MOOD project is at the forefront of European research of infectious disease surveillance and modelling from a data science perspective, investigating the impact of global warming on disease outbreaks, and proposing innovations for building of One Health systems across Europe and the world.
In the table below all publications to which the MOOD project contributed are listed. Use the filter to select the most relevant articles.
88.
Faucher, Benjamin; Sabbatini, Chiara E.; Czuppon, Peter; Kraemer, Moritz U. G.; Lemey, Philippe; Colizza, Vittoria; Blanquart, François; Boëlle, Pierre-Yves; Poletto, Chiara
Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha Journal Article
In: Nature Communications, vol. 15, no. 2152, 2024.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha},
author = {Benjamin Faucher and Chiara E. Sabbatini and Peter Czuppon and Moritz U. G. Kraemer and Philippe Lemey and Vittoria Colizza and François Blanquart and Pierre-Yves Boëlle and Chiara Poletto},
url = {https://www.nature.com/articles/s41467-024-46345-1},
doi = {10.1038/s41467-024-46345-1},
year = {2024},
date = {2024-03-09},
journal = {Nature Communications},
volume = {15},
number = {2152},
abstract = {SARS-CoV-2 variants of concern (VOCs) circulated cryptically before being identified as a threat, delaying interventions. Here we studied the drivers of such silent spread and its epidemic impact to inform future response planning. We focused on Alpha spread out of the UK. We integrated spatio-temporal records of international mobility, local epidemic growth and genomic surveillance into a Bayesian framework to reconstruct the first three months after Alpha emergence. We found that silent circulation lasted from days to months and decreased with the logarithm of sequencing coverage. Social restrictions in some countries likely delayed the establishment of local transmission, mitigating the negative consequences of late detection. Revisiting the initial spread of Alpha supports local mitigation at the destination in case of emerging events.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
SARS-CoV-2 variants of concern (VOCs) circulated cryptically before being identified as a threat, delaying interventions. Here we studied the drivers of such silent spread and its epidemic impact to inform future response planning. We focused on Alpha spread out of the UK. We integrated spatio-temporal records of international mobility, local epidemic growth and genomic surveillance into a Bayesian framework to reconstruct the first three months after Alpha emergence. We found that silent circulation lasted from days to months and decreased with the logarithm of sequencing coverage. Social restrictions in some countries likely delayed the establishment of local transmission, mitigating the negative consequences of late detection. Revisiting the initial spread of Alpha supports local mitigation at the destination in case of emerging events.
87.
Sabbatini, Chiara E.; Pullano, Giulia; Domenico, Laura Di; Rubrichi, Stefania; & Vittoria Colizza, Shweta Bansal
The impact of spatial connectivity on NPIs effectiveness Journal Article
In: BMC Infectious Diseases, no. 21, 2024.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {The impact of spatial connectivity on NPIs effectiveness},
author = {Chiara E. Sabbatini and Giulia Pullano and Laura Di Domenico and Stefania Rubrichi and Shweta Bansal & Vittoria Colizza},
url = {https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-023-08900-x},
doi = {10.1186/s12879-023-08900-x},
year = {2024},
date = {2024-01-02},
urldate = {2024-01-02},
journal = {BMC Infectious Diseases},
number = {21},
abstract = {Background
France implemented a combination of non-pharmaceutical interventions (NPIs) to manage the COVID-19 pandemic between September 2020 and June 2021. These included a lockdown in the fall 2020 – the second since the start of the pandemic – to counteract the second wave, followed by a long period of nighttime curfew, and by a third lockdown in the spring 2021 against the Alpha wave. Interventions have so far been evaluated in isolation, neglecting the spatial connectivity between regions through mobility that may impact NPI effectiveness.
Methods
Focusing on September 2020–June 2021, we developed a regionally-based epidemic metapopulation model informed by observed mobility fluxes from daily mobile phone data and fitted the model to regional hospital admissions. The model integrated data on vaccination and variants spread. Scenarios were designed to assess the impact of the Alpha variant, characterized by increased transmissibility and risk of hospitalization, of the vaccination campaign and alternative policy decisions.
Results
The spatial model better captured the heterogeneity observed in the regional dynamics, compared to models neglecting inter-regional mobility. The third lockdown was similarly effective to the second lockdown after discounting for immunity, Alpha, and seasonality (51% vs 52% median regional reduction in the reproductive number R0, respectively). The 6pm nighttime curfew with bars and restaurants closed, implemented in January 2021, substantially reduced COVID-19 transmission. It initially led to 49% median regional reduction of R0, decreasing to 43% reduction by March 2021. In absence of vaccination, implemented interventions would have been insufficient against the Alpha wave. Counterfactual scenarios proposing a sequence of lockdowns in a stop-and-go fashion would have reduced hospitalizations and restriction days for low enough thresholds triggering and lifting restrictions.
Conclusions
Spatial connectivity induced by mobility impacted the effectiveness of interventions especially in regions with higher mobility rates. Early evening curfew with gastronomy sector closed allowed authorities to delay the third wave. Stop-and-go lockdowns could have substantially lowered both healthcare and societal burdens if implemented early enough, compared to the observed application of lockdown-curfew-lockdown, but likely at the expense of several labor sectors. These findings contribute to characterize the effectiveness of implemented strategies and improve pandemic preparedness.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
Background
France implemented a combination of non-pharmaceutical interventions (NPIs) to manage the COVID-19 pandemic between September 2020 and June 2021. These included a lockdown in the fall 2020 – the second since the start of the pandemic – to counteract the second wave, followed by a long period of nighttime curfew, and by a third lockdown in the spring 2021 against the Alpha wave. Interventions have so far been evaluated in isolation, neglecting the spatial connectivity between regions through mobility that may impact NPI effectiveness.
Methods
Focusing on September 2020–June 2021, we developed a regionally-based epidemic metapopulation model informed by observed mobility fluxes from daily mobile phone data and fitted the model to regional hospital admissions. The model integrated data on vaccination and variants spread. Scenarios were designed to assess the impact of the Alpha variant, characterized by increased transmissibility and risk of hospitalization, of the vaccination campaign and alternative policy decisions.
Results
The spatial model better captured the heterogeneity observed in the regional dynamics, compared to models neglecting inter-regional mobility. The third lockdown was similarly effective to the second lockdown after discounting for immunity, Alpha, and seasonality (51% vs 52% median regional reduction in the reproductive number R0, respectively). The 6pm nighttime curfew with bars and restaurants closed, implemented in January 2021, substantially reduced COVID-19 transmission. It initially led to 49% median regional reduction of R0, decreasing to 43% reduction by March 2021. In absence of vaccination, implemented interventions would have been insufficient against the Alpha wave. Counterfactual scenarios proposing a sequence of lockdowns in a stop-and-go fashion would have reduced hospitalizations and restriction days for low enough thresholds triggering and lifting restrictions.
Conclusions
Spatial connectivity induced by mobility impacted the effectiveness of interventions especially in regions with higher mobility rates. Early evening curfew with gastronomy sector closed allowed authorities to delay the third wave. Stop-and-go lockdowns could have substantially lowered both healthcare and societal burdens if implemented early enough, compared to the observed application of lockdown-curfew-lockdown, but likely at the expense of several labor sectors. These findings contribute to characterize the effectiveness of implemented strategies and improve pandemic preparedness.
France implemented a combination of non-pharmaceutical interventions (NPIs) to manage the COVID-19 pandemic between September 2020 and June 2021. These included a lockdown in the fall 2020 – the second since the start of the pandemic – to counteract the second wave, followed by a long period of nighttime curfew, and by a third lockdown in the spring 2021 against the Alpha wave. Interventions have so far been evaluated in isolation, neglecting the spatial connectivity between regions through mobility that may impact NPI effectiveness.
Methods
Focusing on September 2020–June 2021, we developed a regionally-based epidemic metapopulation model informed by observed mobility fluxes from daily mobile phone data and fitted the model to regional hospital admissions. The model integrated data on vaccination and variants spread. Scenarios were designed to assess the impact of the Alpha variant, characterized by increased transmissibility and risk of hospitalization, of the vaccination campaign and alternative policy decisions.
Results
The spatial model better captured the heterogeneity observed in the regional dynamics, compared to models neglecting inter-regional mobility. The third lockdown was similarly effective to the second lockdown after discounting for immunity, Alpha, and seasonality (51% vs 52% median regional reduction in the reproductive number R0, respectively). The 6pm nighttime curfew with bars and restaurants closed, implemented in January 2021, substantially reduced COVID-19 transmission. It initially led to 49% median regional reduction of R0, decreasing to 43% reduction by March 2021. In absence of vaccination, implemented interventions would have been insufficient against the Alpha wave. Counterfactual scenarios proposing a sequence of lockdowns in a stop-and-go fashion would have reduced hospitalizations and restriction days for low enough thresholds triggering and lifting restrictions.
Conclusions
Spatial connectivity induced by mobility impacted the effectiveness of interventions especially in regions with higher mobility rates. Early evening curfew with gastronomy sector closed allowed authorities to delay the third wave. Stop-and-go lockdowns could have substantially lowered both healthcare and societal burdens if implemented early enough, compared to the observed application of lockdown-curfew-lockdown, but likely at the expense of several labor sectors. These findings contribute to characterize the effectiveness of implemented strategies and improve pandemic preparedness.
86.
Inward, Rhys P. D.; Jackson, Felix; Dasgupta, Abhishek; Lee, Graham; Battle, Anya Lindström; Parag, Kris V.; Kraemer, Moritz U. G.
Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates Journal Article
In: Epidemics, vol. 41, pp. 100627, 2023, ISSN: 1755-4365.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates},
author = {Rhys P.D. Inward and Felix Jackson and Abhishek Dasgupta and Graham Lee and Anya Lindström Battle and Kris V. Parag and Moritz U.G. Kraemer},
url = {https://www.sciencedirect.com/science/article/pii/S1755436522000676},
doi = {10.1016/j.epidem.2022.100627},
issn = {1755-4365},
year = {2023},
date = {2023-12-01},
urldate = {2023-12-01},
journal = {Epidemics},
volume = {41},
pages = {100627},
abstract = {SARS-CoV-2 case data are primary sources for estimating epidemiological parameters and for modelling the dynamics of outbreaks. Understanding biases within case-based data sources used in epidemiological analyses is important as they can detract from the value of these rich datasets. This raises questions of how variations in surveillance can affect the estimation of epidemiological parameters such as the case growth rates. We use standardised line list data of COVID-19 from Argentina, Brazil, Mexico and Colombia to estimate delay distributions of symptom-onset-to-confirmation, -hospitalisation and -death as well as hospitalisation-to-death at high spatial resolutions and throughout time. Using these estimates, we model the biases introduced by the delay from symptom-onset-to-confirmation on national and state level case growth rates (rt) using an adaptation of the Richardson-Lucy deconvolution algorithm. We find significant heterogeneities in the estimation of delay distributions through time and space with delay difference of up to 19 days between epochs at the state level. Further, we find that by changing the spatial scale, estimates of case growth rate can vary by up to 0.13 d−1. Lastly, we find that states with a high variance and/or mean delay in symptom-onset-to-diagnosis also have the largest difference between the rt estimated from raw and deconvolved case counts at the state level. We highlight the importance of high-resolution case-based data in understanding biases in disease reporting and how these biases can be avoided by adjusting case numbers based on empirical delay distributions. Code and openly accessible data to reproduce analyses presented here are available.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
SARS-CoV-2 case data are primary sources for estimating epidemiological parameters and for modelling the dynamics of outbreaks. Understanding biases within case-based data sources used in epidemiological analyses is important as they can detract from the value of these rich datasets. This raises questions of how variations in surveillance can affect the estimation of epidemiological parameters such as the case growth rates. We use standardised line list data of COVID-19 from Argentina, Brazil, Mexico and Colombia to estimate delay distributions of symptom-onset-to-confirmation, -hospitalisation and -death as well as hospitalisation-to-death at high spatial resolutions and throughout time. Using these estimates, we model the biases introduced by the delay from symptom-onset-to-confirmation on national and state level case growth rates (rt) using an adaptation of the Richardson-Lucy deconvolution algorithm. We find significant heterogeneities in the estimation of delay distributions through time and space with delay difference of up to 19 days between epochs at the state level. Further, we find that by changing the spatial scale, estimates of case growth rate can vary by up to 0.13 d−1. Lastly, we find that states with a high variance and/or mean delay in symptom-onset-to-diagnosis also have the largest difference between the rt estimated from raw and deconvolved case counts at the state level. We highlight the importance of high-resolution case-based data in understanding biases in disease reporting and how these biases can be avoided by adjusting case numbers based on empirical delay distributions. Code and openly accessible data to reproduce analyses presented here are available.
85.
Jore, Solveig; Viljugrein, Hildegunn; Hjertqvist, Marika; Dub, Timothée; Mäkelä, Henna
Outdoor recreation, tick borne encephalitis incidence and seasonality in Finland, Norway and Sweden during the COVID-19 pandemic (2020/2021) Journal Article
In: Infection Ecology & Epidemiology, vol. 13, no. 1, pp. 2281055, 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), TBE (Tick Borne Encephalitis)
@article{nokey,
title = {Outdoor recreation, tick borne encephalitis incidence and seasonality in Finland, Norway and Sweden during the COVID-19 pandemic (2020/2021)},
author = {Solveig Jore and Hildegunn Viljugrein and Marika Hjertqvist and Timothée Dub and Henna Mäkelä},
url = {https://doi.org/10.1080/20008686.2023.2281055},
doi = {10.1080/20008686.2023.2281055},
year = {2023},
date = {2023-11-18},
urldate = {2023-11-18},
journal = {Infection Ecology & Epidemiology},
volume = {13},
number = {1},
pages = {2281055},
abstract = {During the pandemic outdoor activities were encouraged to mitigate transmission risk while providing safe spaces for social interactions. Human behaviour, which may favour or disfavour, contact rates between questing ticks and humans, is a key factor impacting tick-borne encephalitis (TBE) incidence. We analyzed annual and weekly TBE cases in Finland, Norway and Sweden from 2010 to 2021 to assess trend, seasonality, and discuss changes in human tick exposure imposed by COVID-19. We compared the pre-pandemic incidence (2010–2019) with the pandemic incidence (2020–2021) by fitting a generalized linear model (GLM) to incidence data. Pre-pandemic incidence was 1.0, 0.29 and 2.8 for Finland, Norway and Sweden, respectively, compared to incidence of 2.2, 1.0 and 3.9 during the pandemic years. However, there was an increasing trend for all countries across the whole study period. Therefore, we predicted the number of cases in 2020/2021 based on a model fitted to the annual cases in 2010–2019. The incidences during the pandemic were 1.3 times higher for Finland, 1.7 times higher for Norway and no difference for Sweden. When social restrictions were enforced to curb the spread of SARS-CoV-2 there were profound changes in outdoor recreational behavior. Future consideration of public health interventions that promote outdoor activities may increase exposure to vector-borne diseases. },
keywords = {Covid-19 (Coronavirus), TBE (Tick Borne Encephalitis)},
pubstate = {published},
tppubtype = {article}
}
During the pandemic outdoor activities were encouraged to mitigate transmission risk while providing safe spaces for social interactions. Human behaviour, which may favour or disfavour, contact rates between questing ticks and humans, is a key factor impacting tick-borne encephalitis (TBE) incidence. We analyzed annual and weekly TBE cases in Finland, Norway and Sweden from 2010 to 2021 to assess trend, seasonality, and discuss changes in human tick exposure imposed by COVID-19. We compared the pre-pandemic incidence (2010–2019) with the pandemic incidence (2020–2021) by fitting a generalized linear model (GLM) to incidence data. Pre-pandemic incidence was 1.0, 0.29 and 2.8 for Finland, Norway and Sweden, respectively, compared to incidence of 2.2, 1.0 and 3.9 during the pandemic years. However, there was an increasing trend for all countries across the whole study period. Therefore, we predicted the number of cases in 2020/2021 based on a model fitted to the annual cases in 2010–2019. The incidences during the pandemic were 1.3 times higher for Finland, 1.7 times higher for Norway and no difference for Sweden. When social restrictions were enforced to curb the spread of SARS-CoV-2 there were profound changes in outdoor recreational behavior. Future consideration of public health interventions that promote outdoor activities may increase exposure to vector-borne diseases.
84.
Marziano, Valentina; Guzzetta, Giorgio; Menegale, Francesco; Sacco, Chiara; Petrone, Daniele; Urdiales, Alberto Mateo; Manso, Martina Del; Bella, Antonino; Fabiani, Massimo; Vescio, Maria Fenicia; Riccardo, Flavia; Poletti, Piero; Manica, Mattia; Zardini, Agnese; d'Andrea, Valeria; Trentini, Filippo; Stefanelli, Paola; Rezza, Giovanni; Palamara, Anna Teresa; Brusaferro, Silvio; Ajelli, Marco; Pezzotti, Patrizio; Merler, Stefano
Estimating SARS-CoV-2 infections and associated changes in COVID-19 severity and fatality Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Estimating SARS-CoV-2 infections and associated changes in COVID-19 severity and fatality},
author = {Valentina Marziano and Giorgio Guzzetta and Francesco Menegale and Chiara Sacco and Daniele Petrone and Alberto Mateo Urdiales and Martina Del Manso and Antonino Bella and Massimo Fabiani and Maria Fenicia Vescio and Flavia Riccardo and Piero Poletti and Mattia Manica and Agnese Zardini and Valeria d'Andrea and Filippo Trentini and Paola Stefanelli and Giovanni Rezza and Anna Teresa Palamara and Silvio Brusaferro and Marco Ajelli and Patrizio Pezzotti and Stefano Merler},
url = {https://onlinelibrary.wiley.com/doi/10.1111/irv.13181},
doi = {10.1111/irv.13181},
year = {2023},
date = {2023-08-16},
urldate = {2023-08-16},
abstract = {Background
The difficulty in identifying SARS-CoV-2 infections has not only been the major obstacle to control the COVID-19 pandemic but also to quantify changes in the proportion of infections resulting in hospitalization, intensive care unit (ICU) admission, or death.
Methods
We developed a model of SARS-CoV-2 transmission and vaccination informed by official estimates of the time-varying reproduction number to estimate infections that occurred in Italy between February 2020 and 2022. Model outcomes were compared with the Italian National surveillance data to estimate changes in the SARS-CoV-2 infection ascertainment ratio (IAR), infection hospitalization ratio (IHR), infection ICU ratio (IIR), and infection fatality ratio (IFR) in five different sub-periods associated with the dominance of the ancestral lineages and Alpha, Delta, and Omicron BA.1 variants.
Results
We estimate that, over the first 2 years of pandemic, the IAR ranged between 15% and 40% (range of 95%CI: 11%–61%), with a peak value in the second half of 2020. The IHR, IIR, and IFR consistently decreased throughout the pandemic with 22–44-fold reductions between the initial phase and the Omicron period. At the end of the study period, we estimate an IHR of 0.24% (95%CI: 0.17–0.36), IIR of 0.015% (95%CI: 0.011–0.023), and IFR of 0.05% (95%CI: 0.04–0.08).
