and regional socio-economic indicators from the French National Statistical Institute. We measured mobility changes before and during lockdown at both local and country scales using a case-crossover framework. We analysed all trips combined and trips longer than 100 km (termed long trips), and separated trips by daytime or night-time, weekdays or weekends, and rush hours.
Findings: Lockdown caused a 65% reduction in the countrywide number of displacements (from about 57 million to about 20 million trips per day) and was particularly effective in reducing work-related short-range mobility, especially during rush hour, and long trips. Geographical heterogeneities showed anomalous increases in long-range movements even before lockdown announcement that were tightly localised in space. During lockdown, mobility drops were unevenly distributed across regions (eg, Île-de-France, the region of Paris, went from 585 000 to 117 000 outgoing trips per day). They were strongly associated with active populations, workers employed in sectors highly affected by lockdown, and number of hospitalisations per region, and moderately associated with the socioeconomic level of the regions. Major cities largely shrank their pattern of connectivity, reducing it mainly to short-range commuting (95% of traffic leaving Paris was contained in a 201 km radius before lockdown, which was reduced to 29 km during lockdown).},
keywords = {big data, contac tracing, COVID-19, epidemiology, France, measures, mobility, transmission},
pubstate = {published},
tppubtype = {article}
}
Background: On March 17, 2020, French authorities implemented a nationwide lockdown to respond to the COVID-19 epidemic and curb the surge of patients requiring critical care. Assessing the effect of lockdown on individual displacements is essential to quantify achievable mobility reductions and identify the factors driving the changes in social dynamics that affected viral diffusion. We aimed to use mobile phone data to study how mobility in France changed before and during the lockdown, breaking down our findings by trip distance, user age and residency, and time of day, and analysing regional data and spatial heterogeneities. For this population-based study, we used temporally resolved travel flows among 1436 administrative areas of mainland France reconstructed from mobile phone trajectories. Data were stratified by age class (younger than 18 years, 18-64 years, and 65 years or older). We distinguished between residents and non-residents and used population data and regional socio-economic indicators from the French National Statistical Institute. We measured mobility changes before and during lockdown at both local and country scales using a case-crossover framework. We analysed all trips combined and trips longer than 100 km (termed long trips), and separated trips by daytime or night-time, weekdays or weekends, and rush hours.
Findings: Lockdown caused a 65% reduction in the countrywide number of displacements (from about 57 million to about 20 million trips per day) and was particularly effective in reducing work-related short-range mobility, especially during rush hour, and long trips. Geographical heterogeneities showed anomalous increases in long-range movements even before lockdown announcement that were tightly localised in space. During lockdown, mobility drops were unevenly distributed across regions (eg, Île-de-France, the region of Paris, went from 585 000 to 117 000 outgoing trips per day). They were strongly associated with active populations, workers employed in sectors highly affected by lockdown, and number of hospitalisations per region, and moderately associated with the socioeconomic level of the regions. Major cities largely shrank their pattern of connectivity, reducing it mainly to short-range commuting (95% of traffic leaving Paris was contained in a 201 km radius before lockdown, which was reduced to 29 km during lockdown).
Findings: Lockdown caused a 65% reduction in the countrywide number of displacements (from about 57 million to about 20 million trips per day) and was particularly effective in reducing work-related short-range mobility, especially during rush hour, and long trips. Geographical heterogeneities showed anomalous increases in long-range movements even before lockdown announcement that were tightly localised in space. During lockdown, mobility drops were unevenly distributed across regions (eg, Île-de-France, the region of Paris, went from 585 000 to 117 000 outgoing trips per day). They were strongly associated with active populations, workers employed in sectors highly affected by lockdown, and number of hospitalisations per region, and moderately associated with the socioeconomic level of the regions. Major cities largely shrank their pattern of connectivity, reducing it mainly to short-range commuting (95% of traffic leaving Paris was contained in a 201 km radius before lockdown, which was reduced to 29 km during lockdown).
5.
Candido, Darlan S; Claro, Ingra M; Jesus, Jaqueline G De; Souza, William M; Moreira, Filipe RR; Dellicour, Simon; Mellan, Thomas A; Plessis, Louis Du; Pereira, Rafael HM; Sales, Flavia CS; others,
Evolution and epidemic spread of SARS-CoV-2 in Brazil Journal Article
In: Science, vol. 369, no. 6508, pp. 1255–1260, 2020.
