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.
143.
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.
142.
Decoupes, Rémy; Roche, Mathieu; Teisseire, Maguelonne
GeoNLPlify: A spatial data augmentation enhancing text classification for crisis monitoring Journal Article
In: Intelligent Data Analysis, pp. 1-25, 2023.
Abstract | Links | BibTeX | Tags: OpenDataSet, Text mining
@article{nokey,
title = {GeoNLPlify: A spatial data augmentation enhancing text classification for crisis monitoring},
author = {Rémy Decoupes and Mathieu Roche and Maguelonne Teisseire},
url = {https://content.iospress.com/articles/intelligent-data-analysis/ida230040},
doi = {10.3233/IDA-230040},
year = {2023},
date = {2023-07-06},
urldate = {2023-07-06},
journal = {Intelligent Data Analysis},
pages = {1-25},
abstract = {Crises such as natural disasters and public health emergencies generate vast amounts of text data, making it challenging to classify the information into relevant categories. Acquiring expert-labeled data for such scenarios can be difficult, leading to limited training datasets for text classification by fine-tuning BERT-like models. Unfortunately, traditional data augmentation techniques only slightly improve F1-scores. How can data augmentation be used to obtain better results in this applied domain? In this paper, using neural network explicability methods, we aim to highlight that fine-tuned BERT-like models on crisis corpora give too much importance to spatial information to make their predictions. This overfitting of spatial information limits their ability to generalize especially when the event which occurs in a place has evolved and changed since the training dataset has been built. To reduce this bias, we propose GeoNLPlify,1
a novel data augmentation technique that leverages spatial information to generate new labeled data for text classification related to crises. Our approach aims to address overfitting without necessitating modifications to the underlying model architecture, distinguishing it from other prevalent methods employed to combat overfitting. Our results show that GeoNLPlify significantly improves F1-scores, demonstrating the potential of the spatial information for data augmentation for crisis-related text classification tasks. In order to evaluate the contribution of our method, GeoNLPlify is applied to three public datasets (PADI-web, CrisisNLP and SST2) and compared with classical natural language processing data augmentations.},
keywords = {OpenDataSet, Text mining},
pubstate = {published},
tppubtype = {article}
}
Crises such as natural disasters and public health emergencies generate vast amounts of text data, making it challenging to classify the information into relevant categories. Acquiring expert-labeled data for such scenarios can be difficult, leading to limited training datasets for text classification by fine-tuning BERT-like models. Unfortunately, traditional data augmentation techniques only slightly improve F1-scores. How can data augmentation be used to obtain better results in this applied domain? In this paper, using neural network explicability methods, we aim to highlight that fine-tuned BERT-like models on crisis corpora give too much importance to spatial information to make their predictions. This overfitting of spatial information limits their ability to generalize especially when the event which occurs in a place has evolved and changed since the training dataset has been built. To reduce this bias, we propose GeoNLPlify,1
a novel data augmentation technique that leverages spatial information to generate new labeled data for text classification related to crises. Our approach aims to address overfitting without necessitating modifications to the underlying model architecture, distinguishing it from other prevalent methods employed to combat overfitting. Our results show that GeoNLPlify significantly improves F1-scores, demonstrating the potential of the spatial information for data augmentation for crisis-related text classification tasks. In order to evaluate the contribution of our method, GeoNLPlify is applied to three public datasets (PADI-web, CrisisNLP and SST2) and compared with classical natural language processing data augmentations.
a novel data augmentation technique that leverages spatial information to generate new labeled data for text classification related to crises. Our approach aims to address overfitting without necessitating modifications to the underlying model architecture, distinguishing it from other prevalent methods employed to combat overfitting. Our results show that GeoNLPlify significantly improves F1-scores, demonstrating the potential of the spatial information for data augmentation for crisis-related text classification tasks. In order to evaluate the contribution of our method, GeoNLPlify is applied to three public datasets (PADI-web, CrisisNLP and SST2) and compared with classical natural language processing data augmentations.
141.
Valentin, Sarah; Decoupes, Rémy; Lancelot, Renaud; Roche, Mathieu
Animal disease surveillance: How to represent textual data for classifying epidemiological information Journal Article
In: ScienceDirect, 2023.
Abstract | Links | BibTeX | Tags:
@article{nokey,
title = {Animal disease surveillance: How to represent textual data for classifying epidemiological information},
author = {Sarah Valentin and Rémy Decoupes and Renaud Lancelot and Mathieu Roche
},
url = {https://www.sciencedirect.com/science/article/pii/S016758772300096X?via%3Dihub},
doi = {10.1016/j.prevetmed.2023.105932},
year = {2023},
date = {2023-07-04},
urldate = {2023-07-04},
journal = {ScienceDirect},
abstract = {The value of informal sources in increasing the timeliness of disease outbreak detection and providing detailed epidemiological information in the early warning and preparedness context is recognized. This study evaluates machine learning methods for classifying information from animal disease-related news at a fine-grained level (i.e., epidemiological topic). We compare two textual representations, the bag-of-words method and a distributional approach, i.e., word embeddings. Both representations performed well for binary relevance classification (F-measure of 0.839 and 0.871, respectively). Bag-of-words representation was outperformed by word embedding representation for classifying sentences into fine-grained epidemiological topics (F-measure of 0.745). Our results suggest that the word embedding approach is of interest in the context of low-frequency classes in a specialized domain. However, this representation did not bring significant performance improvements for binary relevance classification, indicating that the textual representation should be adapted to each classification task.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The value of informal sources in increasing the timeliness of disease outbreak detection and providing detailed epidemiological information in the early warning and preparedness context is recognized. This study evaluates machine learning methods for classifying information from animal disease-related news at a fine-grained level (i.e., epidemiological topic). We compare two textual representations, the bag-of-words method and a distributional approach, i.e., word embeddings. Both representations performed well for binary relevance classification (F-measure of 0.839 and 0.871, respectively). Bag-of-words representation was outperformed by word embedding representation for classifying sentences into fine-grained epidemiological topics (F-measure of 0.745). Our results suggest that the word embedding approach is of interest in the context of low-frequency classes in a specialized domain. However, this representation did not bring significant performance improvements for binary relevance classification, indicating that the textual representation should be adapted to each classification task.