Conclusions
Since 2021, changes in the dominant SARS-CoV-2 variant, vaccination rollout, and the shift of infection to younger ages have reduced SARS-CoV-2 infection ascertainment. The same factors, combined with the improvement of patient management and care, contributed to a massive reduction in the severity and fatality of COVID-19.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Background
The difficulty in identifying SARS-CoV-2 infections has not only been the major obstacle to control the COVID-19 pandemic but also to quantify changes in the proportion of infections resulting in hospitalization, intensive care unit (ICU) admission, or death.
Methods
We developed a model of SARS-CoV-2 transmission and vaccination informed by official estimates of the time-varying reproduction number to estimate infections that occurred in Italy between February 2020 and 2022. Model outcomes were compared with the Italian National surveillance data to estimate changes in the SARS-CoV-2 infection ascertainment ratio (IAR), infection hospitalization ratio (IHR), infection ICU ratio (IIR), and infection fatality ratio (IFR) in five different sub-periods associated with the dominance of the ancestral lineages and Alpha, Delta, and Omicron BA.1 variants.
Results
We estimate that, over the first 2 years of pandemic, the IAR ranged between 15% and 40% (range of 95%CI: 11%–61%), with a peak value in the second half of 2020. The IHR, IIR, and IFR consistently decreased throughout the pandemic with 22–44-fold reductions between the initial phase and the Omicron period. At the end of the study period, we estimate an IHR of 0.24% (95%CI: 0.17–0.36), IIR of 0.015% (95%CI: 0.011–0.023), and IFR of 0.05% (95%CI: 0.04–0.08).
Conclusions
Since 2021, changes in the dominant SARS-CoV-2 variant, vaccination rollout, and the shift of infection to younger ages have reduced SARS-CoV-2 infection ascertainment. The same factors, combined with the improvement of patient management and care, contributed to a massive reduction in the severity and fatality of COVID-19.
The difficulty in identifying SARS-CoV-2 infections has not only been the major obstacle to control the COVID-19 pandemic but also to quantify changes in the proportion of infections resulting in hospitalization, intensive care unit (ICU) admission, or death.
Methods
We developed a model of SARS-CoV-2 transmission and vaccination informed by official estimates of the time-varying reproduction number to estimate infections that occurred in Italy between February 2020 and 2022. Model outcomes were compared with the Italian National surveillance data to estimate changes in the SARS-CoV-2 infection ascertainment ratio (IAR), infection hospitalization ratio (IHR), infection ICU ratio (IIR), and infection fatality ratio (IFR) in five different sub-periods associated with the dominance of the ancestral lineages and Alpha, Delta, and Omicron BA.1 variants.
Results
We estimate that, over the first 2 years of pandemic, the IAR ranged between 15% and 40% (range of 95%CI: 11%–61%), with a peak value in the second half of 2020. The IHR, IIR, and IFR consistently decreased throughout the pandemic with 22–44-fold reductions between the initial phase and the Omicron period. At the end of the study period, we estimate an IHR of 0.24% (95%CI: 0.17–0.36), IIR of 0.015% (95%CI: 0.011–0.023), and IFR of 0.05% (95%CI: 0.04–0.08).
Conclusions
Since 2021, changes in the dominant SARS-CoV-2 variant, vaccination rollout, and the shift of infection to younger ages have reduced SARS-CoV-2 infection ascertainment. The same factors, combined with the improvement of patient management and care, contributed to a massive reduction in the severity and fatality of COVID-19.
83.
Hobeika, Alexandre; Stauffer, Maxime Henri Tibault; Dub, Timothée; van Bortel, Wim; Beniston, Martin; Bukachi, Salome; Burci, Gian Luca; Crump, Lisa; Markotter, Prof Wanda; Sepe, Ludovico Pasquale; Placella, Enrichetta; Roche, Benjamin; Thiongane, Oumy; Wang, Zhanyun; Guérin, Frédérique; van Kleef, Esther
The values and risks of an Intergovernmental Panel for One Health to strengthen pandemic prevention, preparedness, and response Journal Article
In: The values and risks of an Intergovernmental Panel for One Health to strengthen pandemic prevention, preparedness, and response, vol. 11, iss. 8, pp. 1301-1307, 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {The values and risks of an Intergovernmental Panel for One Health to strengthen pandemic prevention, preparedness, and response},
author = {Alexandre Hobeika and Maxime Henri Tibault Stauffer and Timothée Dub and Wim van Bortel and Martin Beniston and Salome Bukachi and Gian Luca Burci and Lisa Crump and Prof Wanda Markotter and Ludovico Pasquale Sepe and Enrichetta Placella and Benjamin Roche and Oumy Thiongane and Zhanyun Wang and Frédérique Guérin and Esther van Kleef},
doi = {10.1016/S2214-109X(23)00246-2},
year = {2023},
date = {2023-08-15},
urldate = {2023-08-15},
journal = {The values and risks of an Intergovernmental Panel for One Health to strengthen pandemic prevention, preparedness, and response},
volume = {11},
issue = {8},
pages = {1301-1307},
abstract = {The COVID-19 pandemic has shown the need for better global governance of pandemic prevention, preparedness, and response (PPR) and has emphasised the importance of organised knowledge production and uptake. In this Health Policy, we assess the potential values and risks of establishing an Intergovernmental Panel for One Health (IPOH). Similar to the Intergovernmental Panel on Climate Change, an IPOH would facilitate knowledge uptake in policy making via a multisectoral approach, and hence support the addressing of infectious disease emergence and re-emergence at the human–animal–environment interface. The potential benefits to pandemic PPR include a clear, unified, and authoritative voice from the scientific community, support to help donors and institutions to prioritise their investments, evidence-based policies for implementation, and guidance on defragmenting the global health system. Potential risks include a scope not encompassing all pandemic origins, unclear efficacy in fostering knowledge uptake by policy makers, potentially inadequate speed in facilitating response efforts, and coordination challenges among an already dense set of stakeholders. We recommend weighing these factors when designing institutional reforms for a more effective global health system.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
The COVID-19 pandemic has shown the need for better global governance of pandemic prevention, preparedness, and response (PPR) and has emphasised the importance of organised knowledge production and uptake. In this Health Policy, we assess the potential values and risks of establishing an Intergovernmental Panel for One Health (IPOH). Similar to the Intergovernmental Panel on Climate Change, an IPOH would facilitate knowledge uptake in policy making via a multisectoral approach, and hence support the addressing of infectious disease emergence and re-emergence at the human–animal–environment interface. The potential benefits to pandemic PPR include a clear, unified, and authoritative voice from the scientific community, support to help donors and institutions to prioritise their investments, evidence-based policies for implementation, and guidance on defragmenting the global health system. Potential risks include a scope not encompassing all pandemic origins, unclear efficacy in fostering knowledge uptake by policy makers, potentially inadequate speed in facilitating response efforts, and coordination challenges among an already dense set of stakeholders. We recommend weighing these factors when designing institutional reforms for a more effective global health system.
82.
joseph l.-h. tsui,; john t. mccrone,; ben lambert,; sumali bajaj,; rhys p. d. inward,; paolo bosetti,; rosario evans pena,; houriiyah tegally,; verity hill,; alexander e. zarebski,; thomas p. peacock,; luyang liu,; neo wu,; megan davis,; isaac i. bogoch,; kamran khan,; meaghan kall,; nurin iwani binti abdul aziz,; rachel colquhoun,; áine o’toole,; ben jackson,; abhishek dasgupta,; eduan wilkinson,; tulio de oliveira,; the covid-19 genomics uk (cog-uk) consortium,; thomas r. connor,; nicholas j. loman,; vittoria colizza,; christophe fraser,; erik volz,; xiang ji,; bernardo gutierrez,; meera chand,; simon dellicour,; simon cauchemez,; jayna raghwani,; marc a. suchard,; philippe lemey,; andrew rambaut,; oliver g. pybus,; moritz u. g. kraemer,
Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1 Journal Article
In: Science, vol. 381, iss. 6655, pp. 336-343, 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1},
author = {joseph l.-h. tsui and john t. mccrone and ben lambert and sumali bajaj and rhys p. d. inward and paolo bosetti and rosario evans pena and houriiyah tegally and verity hill and alexander e. zarebski and thomas p. peacock and luyang liu and neo wu and megan davis and isaac i. bogoch and kamran khan and meaghan kall and nurin iwani binti abdul aziz and rachel colquhoun and áine o’toole and ben jackson and abhishek dasgupta and eduan wilkinson and tulio de oliveira and the covid-19 genomics uk (cog-uk) consortium and thomas r. connor and nicholas j. loman and vittoria colizza and christophe fraser and erik volz and xiang ji and bernardo gutierrez and meera chand and simon dellicour and simon cauchemez and jayna raghwani and marc a. suchard and philippe lemey and andrew rambaut and oliver g. pybus and moritz u. g. kraemer},
url = {https://www.science.org/doi/10.1126/science.adg6605#supplementary-materials},
doi = {10.1126/science.adg660},
year = {2023},
date = {2023-07-20},
urldate = {2023-07-20},
journal = {Science},
volume = {381},
issue = {6655},
pages = {336-343},
abstract = {Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) now arise in the context of heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron BA.1 genomes, we identified >6,000 introductions of the antigenically distinct VOC into England and analyzed their local transmission and dispersal history. We find that six of the eight largest English Omicron lineages were already transmitting when Omicron was first reported in southern Africa (22 November 2021). Multiple datasets show that importation of Omicron continued despite subsequent restrictions on travel from southern Africa as a result of export from well-connected secondary locations. Initiation and dispersal of Omicron transmission lineages in England was a two-stage process that can be explained by models of the country’s human geography and hierarchical travel network. Our results enable a comparison of the processes that drive the invasion of Omicron and other VOCs across multiple spatial scales.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) now arise in the context of heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron BA.1 genomes, we identified >6,000 introductions of the antigenically distinct VOC into England and analyzed their local transmission and dispersal history. We find that six of the eight largest English Omicron lineages were already transmitting when Omicron was first reported in southern Africa (22 November 2021). Multiple datasets show that importation of Omicron continued despite subsequent restrictions on travel from southern Africa as a result of export from well-connected secondary locations. Initiation and dispersal of Omicron transmission lineages in England was a two-stage process that can be explained by models of the country’s human geography and hierarchical travel network. Our results enable a comparison of the processes that drive the invasion of Omicron and other VOCs across multiple spatial scales.
