MOOD publications

@article{@article{SCHAEFFER2022108317,,

title = {Labeled entities from social media data related to avian influenza disease},

author = {Schaeffer, Camille and Interdonato, Roberto and Lancelot, Renaud and Roche, Mathieu and Teisseire, Maguelonne},

url = {https://www.sciencedirect.com/science/article/pii/S2352340922005194},

doi = {https://doi.org/10.1016/j.dib.2022.108317},

issn = {2352-3409},

year  = {2022},

date = {2022-08-01},

urldate = {2022-08-01},

journal = {Data in Brief},

volume = {43},

pages = {108317},

abstract = {This dataset is composed by spatial (e.g. location) and thematic (e.g. diseases, symptoms, virus) entities concerning avian influenza in social media (textual) data in English. It was created from three corpora: the first one includes 10 transcriptions of YouTube videos and 70 tweets manually annotated. The second corpus is composed by the same textual data but automatically annotated with Named Entity Recognition (NER) tools. These two corpora have been built to evaluate NER tools and apply them to a bigger corpus. The third corpus is composed of 100 YouTube transcriptions automatically annotated with NER tools. The aim of the annotation task is to recognize spatial information such as the names of the cities and epidemiological information such as the names of the diseases. An annotation guideline is provided in order to ensure a unified annotation and to help the annotators. This dataset can be used to train or evaluate Natural Language Processing (NLP) approaches such as specialized entity recognition.},

keywords = {avian influenza, epidemiology, named entity recognition, OpenDataSet, social networks, Text mining},

pubstate = {forthcoming},

tppubtype = {article}

}

@article{@article{bernardsystematic,

title = {Systematic Review on Crimean–Congo Hemorrhagic Fever Enzootic Cycle and Factors Favoring Virus Transmission: Special Focus on France, an Apparently Free-Disease Area in Europe},

author = {Bernard, Celia and Holzmuller, Philippe and Bah, Madiou Thierno and Bastien, Matthieu and Combes, Benoit and Jori, Ferran and Grosbois, Vladimir and Vial, Laurence},

url = {https://www.frontiersin.org/articles/10.3389/fvets.2022.932304/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Veterinary_Science&id=932304},

doi = {https://doi.org/10.3389/fvets.2022.932304},

year  = {2022},

date = {2022-07-19},

journal = {Frontiers in Veterinary Science},

pages = {973},

abstract = {Crimean–Congo hemorrhagic fever (CCHF) is a viral zoonotic disease resulting in hemorrhagic syndrome in humans. Its causative agent is naturally transmitted by ticks to non-human vertebrate hosts within an enzootic sylvatic cycle. Ticks are considered biological vectors, as well as reservoirs for CCHF virus (CCHFV), as they are able to maintain the virus for several months or even years and to transmit CCHFV to other ticks. Although animals are not symptomatic, some of them can sufficiently replicate the virus, becoming a source of infection for ticks as well as humans through direct contact with contaminated body fluids. The recent emergence of CCHF in Spain indicates that tick–human interaction rates promoting virus transmission are changing and lead to the emergence of CCHF. In other European countries such as France, the presence of one of its main tick vectors and the detection of antibodies targeting CCHFV in animals, at least in Corsica and in the absence of human cases, suggest that CCHFV could be spreading silently. In this review, we study the CCHFV epidemiological cycle as hypothesized in the French local context and select the most likely parameters that may influence virus transmission among tick vectors and non-human vertebrate hosts. For this, a total of 1,035 articles dating from 1957 to 2021 were selected for data extraction. This study made it possible to identify the tick species that seem to be the best candidate vectors of CCHFV in France, but also to highlight the importance of the abundance and composition of local host communities on vectors' infection prevalence. Regarding the presumed transmission cycle involving Hyalomma marginatum, as it might exist in France, at least in Corsica, it is assumed that tick vectors are still weakly infected and the probability of disease emergence in humans remains low. The likelihood of factors that may modify this equilibrium is discussed.},