140.
Dagostin, Francesca; Tagliapietra, Valentina; Marini, Giovanni; Ferrari, Giulia; Cervellini, Marco; Wint, William; Alexander, Neil S.; Zuccali, Maria Grazia; Molinaro, Silvia; Fiorito, Nahuel; Dub, Timothée; Rocchini, Duccio; Rizzoli, Annapaola
High habitat richness reduces the risk of tick-borne encephalitis in Europe: A multi-scale study Journal Article
In: One Health, vol. 18, pp. 100669, 2023, ISSN: 2352-7714.
Abstract | Links | BibTeX | Tags: TBE (Tick Borne Encephalitis)
@article{nokey,
title = {High habitat richness reduces the risk of tick-borne encephalitis in Europe: A multi-scale study},
author = {Francesca Dagostin and Valentina Tagliapietra and Giovanni Marini and Giulia Ferrari and Marco Cervellini and William Wint and Neil S. Alexander and Maria Grazia Zuccali and Silvia Molinaro and Nahuel Fiorito and Timothée Dub and Duccio Rocchini and Annapaola Rizzoli},
url = {https://www.sciencedirect.com/science/article/pii/S2352771423001891},
doi = {10.1016/j.onehlt.2023.100669},
issn = {2352-7714},
year = {2023},
date = {2023-06-01},
urldate = {2023-06-01},
journal = {One Health},
volume = {18},
pages = {100669},
abstract = {Background
The natural transmission cycle of tick-borne encephalitis (TBE) virus is enhanced by complex interactions between ticks and key hosts strongly connected to habitat characteristics. The diversity of wildlife host species and their relative abundance is known to affect transmission of tick-borne diseases. Therefore, in the current context of global biodiversity loss, we explored the relationship between habitat richness and the pattern of human TBE cases in Europe to assess biodiversity's role in disease risk mitigation.
Methods
We assessed human TBE case distribution across 879 European regions using official epidemiological data reported to The European Surveillance System (TESSy) between 2017 and 2021 from 15 countries. We explored the relationship between TBE presence and the habitat richness index (HRI1) by means of binomial regression. We validated our findings at local scale using data collected between 2017 and 2021 in 227 municipalities located in Trento and Belluno provinces, two known TBE foci in northern Italy.
Findings
Our results showed a significant parabolic effect of HRI on the probability of presence of human TBE cases in the European regions included in our dataset, and a significant, negative effect of HRI on the local presence of TBE in northern Italy. At both spatial scales, TBE risk decreases in areas with higher values of HRI.
Interpretation
To our knowledge, no efforts have yet been made to explore the relationship between biodiversity and TBE risk, probably due to the scarcity of high-resolution, large-scale data about the abundance or density of critical host species. Hence, in this study we considered habitat richness as proxy for vertebrate host diversity. The results suggest that in highly diverse habitats TBE risk decreases. Hence, biodiversity loss could enhance TBE risk for both humans and wildlife. This association is relevant to support the hypothesis that the maintenance of highly diverse ecosystems mitigates disease risk.},
keywords = {TBE (Tick Borne Encephalitis)},
pubstate = {published},
tppubtype = {article}
}
Background
The natural transmission cycle of tick-borne encephalitis (TBE) virus is enhanced by complex interactions between ticks and key hosts strongly connected to habitat characteristics. The diversity of wildlife host species and their relative abundance is known to affect transmission of tick-borne diseases. Therefore, in the current context of global biodiversity loss, we explored the relationship between habitat richness and the pattern of human TBE cases in Europe to assess biodiversity's role in disease risk mitigation.
Methods
We assessed human TBE case distribution across 879 European regions using official epidemiological data reported to The European Surveillance System (TESSy) between 2017 and 2021 from 15 countries. We explored the relationship between TBE presence and the habitat richness index (HRI1) by means of binomial regression. We validated our findings at local scale using data collected between 2017 and 2021 in 227 municipalities located in Trento and Belluno provinces, two known TBE foci in northern Italy.
Findings
Our results showed a significant parabolic effect of HRI on the probability of presence of human TBE cases in the European regions included in our dataset, and a significant, negative effect of HRI on the local presence of TBE in northern Italy. At both spatial scales, TBE risk decreases in areas with higher values of HRI.