81.
Cuypers, Lize; Keyaerts, Els; Hong, Samuel Leandro; Gorissen, Sarah; Menezes, Soraya Maria; Starick, Marick; Elslande, Jan Van; Weemaes, Matthias; Wawina-Bokalanga, Tony; Marti-Carreras, Joan; Vanmechelen, Bert; Holm, Bram Van; Bloemen, Mandy; Dogne, Jean-Michel; Dufrasne, François; Durkin, Keith; Ruelle, Jean; Mendonca, Ricardo De; Wollants, Elke; Vermeersch, Pieter; Consortium, COVID-19 Genomics Belgium; Boulouffe, Caroline; Djiena, Achille; Broucke, Caroline; Catry, Boudewijn; Lagrou, Katrien; Ranst, Marc Van; Neyts, Johan; Baele, Guy; Maes, Piet; André, Emmanuel; Dellicour, Simon; Weyenbergh, Johan Van
Immunovirological and environmental screening reveals actionable risk factors for fatal COVID-19 during post-vaccination nursing home outbreaks Journal Article
In: Nature Aging , vol. 3, pp. 722–733, 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Immunovirological and environmental screening reveals actionable risk factors for fatal COVID-19 during post-vaccination nursing home outbreaks},
author = {Lize Cuypers and Els Keyaerts and Samuel Leandro Hong and Sarah Gorissen and Soraya Maria Menezes and Marick Starick and Jan Van Elslande and Matthias Weemaes and Tony Wawina-Bokalanga and Joan Marti-Carreras and Bert Vanmechelen and Bram Van Holm and Mandy Bloemen and Jean-Michel Dogne and François Dufrasne and Keith Durkin and Jean Ruelle and Ricardo De Mendonca and Elke Wollants and Pieter Vermeersch and COVID-19 Genomics Belgium Consortium and Caroline Boulouffe and Achille Djiena and Caroline Broucke and Boudewijn Catry and Katrien Lagrou and Marc Van Ranst and Johan Neyts and Guy Baele and Piet Maes and Emmanuel André and Simon Dellicour and Johan Van Weyenbergh},
url = {https://www.nature.com/articles/s43587-023-00421-1#citeas},
doi = {10.1038/s43587-023-00421-1},
year = {2023},
date = {2023-05-22},
urldate = {2023-05-22},
journal = {Nature Aging },
volume = {3},
pages = {722–733},
abstract = {Coronavirus Disease 2019 (COVID-19) vaccination has resulted in excellent protection against fatal disease, including in older adults. However, risk factors for post-vaccination fatal COVID-19 are largely unknown. We comprehensively studied three large nursing home outbreaks (20–35% fatal cases among residents) by combining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) aerosol monitoring, whole-genome phylogenetic analysis and immunovirological profiling of nasal mucosa by digital nCounter transcriptomics. Phylogenetic investigations indicated that each outbreak stemmed from a single introduction event, although with different variants (Delta, Gamma and Mu). SARS-CoV-2 was detected in aerosol samples up to 52 d after the initial infection. Combining demographic, immune and viral parameters, the best predictive models for mortality comprised IFNB1 or age, viral ORF7a and ACE2 receptor transcripts. Comparison with published pre-vaccine fatal COVID-19 transcriptomic and genomic signatures uncovered a unique IRF3 low/IRF7 high immune signature in post-vaccine fatal COVID-19 outbreaks. A multi-layered strategy, including environmental sampling, immunomonitoring and early antiviral therapy, should be considered to prevent post-vaccination COVID-19 mortality in nursing homes.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Coronavirus Disease 2019 (COVID-19) vaccination has resulted in excellent protection against fatal disease, including in older adults. However, risk factors for post-vaccination fatal COVID-19 are largely unknown. We comprehensively studied three large nursing home outbreaks (20–35% fatal cases among residents) by combining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) aerosol monitoring, whole-genome phylogenetic analysis and immunovirological profiling of nasal mucosa by digital nCounter transcriptomics. Phylogenetic investigations indicated that each outbreak stemmed from a single introduction event, although with different variants (Delta, Gamma and Mu). SARS-CoV-2 was detected in aerosol samples up to 52 d after the initial infection. Combining demographic, immune and viral parameters, the best predictive models for mortality comprised IFNB1 or age, viral ORF7a and ACE2 receptor transcripts. Comparison with published pre-vaccine fatal COVID-19 transcriptomic and genomic signatures uncovered a unique IRF3 low/IRF7 high immune signature in post-vaccine fatal COVID-19 outbreaks. A multi-layered strategy, including environmental sampling, immunomonitoring and early antiviral therapy, should be considered to prevent post-vaccination COVID-19 mortality in nursing homes.
80.
de Meijere, Giulia; Valdano, Eugenio; Castellano, Claudio; Debin, Marion; Kengne-Kuetche, Charly; Turbelin, Clément; Noël, Harold; Weitz, Joshua S.; Paolotti, Daniela; Hermans, Lisa; Hens, Niel; Colizza, Vittoria
In: 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Attitudes towards booster, testing and isolation, and their impact on COVID-19 response in winter 2022/2023 in France, Belgium, and Italy: a cross-sectional survey and modelling study},
author = {Giulia de Meijere and Eugenio Valdano and Claudio Castellano and Marion Debin and Charly Kengne-Kuetche and Clément Turbelin and Harold Noël and Joshua S. Weitz and Daniela Paolotti and Lisa Hermans and Niel Hens and Vittoria Colizza
},
url = {https://www.sciencedirect.com/science/article/pii/S2666776223000327?via%3Dihub},
doi = {10.1016/j.lanepe.2023.100614},
year = {2023},
date = {2023-05-11},
urldate = {2023-05-11},
abstract = {The vast majority of survey participants (N = 4594) was willing to adhere to testing (>91%) and rapid isolation (>88%) across the three countries. Pronounced differences emerged in the declared senior adherence to booster vaccination (73% in France, 94% in Belgium, 86% in Italy). Epidemic model results estimate that testing and isolation protocols would confer significant benefit in reducing transmission (17–24% reduction, from R = 1.6 to R = 1.3 in France and Belgium, to R = 1.2 in Italy) with declared adherence. Achieving a mitigating level similar to the French protocol, the Belgian protocol would require 35% fewer tests (from 1 test to 0.65 test per infected person) and avoid the long isolation periods of the Italian protocol (average of 6 days vs. 11). A cost barrier to test would significantly decrease adherence in France and Belgium, undermining protocols’ effectiveness.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The vast majority of survey participants (N = 4594) was willing to adhere to testing (>91%) and rapid isolation (>88%) across the three countries. Pronounced differences emerged in the declared senior adherence to booster vaccination (73% in France, 94% in Belgium, 86% in Italy). Epidemic model results estimate that testing and isolation protocols would confer significant benefit in reducing transmission (17–24% reduction, from R = 1.6 to R = 1.3 in France and Belgium, to R = 1.2 in Italy) with declared adherence. Achieving a mitigating level similar to the French protocol, the Belgian protocol would require 35% fewer tests (from 1 test to 0.65 test per infected person) and avoid the long isolation periods of the Italian protocol (average of 6 days vs. 11). A cost barrier to test would significantly decrease adherence in France and Belgium, undermining protocols’ effectiveness.
79.
Menegale, Francesco; Manica, Mattia; Zardini, Agnese
Evaluation of Waning of SARS-CoV-2 Vaccine–Induced Immunity Journal Article
In: JAMA Network, 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Evaluation of Waning of SARS-CoV-2 Vaccine–Induced Immunity},
author = {Francesco Menegale and Mattia Manica and Agnese Zardini et al.},
url = {https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2804451},
doi = {10.1001/jamanetworkopen.2023.10650},
year = {2023},
date = {2023-05-03},
urldate = {2023-05-03},
journal = {JAMA Network},
abstract = {Importance Estimates of the rate of waning of vaccine effectiveness (VE) against COVID-19 are key to assess population levels of protection and future needs for booster doses to face the resurgence of epidemic waves.
Objective To quantify the progressive waning of VE associated with the Delta and Omicron variants of SARS-CoV-2 by number of received doses.
Data Sources PubMed and Web of Science were searched from the databases’ inception to October 19, 2022, as well as reference lists of eligible articles. Preprints were included.
Study Selection Selected studies for this systematic review and meta-analysis were original articles reporting estimates of VE over time against laboratory-confirmed SARS-CoV-2 infection and symptomatic disease.
Data Extraction and Synthesis Estimates of VE at different time points from vaccination were retrieved from original studies. A secondary data analysis was performed to project VE at any time from last dose administration, improving the comparability across different studies and between the 2 considered variants. Pooled estimates were obtained from random-effects meta-analysis.