keywords = {CCHF, France, hyalomma tick vectors, ticks, vector},

pubstate = {published},

tppubtype = {article}

}

@article{@article{contreras2022impact,

title = {Impact of contact data resolution on the evaluation of interventions in mathematical models of infectious diseases},

author = {Contreras, Diego Andrés and Colosi, Elisabetta and Bassignana, Giulia and Colizza, Vittoria and Barrat, Alain},

url = {https://doi.org/10.1098/rsif.2022.0164},

doi = {10.1098/rsif.2022.0164},

year  = {2022},

date = {2022-06-22},

urldate = {2022-06-22},

journal = {Journal of the Royal Society Interface},

volume = {19},

number = {191},

pages = {20220164},

abstract = {Computational models offer a unique setting to test strategies to mitigate the spread of infectious diseases, providing useful insights to applied public health. To be actionable, models need to be informed by data, which can be available at different levels of detail. While high-resolution data describing contacts between individuals are increasingly available, data gathering remains challenging, especially during a health emergency. Many models thus use synthetic data or coarse information to evaluate intervention protocols. Here, we evaluate how the representation of contact data might affect the impact of various strategies in models, in the realm of COVID-19 transmission in educational and work contexts. Starting from high-resolution contact data, we use detailed to coarse data representations to inform a model of SARS-CoV-2 transmission and simulate different mitigation strategies. We find that coarse data representations estimate a lower risk of superspreading events. However, the rankings of protocols according to their efficiency or cost remain coherent across representations, ensuring the consistency of model findings to inform public health advice. Caution should be taken, however, on the quantitative estimations of those benefits and costs triggering the adoption of protocols, as these may depend on data representation.},

keywords = {Computational models, COVID-19, infectious diseases, OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@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 = {razo, Diana and Vincenti-Gonzalez, Maria F. and van Loenhout, Joris A. F. and Hubin, Pierre and Vandromme, Mathil and Maes, Piet and Taquet, Maxime and Van Weyenbergh, Johan and Catteau, Lucy and Dellicour, Simon},

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, hospitalisation surveillance, risk ratio, SARS-CoV-2, vaccination impact},

pubstate = {published},

tppubtype = {article}

}

@article{@article{10.7554/eLife.71703,

title = {Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: A retrospective genomic study},

author = {Agoti, Charles N and Ochola-Oyier, Lynette Isabella and Dellicour, Simon and Mohammed, Khadija Said and Lambisia, Arnold W and de Laurent, Zaydah R and Morobe, John M and Mburu, Maureen W and Omuoyo, Donwilliams O and Ongera, Edidah M and Ndwiga, Leonard and Maitha, Eric and Kitole, Benson and Suleiman, Thani and Mwakinangu, Mohamed and Nyambu, John K and Otieno, John and Salim, Barke and Musyoki, Jennifer and Murunga, Nickson and Otieno, Edward and Kiiru, John N and Kasera, Kadondi and Amoth, Patrick and Mwangangi, Mercy and Aman, Rashid and Kinyanjui, Samson and Warimwe, George and Phan, My and Agweyu, Ambrose and Cotten, Matthew and Barasa, Edwine and Tsofa, Benjamin and Nokes, D James and Bejon, Philip and Githinji, George},