Interpretation
To our knowledge, no efforts have yet been made to explore the relationship between biodiversity and TBE risk, probably due to the scarcity of high-resolution, large-scale data about the abundance or density of critical host species. Hence, in this study we considered habitat richness as proxy for vertebrate host diversity. The results suggest that in highly diverse habitats TBE risk decreases. Hence, biodiversity loss could enhance TBE risk for both humans and wildlife. This association is relevant to support the hypothesis that the maintenance of highly diverse ecosystems mitigates disease risk.
The natural transmission cycle of tick-borne encephalitis (TBE) virus is enhanced by complex interactions between ticks and key hosts strongly connected to habitat characteristics. The diversity of wildlife host species and their relative abundance is known to affect transmission of tick-borne diseases. Therefore, in the current context of global biodiversity loss, we explored the relationship between habitat richness and the pattern of human TBE cases in Europe to assess biodiversity's role in disease risk mitigation.
Methods
We assessed human TBE case distribution across 879 European regions using official epidemiological data reported to The European Surveillance System (TESSy) between 2017 and 2021 from 15 countries. We explored the relationship between TBE presence and the habitat richness index (HRI1) by means of binomial regression. We validated our findings at local scale using data collected between 2017 and 2021 in 227 municipalities located in Trento and Belluno provinces, two known TBE foci in northern Italy.
Findings
Our results showed a significant parabolic effect of HRI on the probability of presence of human TBE cases in the European regions included in our dataset, and a significant, negative effect of HRI on the local presence of TBE in northern Italy. At both spatial scales, TBE risk decreases in areas with higher values of HRI.
Interpretation
To our knowledge, no efforts have yet been made to explore the relationship between biodiversity and TBE risk, probably due to the scarcity of high-resolution, large-scale data about the abundance or density of critical host species. Hence, in this study we considered habitat richness as proxy for vertebrate host diversity. The results suggest that in highly diverse habitats TBE risk decreases. Hence, biodiversity loss could enhance TBE risk for both humans and wildlife. This association is relevant to support the hypothesis that the maintenance of highly diverse ecosystems mitigates disease risk.
139.
Marini, Giovanni; Tagliapietra, Valentina; Cristofolini, Fabiana; Cristofori, Antonella; Dagostin, Francesca; Zuccali, Maria Grazia; Molinaro, Silvia; Gottardini, Elena; Rizzoli, Annapaola
Correlation between airborne pollen data and the risk of tick-borne encephalitis in northern Italy Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: OpenDataSet, TBE (Tick Borne Encephalitis)
@article{nokey_42,
title = {Correlation between airborne pollen data and the risk of tick-borne encephalitis in northern Italy},
author = {Giovanni Marini and Valentina Tagliapietra and Fabiana Cristofolini and Antonella Cristofori and Francesca Dagostin and Maria Grazia Zuccali and Silvia Molinaro and Elena Gottardini and Annapaola Rizzoli },
url = {https://www.nature.com/articles/s41598-023-35478-w#article-info},
doi = {10.1038/s41598-023-35478-w},
year = {2023},
date = {2023-05-22},
urldate = {2023-05-22},
abstract = {Tick-borne encephalitis (TBE) is caused by a flavivirus that infects animals including humans. In Europe, the TBE virus circulates enzootically in natural foci among ticks and rodent hosts. The abundance of ticks depends on the abundance of rodent hosts, which in turn depends on the availability of food resources, such as tree seeds. Trees can exhibit large inter-annual fluctuations in seed production (masting), which influences the abundance of rodents the following year, and the abundance of nymphal ticks two years later. Thus, the biology of this system predicts a 2-year time lag between masting and the incidence of tick-borne diseases such as TBE. As airborne pollen abundance is related to masting, we investigated whether inter-annual variation in pollen load could be directly correlated with inter-annual variation in the incidence of TBE in human populations with a 2-year time lag. We focused our study on the province of Trento (northern Italy), where 206 TBE cases were notified between 1992 and 2020. We tested the relationship between TBE incidence and pollen load collected from 1989 to 2020 for 7 different tree species common in our study area. Through univariate analysis we found that the pollen quantities recorded two years prior for two tree species, hop-hornbeam (Ostrya carpinifolia) and downy oak (Quercus pubescens), were positively correlated with TBE emergence (R2 = 0.2) while a multivariate model with both tree species better explained the variation in annual TBE incidence (R2 = 0.34). To the best of our knowledge, this is the first attempt at quantifying the correlation between pollen quantities and the incidence of TBE in human populations. As pollen loads are collected by widespread aerobiological networks using standardized procedures, our study could be easily replicated to test their potential as early warning system for TBE and other tick-borne diseases.},
keywords = {OpenDataSet, TBE (Tick Borne Encephalitis)},
pubstate = {published},
tppubtype = {article}
}
Tick-borne encephalitis (TBE) is caused by a flavivirus that infects animals including humans. In Europe, the TBE virus circulates enzootically in natural foci among ticks and rodent hosts. The abundance of ticks depends on the abundance of rodent hosts, which in turn depends on the availability of food resources, such as tree seeds. Trees can exhibit large inter-annual fluctuations in seed production (masting), which influences the abundance of rodents the following year, and the abundance of nymphal ticks two years later. Thus, the biology of this system predicts a 2-year time lag between masting and the incidence of tick-borne diseases such as TBE. As airborne pollen abundance is related to masting, we investigated whether inter-annual variation in pollen load could be directly correlated with inter-annual variation in the incidence of TBE in human populations with a 2-year time lag. We focused our study on the province of Trento (northern Italy), where 206 TBE cases were notified between 1992 and 2020. We tested the relationship between TBE incidence and pollen load collected from 1989 to 2020 for 7 different tree species common in our study area. Through univariate analysis we found that the pollen quantities recorded two years prior for two tree species, hop-hornbeam (Ostrya carpinifolia) and downy oak (Quercus pubescens), were positively correlated with TBE emergence (R2 = 0.2) while a multivariate model with both tree species better explained the variation in annual TBE incidence (R2 = 0.34). To the best of our knowledge, this is the first attempt at quantifying the correlation between pollen quantities and the incidence of TBE in human populations. As pollen loads are collected by widespread aerobiological networks using standardized procedures, our study could be easily replicated to test their potential as early warning system for TBE and other tick-borne diseases.