Main Outcomes and Measures Outcomes were VE against laboratory-confirmed Omicron or Delta infection and symptomatic disease and half-life and waning rate associated with vaccine-induced protection.
Results A total of 799 original articles and 149 reviews published in peer-reviewed journals and 35 preprints were identified. Of these, 40 studies were included in the analysis. Pooled estimates of VE of a primary vaccination cycle against laboratory-confirmed Omicron infection and symptomatic disease were both lower than 20% at 6 months from last dose administration. Booster doses restored VE to levels comparable to those acquired soon after the administration of the primary cycle. However, 9 months after booster administration, VE against Omicron was lower than 30% against laboratory-confirmed infection and symptomatic disease. The half-life of VE against symptomatic infection was estimated to be 87 days (95% CI, 67-129 days) for Omicron compared with 316 days (95% CI, 240-470 days) for Delta. Similar waning rates of VE were found for different age segments of the population.
Conclusions and Relevance These findings suggest that the effectiveness of COVID-19 vaccines against laboratory-confirmed Omicron or Delta infection and symptomatic disease rapidly wanes over time after the primary vaccination cycle and booster dose. These results can inform the design of appropriate targets and timing for future vaccination programs.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Importance Estimates of the rate of waning of vaccine effectiveness (VE) against COVID-19 are key to assess population levels of protection and future needs for booster doses to face the resurgence of epidemic waves.
Objective To quantify the progressive waning of VE associated with the Delta and Omicron variants of SARS-CoV-2 by number of received doses.
Data Sources PubMed and Web of Science were searched from the databases’ inception to October 19, 2022, as well as reference lists of eligible articles. Preprints were included.
Study Selection Selected studies for this systematic review and meta-analysis were original articles reporting estimates of VE over time against laboratory-confirmed SARS-CoV-2 infection and symptomatic disease.
Data Extraction and Synthesis Estimates of VE at different time points from vaccination were retrieved from original studies. A secondary data analysis was performed to project VE at any time from last dose administration, improving the comparability across different studies and between the 2 considered variants. Pooled estimates were obtained from random-effects meta-analysis.
Main Outcomes and Measures Outcomes were VE against laboratory-confirmed Omicron or Delta infection and symptomatic disease and half-life and waning rate associated with vaccine-induced protection.
Results A total of 799 original articles and 149 reviews published in peer-reviewed journals and 35 preprints were identified. Of these, 40 studies were included in the analysis. Pooled estimates of VE of a primary vaccination cycle against laboratory-confirmed Omicron infection and symptomatic disease were both lower than 20% at 6 months from last dose administration. Booster doses restored VE to levels comparable to those acquired soon after the administration of the primary cycle. However, 9 months after booster administration, VE against Omicron was lower than 30% against laboratory-confirmed infection and symptomatic disease. The half-life of VE against symptomatic infection was estimated to be 87 days (95% CI, 67-129 days) for Omicron compared with 316 days (95% CI, 240-470 days) for Delta. Similar waning rates of VE were found for different age segments of the population.
Conclusions and Relevance These findings suggest that the effectiveness of COVID-19 vaccines against laboratory-confirmed Omicron or Delta infection and symptomatic disease rapidly wanes over time after the primary vaccination cycle and booster dose. These results can inform the design of appropriate targets and timing for future vaccination programs.
Objective To quantify the progressive waning of VE associated with the Delta and Omicron variants of SARS-CoV-2 by number of received doses.
Data Sources PubMed and Web of Science were searched from the databases’ inception to October 19, 2022, as well as reference lists of eligible articles. Preprints were included.
Study Selection Selected studies for this systematic review and meta-analysis were original articles reporting estimates of VE over time against laboratory-confirmed SARS-CoV-2 infection and symptomatic disease.
Data Extraction and Synthesis Estimates of VE at different time points from vaccination were retrieved from original studies. A secondary data analysis was performed to project VE at any time from last dose administration, improving the comparability across different studies and between the 2 considered variants. Pooled estimates were obtained from random-effects meta-analysis.
Main Outcomes and Measures Outcomes were VE against laboratory-confirmed Omicron or Delta infection and symptomatic disease and half-life and waning rate associated with vaccine-induced protection.
Results A total of 799 original articles and 149 reviews published in peer-reviewed journals and 35 preprints were identified. Of these, 40 studies were included in the analysis. Pooled estimates of VE of a primary vaccination cycle against laboratory-confirmed Omicron infection and symptomatic disease were both lower than 20% at 6 months from last dose administration. Booster doses restored VE to levels comparable to those acquired soon after the administration of the primary cycle. However, 9 months after booster administration, VE against Omicron was lower than 30% against laboratory-confirmed infection and symptomatic disease. The half-life of VE against symptomatic infection was estimated to be 87 days (95% CI, 67-129 days) for Omicron compared with 316 days (95% CI, 240-470 days) for Delta. Similar waning rates of VE were found for different age segments of the population.
Conclusions and Relevance These findings suggest that the effectiveness of COVID-19 vaccines against laboratory-confirmed Omicron or Delta infection and symptomatic disease rapidly wanes over time after the primary vaccination cycle and booster dose. These results can inform the design of appropriate targets and timing for future vaccination programs.
78.
Dellicour, Simon; Hong, Samuel L.; Hill, Verity; Dimartino, Dacia; Marier, Christian; Zappile, Paul; Harkins, Gordon W.; Lemey, Philippe; Baele, Guy; Duerr, Ralf; Heguy, Adriana
Variant-specific introduction and dispersal dynamics of SARS-CoV-2 in New York City – from Alpha to Omicron Journal Article
In: Plos Pathogens, 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Variant-specific introduction and dispersal dynamics of SARS-CoV-2 in New York City – from Alpha to Omicron},
author = {Simon Dellicour and Samuel L. Hong and Verity Hill and Dacia Dimartino and Christian Marier and Paul Zappile and Gordon W. Harkins and Philippe Lemey and Guy Baele and Ralf Duerr and Adriana Heguy},
url = {https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1011348},
doi = {10.1371/journal.ppat.1011348},
year = {2023},
date = {2023-04-18},
urldate = {2023-04-18},
journal = {Plos Pathogens},
abstract = {Since the latter part of 2020, SARS-CoV-2 evolution has been characterised by the emergence of viral variants associated with distinct biological characteristics. While the main research focus has centred on the ability of new variants to increase in frequency and impact the effective reproductive number of the virus, less attention has been placed on their relative ability to establish transmission chains and to spread through a geographic area. Here, we describe a phylogeographic approach to estimate and compare the introduction and dispersal dynamics of the main SARS-CoV-2 variants – Alpha, Iota, Delta, and Omicron – that circulated in the New York City area between 2020 and 2022. Notably, our results indicate that Delta had a lower ability to establish sustained transmission chains in the NYC area and that Omicron (BA.1) was the variant fastest to disseminate across the study area. The analytical approach presented here complements non-spatially-explicit analytical approaches that seek a better understanding of the epidemiological differences that exist among successive SARS-CoV-2 variants of concern.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Since the latter part of 2020, SARS-CoV-2 evolution has been characterised by the emergence of viral variants associated with distinct biological characteristics. While the main research focus has centred on the ability of new variants to increase in frequency and impact the effective reproductive number of the virus, less attention has been placed on their relative ability to establish transmission chains and to spread through a geographic area. Here, we describe a phylogeographic approach to estimate and compare the introduction and dispersal dynamics of the main SARS-CoV-2 variants – Alpha, Iota, Delta, and Omicron – that circulated in the New York City area between 2020 and 2022. Notably, our results indicate that Delta had a lower ability to establish sustained transmission chains in the NYC area and that Omicron (BA.1) was the variant fastest to disseminate across the study area. The analytical approach presented here complements non-spatially-explicit analytical approaches that seek a better understanding of the epidemiological differences that exist among successive SARS-CoV-2 variants of concern.
77.
Colosi, Elisabetta; Bassignana, Giulia; Barrat, Alain; Lina, Bruno; Vanhems, Philippe; Bielicki, Julia; Colizza, Vittoria
Minimizing school disruption under high incidence conditions due to the Omicron variant in France, Switzerland, Italy in January 2022 Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Minimizing school disruption under high incidence conditions due to the Omicron variant in France, Switzerland, Italy in January 2022},
author = {Elisabetta Colosi and Giulia Bassignana and Alain Barrat and Bruno Lina and Philippe Vanhems and Julia Bielicki and Vittoria Colizza
},
url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2023.28.5.2200192#abstract_content},
doi = {10.2807/1560-7917.ES.2023.28.5.2200192},
year = {2023},
date = {2023-02-02},
urldate = {2023-02-02},
abstract = {Background
As record cases of Omicron variant were registered in Europe in early 2022, schools remained a vulnerable setting undergoing large disruption.
Aim
Through mathematical modelling, we compared school protocols of reactive screening, regular screening, and reactive class closure implemented in France, in Baselland (Switzerland), and in Italy, respectively, and assessed them in terms of case prevention, testing resource demand, and schooldays lost.
Methods
We used a stochastic agent-based model of SARS-CoV-2 transmission in schools accounting for within- and across-class contacts from empirical contact data. We parameterised it to the Omicron BA.1 variant to reproduce the French Omicron wave in January 2022. We simulated the three protocols to assess their costs and effectiveness for varying peak incidence rates in the range experienced by European countries.
Results
We estimated that at the high incidence rates registered in France during the Omicron BA.1 wave in January 2022, the reactive screening protocol applied in France required higher test resources compared with the weekly screening applied in Baselland (0.50 vs 0.45 tests per student-week), but achieved considerably lower control (8% vs 21% reduction of peak incidence). The reactive class closure implemented in Italy was predicted to be very costly, leading to > 20% student-days lost.