editor = {Grabowski, Mary Kate and van der Meer, Jos W},},

url = {https://doi.org/10.7554/eLife.71703},

doi = {10.7554/eLife.71703},

issn = {2050-084X},

year  = {2022},

date = {2022-06-14},

urldate = {2022-06-14},

journal = {eLife},

volume = {11},

pages = {e71703},

abstract = {Detailed understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. textbf{Methods:} Here, we analysed 1139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River, and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction, and virus dispersal between counties was estimated using discrete phylogeographic analysis. textbf{Results:} During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; 9 of which occurred in both waves and 4 seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1, and N.8). Most of the sequenced infections belonged to lineage B.1 (n = 723, 63%), which predominated in both Wave 1 (73%, followed by lineages N.8 [6%] and B.1.1 [6%]) and Wave 2 (56%, followed by lineages B.1.549 [21%] and B.1.530 [5%]). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many Coronavirus Disease 2019 (COVID-19) government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. textbf{Conclusions:} Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission. textbf{Funding:} This work was funded by The Wellcome (grant numbers: 220985, 203077/Z/16/Z, 220977/Z/20/Z, and 222574/Z/21/Z) and the National Institute for Health and Care Research (NIHR), project references: 17/63/and 16/136/33 using UK Aid from the UK government to support global health research, The UK Foreign, Commonwealth and Development Office. The views expressed in this publication are those of the author(s) and not necessarily those of the funding agencies.},},

keywords = {Africa, COVID-19, epidemiology, genome, transmission},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories},

author = {Ge, Yong; Zhang, Wen-Bin; Wu, Xilin; W Ruktanonchai, Corrine; Liu, Haiyan; Wang, Jianghao; Song, Yongze; Liu, Mengxiao; Yan, Wei; Yang, Juan; Cleary, Eimear; H Qader, Sarchil; Atuhaire, Fatumah; W Ruktanonchai, Nick; J Tatem, Andrew; Lai, Shengjie},

url = {https://www.nature.com/articles/s41467-022-30897-1#citeas},

doi = {10.1038/s41467-022-30897-1},

year  = {2022},

date = {2022-06-03},

urldate = {2022-06-03},

journal = {Nature Commun},

volume = {13},

number = {3106},

abstract = {Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants.},

keywords = {Applied mathematics, epidemiology, infectious diseases},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A systematic review of environmental factors related to WNV circulation in European and Mediterranean countries},

author = {Christine Giesen and Zaida Herrador and Beatriz Fernandez-Martinez and Jordi Figuerola and Laura Gangoso and Ana Vazquez and Diana Gómez-Barroso},

url = {https://www.sciencedirect.com/science/article/pii/S2352771422001100},

doi = {10.1016/j.onehlt.2022.100478},

issn = {2352-7714},

year  = {2022},

date = {2022-06-01},

journal = {One Health},

volume = {16},

pages = {100478},

abstract = {Introduction/objective

West Nile virus (WNV) is one of the most widely distributed flaviviruses worldwide. It is considered an endemic and emerging pathogen in different areas of the Europe and Mediterranean countries (MR). Mosquitoes of the genus Culex spp. are the main vectors, and birds its main vertebrate hosts. It can occasionally infect mammals, including humans. Different environmental factors can influence its distribution and transmission through its effects on vector or host populations. Our objective was to determine environmental factors associated with changes in vector distribution and WNV transmission in Europe and MR.

Material & methods

Systematic peer review of articles published between 2000 and 2020. We selected studies on WNV, and its vectors carried out in Europe and MR. The search included terms referring to climatic and environmental factors.

Results

We included 65 studies, of which 21 (32%) were conducted in Italy. Culex spp. was studied in 26 papers (40%), humans in 19 papers (29%) and host animals (mainly horses) in 16 papers (25%), whereas bird reservoirs were addressed in 5 studies (8%). A significant positive relationship was observed between changes in temperature and precipitation patterns and the epidemiology of WNV, although contrasting results were found among studies. Other factors positively related to WNV dynamics were the normalized difference vegetation index (NDVI] and expansion of anthropized habitats.