138.
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.
137.
Syed, Mehtab Alam; Arsevska, Elena; Roche, Mathieu; Teissere, Maguelonne
A metadata approach to classify domain-specific documents for Event-based Surveillance Systems Conference
International Conference on Communication, Computing and Digital Systems (C-CODE), 2023.
@conference{nokey,
title = {A metadata approach to classify domain-specific documents for Event-based Surveillance Systems},
author = {Mehtab Alam Syed and Elena Arsevska and Mathieu Roche and Maguelonne Teissere},
url = {https://www.researchgate.net/publication/371264619_A_metadata_approach_to_classify_domain-specific_documents_for_Event-based_Surveillance_Systems#fullTextFileContent},
doi = {https://doi.org/10.1109/C-CODE58145.2023.10139883},
year = {2023},
date = {2023-05-17},
urldate = {2023-05-17},
booktitle = {International Conference on Communication, Computing and Digital Systems (C-CODE)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
136.
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.
135.
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.
134.
Fesce, Elisa; Marini, Giovanni; Rosà, Roberto; Lelli, Davide; Cerioli, Monica Pierangela; Chiari, Mario; Farioli, Marco; Ferrari, Nicola
Understanding West Nile virus transmission: Mathematical modelling to quantify the most critical parameters to predict infection dynamics Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: OpenDataSet, WNV (West Nile Virus)
@article{nokey,
title = {Understanding West Nile virus transmission: Mathematical modelling to quantify the most critical parameters to predict infection dynamics},
author = {Elisa Fesce and Giovanni Marini and Roberto Rosà and Davide Lelli and Monica Pierangela Cerioli and Mario Chiari and Marco Farioli and Nicola Ferrari},
url = {https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0010252},
doi = {10.1371/journal.pntd.0010252},
year = {2023},
date = {2023-05-01},
urldate = {2023-05-01},
abstract = {Infectious communicable diseases are currently one of the main burdens for human beings and public health. The comprehension of their spread and maintenance is one of the main goals to facilitate their control and eradication, but due to the complexity of their cycles and transmission processes, obtaining this information is often difficult and demanding. The control of vector-borne diseases in particular represents an important and very complex challenge for public health. Mathematical models are suitable tools to investigate disease dynamics and their transmission mechanisms and processes. To build a suitable model that can simulate transmission dynamics, a reliable and precise estimate of parameters for measuring transmission mechanisms is fundamental. We thus propose a sensitivity analysis of four unknown epidemiological parameters (bird recovery rate, mosquito biting rate, avian susceptibility to infection and avian competence to infection) that play a crucial role in driving West Nile virus (WNV) infection to determine which of them have the greatest impact on infection spread. This analysis suggests that the infectious period in birds and mosquito biting rate are the parameters to be prioritised in investigation to increase our ability to model WNV spread.},
keywords = {OpenDataSet, WNV (West Nile Virus)},
pubstate = {published},
tppubtype = {article}
}
Infectious communicable diseases are currently one of the main burdens for human beings and public health. The comprehension of their spread and maintenance is one of the main goals to facilitate their control and eradication, but due to the complexity of their cycles and transmission processes, obtaining this information is often difficult and demanding. The control of vector-borne diseases in particular represents an important and very complex challenge for public health. Mathematical models are suitable tools to investigate disease dynamics and their transmission mechanisms and processes. To build a suitable model that can simulate transmission dynamics, a reliable and precise estimate of parameters for measuring transmission mechanisms is fundamental. We thus propose a sensitivity analysis of four unknown epidemiological parameters (bird recovery rate, mosquito biting rate, avian susceptibility to infection and avian competence to infection) that play a crucial role in driving West Nile virus (WNV) infection to determine which of them have the greatest impact on infection spread. This analysis suggests that the infectious period in birds and mosquito biting rate are the parameters to be prioritised in investigation to increase our ability to model WNV spread.
133.
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.
132.
Vogels, Chantal B. F.; Brackney, Doug E.; Dupuis, Alan P.; Robich, Rebecca M.; Fauver, Joseph R.; Brito, Anderson F.; Williams, Scott C.; Anderson, John F.; Lubelczyk, Charles B.; Lange, Rachel E.; Prusinski, Melissa A.; Kramer, Laura D.; Gangloff-Kaufmann, Jody L.; Goodman, Laura B.; Baele, Guy; Smith, Robert P.; Armstrong, Philip M.; Ciota, Alexander T.; Dellicour, Simon; Grubaugh, Nathan D.