Abstract | Links | BibTeX | Tags: big data, Brazil, Contact tracing, COVID-19, epidemiology, measures, mobility, transmission
@article{candido2020evolution,
title = {Evolution and epidemic spread of SARS-CoV-2 in Brazil},
author = {Darlan S Candido and Ingra M Claro and Jaqueline G De Jesus and William M Souza and Filipe RR Moreira and Simon Dellicour and Thomas A Mellan and Louis Du Plessis and Rafael HM Pereira and Flavia CS Sales and others},
doi = {10.1126/science.abd2161},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Science},
volume = {369},
number = {6508},
pages = {1255--1260},
publisher = {American Association for the Advancement of Science},
abstract = {Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February and 11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.},
keywords = {big data, Brazil, Contact tracing, COVID-19, epidemiology, measures, mobility, transmission},
pubstate = {published},
tppubtype = {article}
}
Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February and 11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.
4.
Zhang, Juanjuan; Litvinova, Maria; Wang, Wei; Wang, Yan; Deng, Xiaowei; Chen, Xinghui; Li, Mei; Zheng, Wen; Yi, Lan; Chen, Xinhua; others,
Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study Journal Article
In: The Lancet Infectious Diseases, vol. 20, no. 7, pp. 793–802, 2020.
Abstract | Links | BibTeX | Tags: China, COVID-19, epidemiology, transmission
@article{zhang2020evolving,
title = {Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study},
author = {Juanjuan Zhang and Maria Litvinova and Wei Wang and Yan Wang and Xiaowei Deng and Xinghui Chen and Mei Li and Wen Zheng and Lan Yi and Xinhua Chen and others},
doi = {https://doi.org/10.1016/S1473-3099(20)30230-9},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {The Lancet Infectious Diseases},
volume = {20},
number = {7},
pages = {793--802},
publisher = {Elsevier},
abstract = {The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.
Methods
We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.
Findings
We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30.
},
keywords = {China, COVID-19, epidemiology, transmission},
pubstate = {published},
tppubtype = {article}
}
The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.
Methods
We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.
Findings
We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30.
Methods
We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.
Findings
We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30.
3.
Zhao, Cheng; Tepekule, Burcu; Criscuolo, Nicola G.; Garcia, Pedro David Wendel; Hilty, Matthias Peter; Switzerland, Risc-Icu Consortium Investigators In; Fumeaux, Thierry; Boeckel, Thomas P. Van
icumonitoring.ch: a platform for short-term forecasting of intensive care unit occupancy during the COVID-19 epidemic in Switzerland. Journal Article
In: Swiss medical weekly, vol. 150, pp. w20277, 2020.
Links | BibTeX | Tags: COVID-19, epidemiology, ICU, Model, platform, Switzerland
@article{Zhao2020icumonitoringchAP,
title = {icumonitoring.ch: a platform for short-term forecasting of intensive care unit occupancy during the COVID-19 epidemic in Switzerland.},
author = {Cheng Zhao and Burcu Tepekule and Nicola G. Criscuolo and Pedro David Wendel Garcia and Matthias Peter Hilty and Risc-Icu Consortium Investigators In Switzerland and Thierry Fumeaux and Thomas P. Van Boeckel},
doi = {10.4414/smw.2020.20277},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Swiss medical weekly},
volume = {150},
pages = {w20277},
keywords = {COVID-19, epidemiology, ICU, Model, platform, Switzerland},
pubstate = {published},
tppubtype = {article}
}
2.
Guzzetta, Giorgio; Riccardo, Flavia; Marziano, Valentina; Poletti, Piero; Trentini, Filippo; Bella, Antonino; Andrianou, Xanthi; Manso, Martina Del; Fabiani, Massimo; Bellino, Stefania; others,
The impact of a nation-wide lockdown on COVID-19 transmissibility in Italy Journal Article
In: arXiv preprint arXiv:2004.12338, 2020.
Abstract | Links | BibTeX | Tags: COVID-19, epidemiology, Italy, lock-down, reproduction number, transmission, zoonoses
@article{guzzetta2020impact,
title = {The impact of a nation-wide lockdown on COVID-19 transmissibility in Italy},
author = {Giorgio Guzzetta and Flavia Riccardo and Valentina Marziano and Piero Poletti and Filippo Trentini and Antonino Bella and Xanthi Andrianou and Martina Del Manso and Massimo Fabiani and Stefania Bellino and others},
doi = {10.3201/eid2701.202114},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {arXiv preprint arXiv:2004.12338},
abstract = {On March 11, 2020, Italy imposed a national lockdown to curtail the spread of severe acute respiratory syndrome coronavirus 2. We estimate that, 14 days after lockdown, the net reproduction number had dropped below 1 and remained stable at »0.76 (95% CI 0.67-0.85) in all regions for >3 of the following weeks.},
keywords = {COVID-19, epidemiology, Italy, lock-down, reproduction number, transmission, zoonoses},
pubstate = {published},
tppubtype = {article}
}
On March 11, 2020, Italy imposed a national lockdown to curtail the spread of severe acute respiratory syndrome coronavirus 2. We estimate that, 14 days after lockdown, the net reproduction number had dropped below 1 and remained stable at »0.76 (95% CI 0.67-0.85) in all regions for >3 of the following weeks.