Conclusion

The epidemiology of WNV seems to be related to climatic factors that are changing globally due to ongoing climate change. Unfortunately, the complete zoonotic cycle was not analyzed in most papers, making it difficult to determine the independent impact of environment on the different components of the transmission cycle. Given the current expansion and endemicity of WNV in the area, it is important to adopt holistic approaches to understand WNV epidemiology and to improve WNV surveillance and control.},

keywords = {Climate, culex, Emerging infectious diseases, Europe, Mediterranean, West Nile Virus},

pubstate = {published},

tppubtype = {article}

}

@article{@article{10.1093/ve/veac041,

title = {Accommodating sampling location uncertainty in continuous phylogeography},

author = {Dellicour, Simon and Lemey, Philippe and Suchard, Marc A and Gilbert, Marius and Baele, Guy},

url = {https://academic.oup.com/ve/article/8/1/veac041/6588218},

doi = {10.1093/ve/veac041},

issn = {2057-1577},

year  = {2022},

date = {2022-05-18},

urldate = {2022-05-18},

journal = {Virus Evolution},

volume = {8},

number = {1},

issue = {1},

abstract = {Phylogeographic inference of the dispersal history of viral lineages offers key opportunities to tackle epidemiological questions about the spread of fast-evolving pathogens across human, animal and plant populations. In continuous space, i.e. when locations are specified by longitude and latitude, these reconstructions are however often limited by the availability or accessibility of precise sampling locations required for such spatially explicit analyses. We here review the different approaches that can be considered when genomic sequences are associated with a geographic area of sampling instead of precise coordinates. In particular, we describe and compare the approaches to define homogeneous and heterogeneous prior ranges of sampling coordinates.},

keywords = {Bayesian inference, BEAST, continuous phylogeography, host species, sampling precision, virus},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = { Meteorological and climatic variables predict the phenology of Ixodes ricinus nymph activity in France, accounting for habitat heterogeneity.},

author = {Phrutsamon Wongnak and Séverine Bord and Maude Jacquot and Albert Agoulon and Frédéric Beugnet and Laure Bournez and Nicolas Cèbe and Adélie Chevalier and Jean-François Cosson and Naïma Dambrine and Thierry Hoch and Frédéric Huard and Nathalie Korboulewsky and Isabelle Lebert and Aurélien Madouasse and Anders Mårell and Sara Moutailler and Olivier Plantard and Thomas Pollet and Valérie Poux and Magalie René-Martellet and Muriel Vayssier-Taussat and Hélène Verheyden and Gwenaël Vourc’h and Karine Chalvet-Monfray},

url = {https://www.nature.com/articles/s41598-022-11479-z},

doi = {https://doi.org/10.1038/s41598-022-11479-z},

year  = {2022},

date = {2022-05-12},

urldate = {2022-05-12},

journal = {Nature Scientific Reports},

volume = {7833},

issue = {12},

abstract = {Ixodes ricinus ticks (Acari: Ixodidae) are the most important vector for Lyme borreliosis in Europe. As climate change might affect their distributions and activities, this study aimed to determine the effects of environmental factors, i.e., meteorological, bioclimatic, and habitat characteristics on host-seeking (questing) activity of I. ricinus nymphs, an important stage in disease transmissions, across diverse climatic types in France over 8 years. Questing activity was observed using a repeated removal sampling with a cloth-dragging technique in 11 sampling sites from 7 tick observatories from 2014 to 2021 at approximately 1-month intervals, involving 631 sampling campaigns. Three phenological patterns were observed, potentially following a climatic gradient. The mixed-effects negative binomial regression revealed that observed nymph counts were driven by different interval-average meteorological variables, including 1-month moving average temperature, previous 3-to-6-month moving average temperature, and 6-month moving average minimum relative humidity. The interaction effects indicated that the phenology in colder climates peaked differently from that of warmer climates. Also, land cover characteristics that support the highest baseline abundance were moderate forest fragmentation with transition borders with agricultural areas. Finally, our model could potentially be used to predict seasonal human-tick exposure risks in France that could contribute to mitigating Lyme borreliosis risk.},

keywords = {Climate, climate change, disease ecology, France, infectious diseases, ixodes, ticks, vector},

pubstate = {published},

tppubtype = {article}

}

@article{@article{colosi2022screening,,

title = {Screening and vaccination against COVID-19 to minimise school closure: a modelling study},