Phylogeographic reconstruction of the emergence and spread of Powassan virus in the northeastern United States Journal Article
In: PNAS, 2023.
Abstract | Links | BibTeX | Tags: OpenDataSet
@article{nokey,
title = {Phylogeographic reconstruction of the emergence and spread of Powassan virus in the northeastern United States},
author = {Chantal B. F. Vogels and Doug E. Brackney and Alan P. Dupuis and Rebecca M. Robich and Joseph R. Fauver and Anderson F. Brito and Scott C. Williams and John F. Anderson and Charles B. Lubelczyk and Rachel E. Lange and Melissa A. Prusinski and Laura D. Kramer and Jody L. Gangloff-Kaufmann and Laura B. Goodman and Guy Baele and Robert P. Smith and Philip M. Armstrong and Alexander T. Ciota and Simon Dellicour and Nathan D. Grubaugh},
url = {https://www.pnas.org/doi/10.1073/pnas.2218012120},
doi = {10.1073/pnas.221801212},
year = {2023},
date = {2023-04-11},
urldate = {2023-04-11},
journal = {PNAS},
abstract = {Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940 and 1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern United States mostly following a south-to-north pattern, with a weighted lineage dispersal velocity of ~3 km/y. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern United States.},
keywords = {OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940 and 1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern United States mostly following a south-to-north pattern, with a weighted lineage dispersal velocity of ~3 km/y. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern United States.
131.
Cataldo, Claudia; Bellenghi, Maria; Masella, Roberta; Busani, Luca
One Health challenges and actions: Integration of gender considerations to reduce risks at the human-animal-environmental interface Journal Article
In: vol. 16, 2023.
Abstract | Links | BibTeX | Tags:
@article{nokey_43,
title = {One Health challenges and actions: Integration of gender considerations to reduce risks at the human-animal-environmental interface},
author = {Claudia Cataldo and Maria Bellenghi and Roberta Masella and Luca Busani},
url = {https://www.sciencedirect.com/science/article/pii/S2352771423000502?via%3Dihub},
doi = {10.1016/j.onehlt.2023.100530},
year = {2023},
date = {2023-04-03},
volume = {16},
abstract = {The human-animal-environment interface is where the emergence of new infectious diseases can occur as a result of many complex reasons, including its alteration due to intensive farming and agriculture, increased human encroachment into wildlife habitats, international travel networks, and urbanization. The One Health approach to zoonoses is a holistic approach that considers environmental sustainability, animal health, and human health together. Gender-specific social and domestic roles can modulate (increase or decrease) an individual's risk of exposure to various hazards, including infectious diseases and zoonoses. The two scenarios presented here, one on avian influenza and the other on leptospirosis, clearly highlight the influence of gender, demonstrating that women's roles at the human-animal-environment interface are not the same as men's.
Integrating the gender aspect into cross-sectoral interventions defined according to the One Health perspective could help reduce the risks of exposure to infections for humans and animals and the possible consequent economic losses. We suggest supplementing the One Health perspective with a gender analysis to study the influence of social norms, activities and risk behavior on exposure to infections, chemical pollution and the consequences of climate change.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The human-animal-environment interface is where the emergence of new infectious diseases can occur as a result of many complex reasons, including its alteration due to intensive farming and agriculture, increased human encroachment into wildlife habitats, international travel networks, and urbanization. The One Health approach to zoonoses is a holistic approach that considers environmental sustainability, animal health, and human health together. Gender-specific social and domestic roles can modulate (increase or decrease) an individual's risk of exposure to various hazards, including infectious diseases and zoonoses. The two scenarios presented here, one on avian influenza and the other on leptospirosis, clearly highlight the influence of gender, demonstrating that women's roles at the human-animal-environment interface are not the same as men's.
Integrating the gender aspect into cross-sectoral interventions defined according to the One Health perspective could help reduce the risks of exposure to infections for humans and animals and the possible consequent economic losses. We suggest supplementing the One Health perspective with a gender analysis to study the influence of social norms, activities and risk behavior on exposure to infections, chemical pollution and the consequences of climate change.
Integrating the gender aspect into cross-sectoral interventions defined according to the One Health perspective could help reduce the risks of exposure to infections for humans and animals and the possible consequent economic losses. We suggest supplementing the One Health perspective with a gender analysis to study the influence of social norms, activities and risk behavior on exposure to infections, chemical pollution and the consequences of climate change.
130.
Arinik, Nejat; Interdonato, Roberto; Roche, Mathieu; Teisseire, Maguelonne
An Evaluation Framework For Comparing Epidemic Intelligence Systems Journal Article
In: IEEE Xplore, 2023.