Conclusions
At high incidence conditions, reactive screening protocols generate a large and unplanned demand in testing resources, for marginal control of school transmissions. Comparable or lower resources could be more efficiently used through weekly screening. Our findings can help define incidence levels triggering school protocols and optimise their cost-effectiveness.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Background
As record cases of Omicron variant were registered in Europe in early 2022, schools remained a vulnerable setting undergoing large disruption.
Aim
Through mathematical modelling, we compared school protocols of reactive screening, regular screening, and reactive class closure implemented in France, in Baselland (Switzerland), and in Italy, respectively, and assessed them in terms of case prevention, testing resource demand, and schooldays lost.
Methods
We used a stochastic agent-based model of SARS-CoV-2 transmission in schools accounting for within- and across-class contacts from empirical contact data. We parameterised it to the Omicron BA.1 variant to reproduce the French Omicron wave in January 2022. We simulated the three protocols to assess their costs and effectiveness for varying peak incidence rates in the range experienced by European countries.
Results
We estimated that at the high incidence rates registered in France during the Omicron BA.1 wave in January 2022, the reactive screening protocol applied in France required higher test resources compared with the weekly screening applied in Baselland (0.50 vs 0.45 tests per student-week), but achieved considerably lower control (8% vs 21% reduction of peak incidence). The reactive class closure implemented in Italy was predicted to be very costly, leading to > 20% student-days lost.
Conclusions
At high incidence conditions, reactive screening protocols generate a large and unplanned demand in testing resources, for marginal control of school transmissions. Comparable or lower resources could be more efficiently used through weekly screening. Our findings can help define incidence levels triggering school protocols and optimise their cost-effectiveness.
As record cases of Omicron variant were registered in Europe in early 2022, schools remained a vulnerable setting undergoing large disruption.
Aim
Through mathematical modelling, we compared school protocols of reactive screening, regular screening, and reactive class closure implemented in France, in Baselland (Switzerland), and in Italy, respectively, and assessed them in terms of case prevention, testing resource demand, and schooldays lost.
Methods
We used a stochastic agent-based model of SARS-CoV-2 transmission in schools accounting for within- and across-class contacts from empirical contact data. We parameterised it to the Omicron BA.1 variant to reproduce the French Omicron wave in January 2022. We simulated the three protocols to assess their costs and effectiveness for varying peak incidence rates in the range experienced by European countries.
Results
We estimated that at the high incidence rates registered in France during the Omicron BA.1 wave in January 2022, the reactive screening protocol applied in France required higher test resources compared with the weekly screening applied in Baselland (0.50 vs 0.45 tests per student-week), but achieved considerably lower control (8% vs 21% reduction of peak incidence). The reactive class closure implemented in Italy was predicted to be very costly, leading to > 20% student-days lost.
Conclusions
At high incidence conditions, reactive screening protocols generate a large and unplanned demand in testing resources, for marginal control of school transmissions. Comparable or lower resources could be more efficiently used through weekly screening. Our findings can help define incidence levels triggering school protocols and optimise their cost-effectiveness.
76.
Bonacina, Francesco; Boëlle, Pierre-Yves; Colizza, Vittoria; Lopez, Olivier; Thomas, Maud; Poletto, Chiara
Global patterns and drivers of influenza decline during the COVID-19 pandemic Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), HPAI (Avian Influenza), OpenDataSet
@article{nokey,
title = {Global patterns and drivers of influenza decline during the COVID-19 pandemic},
author = {Francesco Bonacina and Pierre-Yves Boëlle and Vittoria Colizza and Olivier Lopez and Maud Thomas and Chiara Poletto
},
url = {https://www.ijidonline.com/article/S1201-9712(22)00682-8/fulltext},
doi = {10.1016/j.ijid.2022.12.042},
year = {2023},
date = {2023-01-03},
urldate = {2023-01-03},
abstract = {Objectives
The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers.
Methods
The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors.
Results
During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The “zero-COVID” countries experienced the greatest decline.
Conclusion
Our findings set the stage for interpreting the resurgence of influenza worldwide.},
keywords = {Covid-19 (Coronavirus), HPAI (Avian Influenza), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Objectives
The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers.
Methods
The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors.
Results
During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The “zero-COVID” countries experienced the greatest decline.
Conclusion
Our findings set the stage for interpreting the resurgence of influenza worldwide.
The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers.
Methods
The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors.
Results
During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The “zero-COVID” countries experienced the greatest decline.
Conclusion
Our findings set the stage for interpreting the resurgence of influenza worldwide.
75.
Lai, Shengjie; Bogoch, Isaac; Ruktanonchai, Nick; Watts, Alexander; Lu, Xin; Yang, Weizhong; Yu, Hongjie; Khan, Kamran; Tatem, Andrew J
Assessing spread risk of COVID-19 in early 2020 Journal Article
In: vol. 5, iss. 4, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Assessing spread risk of COVID-19 in early 2020},
author = {Shengjie Lai and Isaac Bogoch and Nick Ruktanonchai and Alexander Watts and Xin Lu and Weizhong Yang and Hongjie Yu and Kamran Khan and Andrew J Tatem
},
url = {https://www.sciencedirect.com/science/article/pii/S2666764922000340?via%3Dihub},
doi = {10.1016/j.dsm.2022.08.004},
year = {2022},
date = {2022-12-08},
urldate = {2022-12-08},
volume = {5},
issue = {4},
abstract = {A novel coronavirus emerged in late 2019, named as the coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO). This study was originally conducted in January 2020 to estimate the potential risk and geographic range of COVID-19 spread at the early stage of the transmission. A series of connectivity and risk analyses based on domestic and international travel networks were conducted using historical aggregated mobile phone data and air passenger itinerary data. We found that the cordon sanitaire of the primary city was likely to have occurred during the latter stages of peak population numbers leaving the city, with travellers departing into neighbouring cities and other megacities in China. We estimated that there were 59,912 international air passengers, of which 834 (95% uncertainty interval: 478–1,349) had COVID-19 infection, with a strong correlation seen between the predicted risks of importation and the number of imported cases found. Given the limited understanding of emerging infectious diseases in the very early stages of outbreaks, our approaches and findings in assessing travel patterns and risk of transmission can help guide public health preparedness and intervention design for new COVID-19 waves caused by variants of concern and future pandemics to effectively limit transmission beyond its initial extent.
},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
A novel coronavirus emerged in late 2019, named as the coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO). This study was originally conducted in January 2020 to estimate the potential risk and geographic range of COVID-19 spread at the early stage of the transmission. A series of connectivity and risk analyses based on domestic and international travel networks were conducted using historical aggregated mobile phone data and air passenger itinerary data. We found that the cordon sanitaire of the primary city was likely to have occurred during the latter stages of peak population numbers leaving the city, with travellers departing into neighbouring cities and other megacities in China. We estimated that there were 59,912 international air passengers, of which 834 (95% uncertainty interval: 478–1,349) had COVID-19 infection, with a strong correlation seen between the predicted risks of importation and the number of imported cases found. Given the limited understanding of emerging infectious diseases in the very early stages of outbreaks, our approaches and findings in assessing travel patterns and risk of transmission can help guide public health preparedness and intervention design for new COVID-19 waves caused by variants of concern and future pandemics to effectively limit transmission beyond its initial extent.
74.