1.
Pinotti, Francesco; Domenico, Laura Di; Ortega, Ernesto; Mancastroppa, Marco; Pullano, Giulia; Valdano, Eugenio; Boëlle, Pierre-Yves; Poletto, Chiara; Colizza, Vittoria
Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study Journal Article
In: PLOS Medicine, vol. 17, no. 7, pp. 1-13, 2020.
Abstract | Links | BibTeX | Tags: COVID-19, epidemiology, reverse transcription-polymerase chain reaction, RT-PCR, STROBE
@article{10.1371/journal.pmed.1003193,
title = {Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study},
author = {Francesco Pinotti and Laura Di Domenico and Ernesto Ortega and Marco Mancastroppa and Giulia Pullano and Eugenio Valdano and Pierre-Yves Boëlle and Chiara Poletto and Vittoria Colizza},
url = {https://doi.org/10.1371/journal.pmed.1003193},
doi = {10.1371/journal.pmed.1003193},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {PLOS Medicine},
volume = {17},
number = {7},
pages = {1-13},
publisher = {Public Library of Science},
abstract = {Background In the early months of 2020, a novel coronavirus disease (COVID-19) spread rapidly from China across multiple countries worldwide. As of March 17, 2020, COVID-19 was officially declared a pandemic by the World Health Organization. We collected data on COVID-19 cases outside China during the early phase of the pandemic and used them to predict trends in importations and quantify the proportion of undetected imported cases. Methods and findings Two hundred and eighty-eight cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized the importation timeline to assess the rapidity of isolation and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, corresponding to a doubling time of 2.8 days, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the successive weeks. Time from travel to detection has considerably decreased since first importation, from 14.5 ± 5.5 days on January 5, 2020, to 6 ± 3.5 days on February 1, 2020. However, we estimated 36% of detection of imported cases. This study is restricted to the early phase of the pandemic, when China was the only large epicenter and foreign countries had not discovered extensive local transmission yet. Missing information in case history was accounted for through modeling and imputation. Conclusions Our findings indicate that travel bans and containment strategies adopted in China were effective in reducing the exportation growth rate. However, the risk of importation was estimated to increase again from other sources in South East Asia. Surveillance and management of traveling cases represented a priority in the early phase of the epidemic. With the majority of imported cases going undetected (6 out of 10), countries experienced several undetected clusters of chains of local transmissions, fueling silent epidemics in the community. These findings become again critical to prevent second waves, now that countries have reduced their epidemic activity and progressively phase out lockdown.},
keywords = {COVID-19, epidemiology, reverse transcription-polymerase chain reaction, RT-PCR, STROBE},
pubstate = {published},
tppubtype = {article}
}
Background In the early months of 2020, a novel coronavirus disease (COVID-19) spread rapidly from China across multiple countries worldwide. As of March 17, 2020, COVID-19 was officially declared a pandemic by the World Health Organization. We collected data on COVID-19 cases outside China during the early phase of the pandemic and used them to predict trends in importations and quantify the proportion of undetected imported cases. Methods and findings Two hundred and eighty-eight cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized the importation timeline to assess the rapidity of isolation and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, corresponding to a doubling time of 2.8 days, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the successive weeks. Time from travel to detection has considerably decreased since first importation, from 14.5 ± 5.5 days on January 5, 2020, to 6 ± 3.5 days on February 1, 2020. However, we estimated 36% of detection of imported cases. This study is restricted to the early phase of the pandemic, when China was the only large epicenter and foreign countries had not discovered extensive local transmission yet. Missing information in case history was accounted for through modeling and imputation. Conclusions Our findings indicate that travel bans and containment strategies adopted in China were effective in reducing the exportation growth rate. However, the risk of importation was estimated to increase again from other sources in South East Asia. Surveillance and management of traveling cases represented a priority in the early phase of the epidemic. With the majority of imported cases going undetected (6 out of 10), countries experienced several undetected clusters of chains of local transmissions, fueling silent epidemics in the community. These findings become again critical to prevent second waves, now that countries have reduced their epidemic activity and progressively phase out lockdown.