Abstract | Links | BibTeX | Tags: OpenDataSet
@article{nokey,
title = {An Evaluation Framework For Comparing Epidemic Intelligence Systems},
author = {Nejat Arinik and Roberto Interdonato and Mathieu Roche and Maguelonne Teisseire
},
url = {https://ieeexplore.ieee.org/document/10082884},
doi = {10.1109/ACCESS.2023.3262462},
year = {2023},
date = {2023-03-27},
urldate = {2023-03-27},
journal = {IEEE Xplore},
abstract = {In the context of Epidemic Intelligence, many Event-Based Surveillance (EBS) systems have been proposed in the literature to promote the early identification and characterization of potential health threats from online sources of any nature. Each EBS system has its own surveillance definitions and priorities, therefore this makes the task of selecting the most appropriate EBS system for a given situation a challenge for end-users. In this work, we propose a new evaluation framework to address this issue. It first transforms the raw input epidemiological event data into a set of normalized events with multi-granularity, then conducts a descriptive retrospective analysis based on four evaluation objectives: spatial, temporal, thematic and source analysis. We illustrate its relevance by applying it to an Avian Influenza dataset collected by a selection of EBS systems, and show how our framework allows identifying their strengths and drawbacks in terms of epidemic surveillance.},
keywords = {OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
In the context of Epidemic Intelligence, many Event-Based Surveillance (EBS) systems have been proposed in the literature to promote the early identification and characterization of potential health threats from online sources of any nature. Each EBS system has its own surveillance definitions and priorities, therefore this makes the task of selecting the most appropriate EBS system for a given situation a challenge for end-users. In this work, we propose a new evaluation framework to address this issue. It first transforms the raw input epidemiological event data into a set of normalized events with multi-granularity, then conducts a descriptive retrospective analysis based on four evaluation objectives: spatial, temporal, thematic and source analysis. We illustrate its relevance by applying it to an Avian Influenza dataset collected by a selection of EBS systems, and show how our framework allows identifying their strengths and drawbacks in terms of epidemic surveillance.
129.
Viau, Laëtitia; Sallaberry, Arnaud; Rodriguez, Nancy; Girres, Jean-François; Poncelet, Pascal
Polygon vector map distortion for increasing the readability ofone-to-many flow maps Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: OpenDataSet
@article{nokey,
title = {Polygon vector map distortion for increasing the readability ofone-to-many flow maps},
author = {Laëtitia Viau and Arnaud Sallaberry and Nancy Rodriguez and Jean-François Girres and Pascal Poncelet
},
url = {https://www.tandfonline.com/doi/full/10.1080/13658816.2023.2190374},
doi = {10.1080/13658816.2023.2190374},
year = {2023},
date = {2023-03-22},
urldate = {2023-03-22},
abstract = {Cartographers have long been interested in the representation of various movements such as migration, commercial exchanges and transportation. There are several techniques for visualizing this information; this paper focuses on flow mapping. A flow map shows a set of movements through line symbols connecting an origin to a destination. Each link is associated with a value that corresponds to the volume of the movement. However, once data reach a certain volume, the maps quickly become cluttered and can be difficult to read and understand. Moreover, the values of the movements must be correctly represented to avoid inducing biased interpretations. The objective of this paper is to create flow maps displaying flows of highly variable thicknesses so that the associated values are correctly represented. The technique used to create the flow paths does not create crossings between flows. In order to remove any visual clutter, such as overlaps between flows and geographic features, some areas of the map are distorted. In other words, our method of map distortion adapts the polygon vector base map to the flows, the central information of the visualization, and not the other way around.
},
keywords = {OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Cartographers have long been interested in the representation of various movements such as migration, commercial exchanges and transportation. There are several techniques for visualizing this information; this paper focuses on flow mapping. A flow map shows a set of movements through line symbols connecting an origin to a destination. Each link is associated with a value that corresponds to the volume of the movement. However, once data reach a certain volume, the maps quickly become cluttered and can be difficult to read and understand. Moreover, the values of the movements must be correctly represented to avoid inducing biased interpretations. The objective of this paper is to create flow maps displaying flows of highly variable thicknesses so that the associated values are correctly represented. The technique used to create the flow paths does not create crossings between flows. In order to remove any visual clutter, such as overlaps between flows and geographic features, some areas of the map are distorted. In other words, our method of map distortion adapts the polygon vector base map to the flows, the central information of the visualization, and not the other way around.
128.
Marini, Giovanni; Arnoldi, Daniele; Rizzoli, Annapaola; Tagliapietra, Valentina
Estimating rodent population abundance using early climatic predictors Journal Article
In: European Journal of Wildlife Research, vol. 69, no. 2, pp. 36, 2023.
Links | BibTeX | Tags: OpenDataSet, TBE (Tick Borne Encephalitis)
@article{nokey,
title = {Estimating rodent population abundance using early climatic predictors},
author = {Giovanni Marini and Daniele Arnoldi and Annapaola Rizzoli and Valentina Tagliapietra},
url = {https://link.springer.com/article/10.1007/s10344-023-01666-2#citeas},
doi = {10.1007/s10344-023-01666-2},
year = {2023},
date = {2023-03-17},
urldate = {2023-03-17},
journal = {European Journal of Wildlife Research},
volume = {69},
number = {2},
pages = {36},
keywords = {OpenDataSet, TBE (Tick Borne Encephalitis)},
pubstate = {published},
tppubtype = {article}
}
127.
Messina, Jane Paula; Wint, William G R
The spatial distribution of Crimean Congo haemorrhagic fever in Europe and neighbouring areas Technical Report
2023.