author = {Colosi, Elisabetta and Bassignana, Giulia and Contreras, Diego Andrés and Poirier, Canelle and Boëlle, Pierre-Yves and Cauchemez, Simon and Yazdanpanah, Yazdan and Lina, Bruno and Fontanet, Arnaud and Barrat, Alain and others},

url = {https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(22)00138-4/fulltext},

doi = {https://doi.org/10.1016/S1473-3099(22)00138-4},

year  = {2022},

date = {2022-04-01},

urldate = {2022-04-01},

journal = {The Lancet Infectious Diseases},

volume = {2},

issue = {7},

pages = {Pages 977-989},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{@article{COLOSI2022101047,

title = {Modelling COVID-19 in school settings to evaluate prevention and control protocols},

author = {Elisabetta Colosi and Giulia Bassignana and Alain Barrat and Vittoria Colizza},

url = {https://www.sciencedirect.com/science/article/pii/S2352556822000285},

doi = {https://doi.org/10.1016/j.accpm.2022.101047},

issn = {2352-5568},

year  = {2022},

date = {2022-04-01},

urldate = {2022-04-01},

journal = {Anaesthesia Critical Care & Pain Medicine},

volume = {41},

number = {2},

pages = {101047},

keywords = {iterative screening, modelling, Non-pharmaceutical interventions, SARS-CoV-2, school},

pubstate = {published},

tppubtype = {article}

}

@article{@article{VALENTIN2022,

title = {Fusion of spatiotemporal and thematic features of textual data for animal disease surveillance},

author = {Sarah Valentin and Renaud Lancelot and Mathieu Roche},

url = {https://www.sciencedirect.com/science/article/pii/S2214317322000312},

doi = {https://doi.org/10.1016/j.inpa.2022.03.004},

issn = {2214-3173},

year  = {2022},

date = {2022-03-28},

journal = {Information Processing in Agriculture},

abstract = {Several internet-based surveillance systems have been created to monitor the web for animal health surveillance. These systems collect a large amount of news dealing with outbreaks related to animal diseases. Automatically identifying news articles that describe the same outbreak event is a key step to quickly detect relevant epidemiological information while alleviating manual curation of news content. This paper addresses the task of retrieving news articles that are related in epidemiological terms. We tackle this issue using text mining and feature fusion methods. The main objective of this paper is to identify a textual representation in which two articles that share the same epidemiological content are close. We compared two types of representations (i.e., features) to represent the documents: (i) morphosyntactic features (i.e., selection and transformation of all terms from the news, based on classical textual processing steps) and (ii) lexicosemantic features (i.e., selection, transformation and fusion of epidemiological terms including diseases, hosts, locations and dates). We compared two types of term weighing (i.e., Boolean and TF-IDF) for both representations. To combine and transform lexicosemantic features, we compared two data fusion techniques (i.e., early fusion and late fusion) and the effect of features generalisation, while evaluating the relative importance of each type of feature. We conducted our analysis using a corpus composed of a subset of news articles in English related to animal disease outbreaks. Our results showed that the combination of relevant lexicosemantic (epidemiological) features using fusion methods improves classical morphosyntactic representation in the context of disease-related news retrieval. The lexicosemantic representation based on TF-IDF and feature generalisation (F-measure = 0.92, r-precision = 0.58) outperformed the morphosyntactic representation (F-measure = 0.89, r-precision = 0.45), while reducing the features space. Converting the features into lower granular features (i.e., generalisation) contributed to improving the results of the lexicosemantic representation. Our results showed no difference between the early and late fusion approaches. Temporal features performed poorly on their own. Conversely, spatial features were the most discriminative features, highlighting the need for robust methods for spatial entity extraction, disambiguation and representation in internet-based surveillance systems.},

keywords = {Animal disease surveillance, fusion, ranking, Text mining},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Agent-based modelling of reactive vaccination of workplaces and schools against COVID-19},