Zardini, Agnese; Galli, Margherita; Tirani, Marcello; Cereda, Danilo; Manica, Mattia; Trentini, Filippo; Guzzetta, Giorgio; Marziano, Valentina; Piccarreta, Raffaella; Melegaro, Alessia; Ajelli, Marco; Poletti, Piero; Merler, Stefano
A quantitative assessment of epidemiological parameters required to investigate COVID-19 burden Journal Article
In: Epidemics, vol. 37, pp. 100530, 2022, ISSN: 1755-4365.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {A quantitative assessment of epidemiological parameters required to investigate COVID-19 burden},
author = {Agnese Zardini and Margherita Galli and Marcello Tirani and Danilo Cereda and Mattia Manica and Filippo Trentini and Giorgio Guzzetta and Valentina Marziano and Raffaella Piccarreta and Alessia Melegaro and Marco Ajelli and Piero Poletti and Stefano Merler},
url = {https://www.sciencedirect.com/science/article/pii/S1755436521000748},
doi = {10.1016/j.epidem.2021.100530},
issn = {1755-4365},
year = {2022},
date = {2022-12-01},
urldate = {2022-12-01},
journal = {Epidemics},
volume = {37},
pages = {100530},
abstract = {Solid estimates describing the clinical course of SARS-CoV-2 infections are still lacking due to under-ascertainment of asymptomatic and mild-disease cases. In this work, we quantify age-specific probabilities of transitions between stages defining the natural history of SARS-CoV-2 infection from 1965 SARS-CoV-2 positive individuals identified in Italy between March and April 2020 among contacts of confirmed cases. Infected contacts of cases were confirmed via RT-PCR tests as part of contact tracing activities or retrospectively via IgG serological tests and followed-up for symptoms and clinical outcomes. In addition, we provide estimates of time intervals between key events defining the clinical progression of cases as obtained from a larger sample, consisting of 95,371 infections ascertained between February and July 2020. We found that being older than 60 years of age was associated with a 39.9% (95%CI: 36.2–43.6%) likelihood of developing respiratory symptoms or fever ≥ 37.5 °C after SARS-CoV-2 infection; the 22.3% (95%CI: 19.3–25.6%) of the infections in this age group required hospital care and the 1% (95%CI: 0.4–2.1%) were admitted to an intensive care unit (ICU). The corresponding proportions in individuals younger than 60 years were estimated at 27.9% (95%CI: 25.4–30.4%), 8.8% (95%CI: 7.3–10.5%) and 0.4% (95%CI: 0.1–0.9%), respectively. The infection fatality ratio (IFR) ranged from 0.2% (95%CI: 0.0–0.6%) in individuals younger than 60 years to 12.3% (95%CI: 6.9–19.7%) for those aged 80 years or more; the case fatality ratio (CFR) in these two age classes was 0.6% (95%CI: 0.1–2%) and 19.2% (95%CI: 10.9–30.1%), respectively. The median length of stay in hospital was 10 (IQR: 3–21) days; the length of stay in ICU was 11 (IQR: 6–19) days. The obtained estimates provide insights into the epidemiology of COVID-19 and could be instrumental to refine mathematical modeling work supporting public health decisions.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
Solid estimates describing the clinical course of SARS-CoV-2 infections are still lacking due to under-ascertainment of asymptomatic and mild-disease cases. In this work, we quantify age-specific probabilities of transitions between stages defining the natural history of SARS-CoV-2 infection from 1965 SARS-CoV-2 positive individuals identified in Italy between March and April 2020 among contacts of confirmed cases. Infected contacts of cases were confirmed via RT-PCR tests as part of contact tracing activities or retrospectively via IgG serological tests and followed-up for symptoms and clinical outcomes. In addition, we provide estimates of time intervals between key events defining the clinical progression of cases as obtained from a larger sample, consisting of 95,371 infections ascertained between February and July 2020. We found that being older than 60 years of age was associated with a 39.9% (95%CI: 36.2–43.6%) likelihood of developing respiratory symptoms or fever ≥ 37.5 °C after SARS-CoV-2 infection; the 22.3% (95%CI: 19.3–25.6%) of the infections in this age group required hospital care and the 1% (95%CI: 0.4–2.1%) were admitted to an intensive care unit (ICU). The corresponding proportions in individuals younger than 60 years were estimated at 27.9% (95%CI: 25.4–30.4%), 8.8% (95%CI: 7.3–10.5%) and 0.4% (95%CI: 0.1–0.9%), respectively. The infection fatality ratio (IFR) ranged from 0.2% (95%CI: 0.0–0.6%) in individuals younger than 60 years to 12.3% (95%CI: 6.9–19.7%) for those aged 80 years or more; the case fatality ratio (CFR) in these two age classes was 0.6% (95%CI: 0.1–2%) and 19.2% (95%CI: 10.9–30.1%), respectively. The median length of stay in hospital was 10 (IQR: 3–21) days; the length of stay in ICU was 11 (IQR: 6–19) days. The obtained estimates provide insights into the epidemiology of COVID-19 and could be instrumental to refine mathematical modeling work supporting public health decisions.
73.
Stefanelli, Paola; Trentini, Filippo; Petrone, Daniele; Mammone, Alessia; Ambrosio, Luigiana; Manica, Mattia; Guzzetta, Giorgio; d'Andrea, Valeria; Marziano, Valentina; Zardini, Agnese; Molina, Carla Grane; Ajelli, Marco; Martino, Angela Di; Riccardo, Flavia; Bella, Antonino; Schepisi, Monica Sane; Maraglino, Francesco; amd Anna Teresa Palamara, Piero Poletti; Brusaferro, Silvio; Rezza, Giovanni; Patrizio, Patrizio Pezzotti; Merler, Stefano; the Genomic SARS–CoV–2 National Surveillance Working Group, the Italian Integrated Surveillance of COVID–19 Study Group
Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022 Journal Article
In: 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{nokey,
title = {Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022},
author = {Paola Stefanelli and Filippo Trentini and Daniele Petrone and Alessia Mammone and Luigiana Ambrosio and Mattia Manica and Giorgio Guzzetta and Valeria d'Andrea and Valentina Marziano and Agnese Zardini and Carla Grane Molina and Marco Ajelli and Angela Di Martino and Flavia Riccardo and Antonino Bella and Monica Sane Schepisi and Francesco Maraglino and Piero Poletti amd Anna Teresa Palamara and Silvio Brusaferro and Giovanni Rezza and Patrizio Pezzotti Patrizio and Stefano Merler and the Genomic SARS–CoV–2 National Surveillance Working Group, the Italian Integrated Surveillance of COVID–19 Study Group
},
url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2022.27.45.2200125#html_fulltext},
doi = {10.2807/1560-7917.ES.2022.27.45.2200125},
year = {2022},
date = {2022-11-10},
urldate = {2022-11-10},
abstract = {Background
The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.
Aim
To comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.
Methods
We analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.
Results
Omicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9–80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7–3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers’ decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.
Conclusion
Estimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
Background
The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.
Aim
To comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.
Methods
We analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.
Results
Omicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9–80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7–3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers’ decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.
Conclusion
Estimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.
The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.
Aim
To comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.
Methods
We analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.
Results
Omicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9–80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7–3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers’ decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.
Conclusion
Estimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.
72.
Cuypers, Lize; Dellicour, Simon; Hong, Samuel L.; l. Potter, Barney; Verhasselt, Bruno; Vereecke, Nick; Lambrechts, Laurens; Durkin, Keith; Bours, Vincent; Klamer, Sofieke; Bayon-Vicente, Guillaume; Vael, Carl; Ariën, Kevin K.; Mendonca, Ricardo De; Soetens, Oriane; Michel, Charlotte; Bearzatto, Bertrand; Naesens, Reinout; Gras, Jeremie; Vankeerberghen, Anne; Matheeussen, Veerle; Martens, Geert; Obbels, Dagmar; Lemmens, Ann; den Poel, Bea Van; Even, Ellen Van; Rauw, Klara De; Waumans, Luc; Reynders, Marijke; Degosserie, Jonathan; Maes, Piet; André, Emmanuel; Baele, Guy
In: Viruses, vol. 14, no. 10, pp. 2301, 2022, ISSN: 1999-4915.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus)
@article{@article{2022b,
title = {Two Years of Genomic Surveillance in Belgium during the SARS-CoV-2 Pandemic to Attain Country-Wide Coverage and Monitor the Introduction and Spread of Emerging Variants},
author = {Lize Cuypers and Simon Dellicour and Samuel L. Hong and Barney l. Potter and Bruno Verhasselt and Nick Vereecke and Laurens Lambrechts and Keith Durkin and Vincent Bours and Sofieke Klamer and Guillaume Bayon-Vicente and Carl Vael and Kevin K. Ariën and Ricardo De Mendonca and Oriane Soetens and Charlotte Michel and Bertrand Bearzatto and Reinout Naesens and Jeremie Gras and Anne Vankeerberghen and Veerle Matheeussen and Geert Martens and Dagmar Obbels and Ann Lemmens and Bea Van den Poel and Ellen Van Even and Klara De Rauw and Luc Waumans and Marijke Reynders and Jonathan Degosserie and Piet Maes and Emmanuel André and Guy Baele},
url = {https://www.mdpi.com/1999-4915/14/10/2301},
doi = {https://doi.org/10.3390/v14102301},
issn = {1999-4915},
year = {2022},
date = {2022-10-20},
urldate = {2022-10-20},
journal = {Viruses},
volume = {14},
number = {10},
pages = {2301},
abstract = {An adequate SARS-CoV-2 genomic surveillance strategy has proven to be essential for countries to obtain a thorough understanding of the variants and lineages being imported and successfully established within their borders. During 2020, genomic surveillance in Belgium was not structurally implemented but performed by individual research laboratories that had to acquire the necessary funds themselves to perform this important task. At the start of 2021, a nationwide genomic surveillance consortium was established in Belgium to markedly increase the country’s genomic sequencing efforts (both in terms of intensity and representativeness), to perform quality control among participating laboratories, and to enable coordination and collaboration of research projects and publications. We here discuss the genomic surveillance efforts in Belgium before and after the establishment of its genomic sequencing consortium, provide an overview of the specifics of the consortium, and explore more details regarding the scientific studies that have been published as a result of the increased number of Belgian SARS-CoV-2 genomes that have become available.},
keywords = {Covid-19 (Coronavirus)},
pubstate = {published},
tppubtype = {article}
}
An adequate SARS-CoV-2 genomic surveillance strategy has proven to be essential for countries to obtain a thorough understanding of the variants and lineages being imported and successfully established within their borders. During 2020, genomic surveillance in Belgium was not structurally implemented but performed by individual research laboratories that had to acquire the necessary funds themselves to perform this important task. At the start of 2021, a nationwide genomic surveillance consortium was established in Belgium to markedly increase the country’s genomic sequencing efforts (both in terms of intensity and representativeness), to perform quality control among participating laboratories, and to enable coordination and collaboration of research projects and publications. We here discuss the genomic surveillance efforts in Belgium before and after the establishment of its genomic sequencing consortium, provide an overview of the specifics of the consortium, and explore more details regarding the scientific studies that have been published as a result of the increased number of Belgian SARS-CoV-2 genomes that have become available.
71.