Abstract | Links | BibTeX | Tags: CCHF (Crimean Congo haemorrhagic fever virus), OpenDataSet
@techreport{nokey,
title = {The spatial distribution of Crimean Congo haemorrhagic fever in Europe and neighbouring areas},
author = {Jane Paula Messina and William G R Wint},
url = {https://mood-h2020.eu/wp-content/uploads/2024/01/MOOD078_TRP-20230222-161_clearancev4April2023clean.pdf},
year = {2023},
date = {2023-03-01},
urldate = {2023-03-01},
abstract = {This report was commissioned by the European Centre for Disease Prevention and Control (ECDC) to
assess the spatial distributions of Crimean-Congo haemorrhagic fever (CCHF) in Europe and neighbouring
areas under specific contract No 4 ECD.13254 ID.13285 implementing inter-agency framework contract
for services No ECDC/2019/020. The European Union Horizon 2020 MOOD Project N° 874850 (https://
https://mood-h2020.eu/) provided driver covariates and vector distributions and has catalogued this
document as MOOD078. The report was managed by Olivier Briet (ECDC)},
keywords = {CCHF (Crimean Congo haemorrhagic fever virus), OpenDataSet},
pubstate = {published},
tppubtype = {techreport}
}
This report was commissioned by the European Centre for Disease Prevention and Control (ECDC) to
assess the spatial distributions of Crimean-Congo haemorrhagic fever (CCHF) in Europe and neighbouring
areas under specific contract No 4 ECD.13254 ID.13285 implementing inter-agency framework contract
for services No ECDC/2019/020. The European Union Horizon 2020 MOOD Project N° 874850 (https://
https://mood-h2020.eu/) provided driver covariates and vector distributions and has catalogued this
document as MOOD078. The report was managed by Olivier Briet (ECDC)
assess the spatial distributions of Crimean-Congo haemorrhagic fever (CCHF) in Europe and neighbouring
areas under specific contract No 4 ECD.13254 ID.13285 implementing inter-agency framework contract
for services No ECDC/2019/020. The European Union Horizon 2020 MOOD Project N° 874850 (https://
https://mood-h2020.eu/) provided driver covariates and vector distributions and has catalogued this
document as MOOD078. The report was managed by Olivier Briet (ECDC)
126.
Mendes, Goncalo Azevedo; Martins, Bruno
Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers Journal Article
In: arXiv, 2023.
Abstract | Links | BibTeX | Tags:
@article{nokey,
title = {Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers},
author = {Goncalo Azevedo Mendes and Bruno Martins},
url = {https://arxiv.org/abs/2302.14021},
doi = {https://doi.org/10.48550/arXiv.2302.14021},
year = {2023},
date = {2023-02-27},
journal = {arXiv},
abstract = {The analysis of emotions expressed in text has numerous applications. In contrast to categorical analysis, focused on classifying emotions according to a pre-defined set of common classes, dimensional approaches can offer a more nuanced way to distinguish between different emotions. Still, dimensional methods have been less studied in the literature. Considering a valence-arousal dimensional space, this work assesses the use of pre-trained Transformers to predict these two dimensions on a continuous scale, with input texts from multiple languages and domains. We specifically combined multiple annotated datasets from previous studies, corresponding to either emotional lexica or short text documents, and evaluated models of multiple sizes and trained under different settings. Our results show that model size can have a significant impact on the quality of predictions, and that by fine-tuning a large model we can confidently predict valence and arousal in multiple languages. We make available the code, models, and supporting data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The analysis of emotions expressed in text has numerous applications. In contrast to categorical analysis, focused on classifying emotions according to a pre-defined set of common classes, dimensional approaches can offer a more nuanced way to distinguish between different emotions. Still, dimensional methods have been less studied in the literature. Considering a valence-arousal dimensional space, this work assesses the use of pre-trained Transformers to predict these two dimensions on a continuous scale, with input texts from multiple languages and domains. We specifically combined multiple annotated datasets from previous studies, corresponding to either emotional lexica or short text documents, and evaluated models of multiple sizes and trained under different settings. Our results show that model size can have a significant impact on the quality of predictions, and that by fine-tuning a large model we can confidently predict valence and arousal in multiple languages. We make available the code, models, and supporting data.
125.
Arınık, Nejat; Bortel, Wim Van; Boudoua, Bahdja; Busani, Luca; Decoupes, Rémy; Interdonato, Roberto; Kafando, Rodrique; van Kleef, Esther; Roche, Mathieu; Syed, Mehtab Alam; Teisseire, Maguelonne
An annotated dataset for event-based surveillance of antimicrobial resistance Journal Article
In: ScienceDirect, 2023.
Abstract | Links | BibTeX | Tags: AMR (Antimicrobial Resistance), OpenDataSet, Text mining
@article{nokey,
title = {An annotated dataset for event-based surveillance of antimicrobial resistance},
author = {Nejat Arınık and Wim Van Bortel and Bahdja Boudoua and Luca Busani and Rémy Decoupes and Roberto Interdonato and Rodrique Kafando and Esther van Kleef and Mathieu Roche and Mehtab Alam Syed and Maguelonne Teisseire
},
url = {https://www.sciencedirect.com/science/article/pii/S2352340922010733?via%3Dihub},
doi = {10.1016/j.dib.2022.108870},
year = {2023},
date = {2023-02-08},
urldate = {2023-02-08},
journal = {ScienceDirect},
abstract = {This paper presents an annotated dataset used in the MOOD Antimicrobial Resistance (AMR) hackathon, hosted in Montpellier, June 2022. The collected data concerns unstructured data from news items, scientific publications and national or international reports, collected from four event-based surveillance (EBS) Systems, i.e. ProMED, PADI-web, HealthMap and MedISys. Data was annotated by relevance for epidemic intelligence (EI) purposes with the help of AMR experts and an annotation guideline. Extracted data were intended to include relevant events on the emergence and spread of AMR such as reports on AMR trends, discovery of new drug-bug resistances, or new AMR genes in human, animal or environmental reservoirs. This dataset can be used to train or evaluate classification approaches to automatically identify written text on AMR events across the different reservoirs and sectors of One Health (i.e. human, animal, food, environmental sources, such as soil and waste water) in unstructured data (e.g. news, tweets) and classify these events by relevance for EI purposes.
},
keywords = {AMR (Antimicrobial Resistance), OpenDataSet, Text mining},
pubstate = {published},
tppubtype = {article}
}
This paper presents an annotated dataset used in the MOOD Antimicrobial Resistance (AMR) hackathon, hosted in Montpellier, June 2022. The collected data concerns unstructured data from news items, scientific publications and national or international reports, collected from four event-based surveillance (EBS) Systems, i.e. ProMED, PADI-web, HealthMap and MedISys. Data was annotated by relevance for epidemic intelligence (EI) purposes with the help of AMR experts and an annotation guideline. Extracted data were intended to include relevant events on the emergence and spread of AMR such as reports on AMR trends, discovery of new drug-bug resistances, or new AMR genes in human, animal or environmental reservoirs. This dataset can be used to train or evaluate classification approaches to automatically identify written text on AMR events across the different reservoirs and sectors of One Health (i.e. human, animal, food, environmental sources, such as soil and waste water) in unstructured data (e.g. news, tweets) and classify these events by relevance for EI purposes.
124.
Cataldo, Claudia; Masella, Roberta; Busani, Luca
Gender gap reduction and the one health benefits Journal Article
In: One Health, vol. 16, pp. 100496, 2023, ISSN: 2352-7714.
Abstract | Links | BibTeX | Tags: OpenDataSet
@article{nokey,
title = {Gender gap reduction and the one health benefits},
author = {Claudia Cataldo and Roberta Masella and Luca Busani},
url = {https://www.sciencedirect.com/science/article/pii/S2352771423000162},
doi = {10.1016/j.onehlt.2023.100496},
issn = {2352-7714},
year = {2023},
date = {2023-02-07},
urldate = {2023-02-07},
journal = {One Health},
volume = {16},
pages = {100496},
abstract = {Several factors including gender, age groups, cultures and social conditions may affect significantly the risk of diseases and their clinical evolution. Unfortunately, little research has been carried out on these aspects and, consequently few guidelines or interventions have been implemented. In particular, gender is considered a main determinant of inequalities in living conditions, access to health services and, thus, in health protection.
Focusing on the gender gap, we propose an ecological approach to find relationships between quantitative indicators of the gender gap dimension, the environmental performance index and the life expectancy at birth as summary of human health index in 155 countries. We speculated on the consequences of wider gender gaps to the population and environmental health. We further explore these relationships considering gender gap and environmental aspect subindexes, to identify determinants that should be addressed to maximize the One Health effect. We found that the gender gap in educational attainment followed by the political empowerment were strongly correlated with life expectancy, environmental health, and ecosystem vitality.
Addressing gender issues, particularly the education attainment and political empowerment, can provide positive impact beyond the social dimension and the population health, and gender should be component of the One Health approach. We recommend gender targeted interventions that integrate these aspects into One Health national policies.},
keywords = {OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
Several factors including gender, age groups, cultures and social conditions may affect significantly the risk of diseases and their clinical evolution. Unfortunately, little research has been carried out on these aspects and, consequently few guidelines or interventions have been implemented. In particular, gender is considered a main determinant of inequalities in living conditions, access to health services and, thus, in health protection.
Focusing on the gender gap, we propose an ecological approach to find relationships between quantitative indicators of the gender gap dimension, the environmental performance index and the life expectancy at birth as summary of human health index in 155 countries. We speculated on the consequences of wider gender gaps to the population and environmental health. We further explore these relationships considering gender gap and environmental aspect subindexes, to identify determinants that should be addressed to maximize the One Health effect. We found that the gender gap in educational attainment followed by the political empowerment were strongly correlated with life expectancy, environmental health, and ecosystem vitality.
Addressing gender issues, particularly the education attainment and political empowerment, can provide positive impact beyond the social dimension and the population health, and gender should be component of the One Health approach. We recommend gender targeted interventions that integrate these aspects into One Health national policies.
Focusing on the gender gap, we propose an ecological approach to find relationships between quantitative indicators of the gender gap dimension, the environmental performance index and the life expectancy at birth as summary of human health index in 155 countries. We speculated on the consequences of wider gender gaps to the population and environmental health. We further explore these relationships considering gender gap and environmental aspect subindexes, to identify determinants that should be addressed to maximize the One Health effect. We found that the gender gap in educational attainment followed by the political empowerment were strongly correlated with life expectancy, environmental health, and ecosystem vitality.
Addressing gender issues, particularly the education attainment and political empowerment, can provide positive impact beyond the social dimension and the population health, and gender should be component of the One Health approach. We recommend gender targeted interventions that integrate these aspects into One Health national policies.