Gonçalves, Bronner P; Hall, Matthew; Jassat, Waasila; Balan, Valeria; Murthy, Srinivas; Kartsonaki, Christiana; Semple, Malcolm G; Rojek, Amanda; Baruch, Joaquín; Reyes, Luis Felipe; Dasgupta, Abhishek; Dunning, Jake; Citarella, Barbara Wanjiru; Pritchard, Mark; Martín-Quiros, Alejandro; Baillie, Uluhan SiliJ Kenneth; Aryal, Diptesh; Arabi, Yaseen; Rashan, Aasiyah; Nor, Andrea AnghebenJanice CaoiliFrançois Martin CarrierEwen M HarrisonJoan Gómez-JunyentClaudia Figueiredo-MelloJames Joshua DouglasMohd Basri Mat; Chow, Yock Ping; Wong, Xin Ci; Bertagnolio, Silvia; Thwin, Soe Soe; Streinu-Cercel, Anca; Salazar, Leonardo; Rishu, Asgar; Rangappa, Rajavardhan; Ong, David SY; Hashmi, Madiha; Carson, Gail; Diaz, Janet; Fowler, Rob; Kraemer, Moritz UG; Wils, Evert-Jan; Horby, Peter; Merson, Laura; Olliaro, Piero L; Group, ISARIC Clinical Characterisation
In: elife, 2022.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients},
author = {Bronner P Gonçalves and Matthew Hall and Waasila Jassat and Valeria Balan and Srinivas Murthy and Christiana Kartsonaki and Malcolm G Semple and Amanda Rojek and Joaquín Baruch and Luis Felipe Reyes and Abhishek Dasgupta and Jake Dunning and Barbara Wanjiru Citarella and Mark Pritchard and Alejandro Martín-Quiros and Uluhan SiliJ Kenneth Baillie and Diptesh Aryal and Yaseen Arabi and Aasiyah Rashan and Andrea AnghebenJanice CaoiliFrançois Martin CarrierEwen M HarrisonJoan Gómez-JunyentClaudia Figueiredo-MelloJames Joshua DouglasMohd Basri Mat Nor and Yock Ping Chow and Xin Ci Wong and Silvia Bertagnolio and Soe Soe Thwin and Anca Streinu-Cercel and Leonardo Salazar and Asgar Rishu and Rajavardhan Rangappa and David SY Ong and Madiha Hashmi and Gail Carson and Janet Diaz and Rob Fowler and Moritz UG Kraemer and Evert-Jan Wils and Peter Horby and Laura Merson and Piero L Olliaro and ISARIC Clinical Characterisation Group},
url = {https://elifesciences.org/articles/80556},
doi = {https://doi.org/10.7554/eLife.80556},
year = {2022},
date = {2022-10-05},
urldate = {2022-10-05},
journal = {elife},
abstract = {Background:
Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings.
Methods:
Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries.
Results:
Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61–0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population.
Conclusions:
Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Background:
Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings.
Methods:
Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries.
Results:
Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61–0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population.
Conclusions:
Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.
Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings.
Methods:
Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries.
Results:
Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61–0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population.
Conclusions:
Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.
70.
Zeller, Mark; Gangavarapu, Karthik; Anderson, Catelyn; Smither, Allison R.; Vanchiere, John A.; Rose, Rebecca; Snyder, Daniel J.; Dudas, Gytis; Watts, Alexander; Matteson, Nathaniel L.; Robles-Sikisaka, Refugio; Marshall, Maximilian; Feehan, Amy K.; Sabino-Santos, Gilberto; Bell-Kareem, Antoinette R.; Hughes, Laura D.; Alkuzweny, Manar; Snarski, Patricia; Garcia-Diaz, Julia; Scott, Rona S.; Melnik, Lilia I.; Klitting, Raphaëlle; McGraw, Michelle; Belda-Ferre, Pedro; DeHoff, Peter; Sathe, Shashank; Marotz, Clarisse; Grubaugh, Nathan D.; Nolan, David J.; Drouin, Arnaud C.; Genemaras, Kaylynn J.; Chao, Karissa; Topol, Sarah; Spencer, Emily; Nicholson, Laura; Aigner, Stefan; Yeo, Gene W.; Farnaes, Lauge; Hobbs, Charlotte A.; Laurent, Louise C.; Knight, Rob; Hodcroft, Emma B.; Khan, Kamran; Fusco, Dahlene N.; Cooper, Vaughn S.; Lemey, Phillipe; Gardner, Lauren; Lamers, Susanna L.; Kamil, Jeremy P.; Garry, Robert F.; Suchard, Marc A.; Andersen, Kristian G.
Emergence of an early SARS-CoV-2 epidemic in the United States Journal Article
In: Cell, vol. 184, iss. 19, pp. 4939-4952.e15, 2022, ISSN: 0092-8674.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{nokey,
title = {Emergence of an early SARS-CoV-2 epidemic in the United States},
author = {Mark Zeller and Karthik Gangavarapu and Catelyn Anderson and Allison R. Smither and John A. Vanchiere and Rebecca Rose and Daniel J. Snyder and Gytis Dudas and Alexander Watts and Nathaniel L. Matteson and Refugio Robles-Sikisaka and Maximilian Marshall and Amy K. Feehan and Gilberto Sabino-Santos and Antoinette R. Bell-Kareem and Laura D. Hughes and Manar Alkuzweny and Patricia Snarski and Julia Garcia-Diaz and Rona S. Scott and Lilia I. Melnik and Raphaëlle Klitting and Michelle McGraw and Pedro Belda-Ferre and Peter DeHoff and Shashank Sathe and Clarisse Marotz and Nathan D. Grubaugh and David J. Nolan and Arnaud C. Drouin and Kaylynn J. Genemaras and Karissa Chao and Sarah Topol and Emily Spencer and Laura Nicholson and Stefan Aigner and Gene W. Yeo and Lauge Farnaes and Charlotte A. Hobbs and Louise C. Laurent and Rob Knight and Emma B. Hodcroft and Kamran Khan and Dahlene N. Fusco and Vaughn S. Cooper and Phillipe Lemey and Lauren Gardner and Susanna L. Lamers and Jeremy P. Kamil and Robert F. Garry and Marc A. Suchard and Kristian G. Andersen},
url = {https://www.sciencedirect.com/science/article/pii/S0092867421008898},
doi = {10.1016/j.cell.2021.07.030},
issn = {0092-8674},
year = {2022},
date = {2022-09-16},
urldate = {2022-09-16},
journal = {Cell},
volume = {184},
issue = {19},
pages = {4939-4952.e15},
abstract = {The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.
69.
Erazo, Diana; Vincenti-Gonzalez, Maria F.; van Loenhout, Joris A. F.; Hubin, Pierre; Vandromme, Mathil; Maes, Piet; Taquet, Maxime; Weyenbergh, Johan Van; Catteau, Lucy; Dellicour, Simon
Investigating COVID-19 Vaccine Impact on the Risk of Hospitalisation through the Analysis of National Surveillance Data Collected in Belgium Journal Article
In: Viruses, vol. 14, no. 6, pp. 1315, 2022, ISSN: 1999-4915.
Abstract | Links | BibTeX | Tags: Covid-19 (Coronavirus), OpenDataSet
@article{@article{2022,
title = {Investigating COVID-19 Vaccine Impact on the Risk of Hospitalisation through the Analysis of National Surveillance Data Collected in Belgium},
author = {Diana Erazo and Maria F. Vincenti-Gonzalez and Joris A. F. van Loenhout and Pierre Hubin and Mathil Vandromme and Piet Maes and Maxime Taquet and Johan Van Weyenbergh and Lucy Catteau and Simon Dellicour},
url = {https://www.mdpi.com/1999-4915/14/6/1315},
doi = {https://doi.org/10.3390/v14061315},
issn = {1999-4915},
year = {2022},
date = {2022-06-16},
urldate = {2022-06-16},
journal = {Viruses},
volume = {14},
number = {6},
pages = {1315},
abstract = {The national vaccination campaign against SARS-CoV-2 started in January 2021 in Belgium. In the present study, we aimed to use national hospitalisation surveillance data to investigate the recent evolution of vaccine impact on the risk of COVID-19 hospitalisation. We analysed aggregated data from 27,608 COVID-19 patients hospitalised between October 2021 and February 2022, stratified by age category and vaccination status. For each period, vaccination status, and age group, we estimated risk ratios (RR) corresponding to the ratio between the probability of being hospitalised following SARS-CoV-2 infection if belonging to the vaccinated population and the same probability if belonging to the unvaccinated population. In October 2021, a relatively high RR was estimated for vaccinated people > 75 years old, possibly reflecting waning immunity within this group, which was vaccinated early in 2021 and invited to receive the booster vaccination at that time. In January 2022, a RR increase was observed in all age categories coinciding with the dominance of the Omicron variant. Despite the absence of control for factors like comorbidities, previous infections, or time since the last administered vaccine, we showed that such real-time aggregated data make it possible to approximate trends in vaccine impact over time.},
keywords = {Covid-19 (Coronavirus), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The national vaccination campaign against SARS-CoV-2 started in January 2021 in Belgium. In the present study, we aimed to use national hospitalisation surveillance data to investigate the recent evolution of vaccine impact on the risk of COVID-19 hospitalisation. We analysed aggregated data from 27,608 COVID-19 patients hospitalised between October 2021 and February 2022, stratified by age category and vaccination status. For each period, vaccination status, and age group, we estimated risk ratios (RR) corresponding to the ratio between the probability of being hospitalised following SARS-CoV-2 infection if belonging to the vaccinated population and the same probability if belonging to the unvaccinated population. In October 2021, a relatively high RR was estimated for vaccinated people > 75 years old, possibly reflecting waning immunity within this group, which was vaccinated early in 2021 and invited to receive the booster vaccination at that time. In January 2022, a RR increase was observed in all age categories coinciding with the dominance of the Omicron variant. Despite the absence of control for factors like comorbidities, previous infections, or time since the last administered vaccine, we showed that such real-time aggregated data make it possible to approximate trends in vaccine impact over time.