author = {Benjamin Faucher and Rania Assab and Jonathan Roux and Daniel Levy-Bruhl and Cécile Tran Kiem and Simon Cauchemez and Laura Zanetti and Vittoria Colizza and Pierre-Yves Boëlle and Chiara Poletto},

url = {https://www.nature.com/articles/s41467-022-29015-y#Abs1},

doi = {10.1038/s41467-022-29015-y},

year  = {2022},

date = {2022-03-17},

urldate = {2022-03-17},

journal = {Nature Communications},

volume = {13},

number = {1414},

abstract = {With vaccination against COVID-19 stalled in some countries, increasing vaccine accessibility and distribution could help keep transmission under control. Here, we study the impact of reactive vaccination targeting schools and workplaces where cases are detected, with an agent-based model accounting for COVID-19 natural history, vaccine characteristics, demographics, behavioural changes and social distancing. In most scenarios, reactive vaccination leads to a higher reduction in cases compared with non-reactive strategies using the same number of doses. The reactive strategy could however be less effective than a moderate/high pace mass vaccination program if initial vaccination coverage is high or disease incidence is low, because few people would be vaccinated around each case. In case of flare-ups, reactive vaccination could better mitigate spread if it is implemented quickly, is supported by enhanced test-trace-isolate and triggers an increased vaccine uptake. These results provide key information to plan an adaptive vaccination rollout.},

keywords = {COVID-19},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {On the Origin and Propagation of the COVID-19 Outbreak in the Italian Province of Trento, a Tourist Region of Northern Italy},

author = {Bianco, Luca and Moser, Mirko and Silverj, Andrea and Micheletti, Diego and Lorenzin, Giovanni and Collini, Lucia and Barbareschi, Mattia and Lanzafame, Paolo and Segata, Nicola and Pindo, Massimo and Franceschi, Pietro and Rota-Stabelli, Omar and Rizzoli, Annapaola and Fontana, Paolo and Donati, Claudio},

url = {https://www.mdpi.com/1999-4915/14/3/580},

doi = {10.3390/v14030580},

issn = {1999-4915},

year  = {2022},

date = {2022-03-11},

journal = {Viruses},

volume = {14},

number = {580},

issue = {3},

abstract = {Background: Trentino is an Italian province with a tourism-based economy, bordering the regions of Lombardy and Veneto, where the two earliest and largest outbreaks of COVID-19 occurred in Italy. The earliest cases in Trentino were reported in the first week of March 2020, with most of the cases occurring in the winter sport areas in the Dolomites mountain range. The number of reported cases decreased over the summer months and was followed by a second wave in the autumn and winter of 2020. Methods: we performed high-coverage Oxford Nanopore sequencing of 253 positive SARS-CoV-2 swabs collected in Trentino between March and December 2020. Results: in this work, we analyzed genome sequences to trace the routes through which the virus entered the area, and assessed whether the autumnal resurgence could be attributed to lineages persisting undetected during summer, or as a consequence of new introductions. Conclusions: Comparing the draft genomes analyzed with a large selection of European sequences retrieved from GISAID we found that multiple introductions of the virus occurred at the early stage of the epidemics; the two epidemic waves were unrelated; the second wave was due to reintroductions of the virus in summer when traveling restrictions were uplifted.},

keywords = {COVID-19, genome, SARS-CoV-2, transmission},

pubstate = {published},

tppubtype = {article}

}

@article{@article{10.1093/ve/veac015,

title = {Phycova — a tool for exploring covariates of pathogen spread},

author = {Blokker, Tim and Baele, Guy and Lemey, Philippe and Dellicour, Simon},

url = {https://academic.oup.com/ve/article/8/1/veac015/6530450},

doi = {https://doi.org/10.1093/ve/veac015},

issn = {2057-1577},

year  = {2022},

date = {2022-02-18},

urldate = {2022-02-18},

journal = {Virus Evolution},

volume = {8},

issue = {1},

abstract = {Genetic analyses of fast-evolving pathogens are frequently undertaken to test the impact of covariates on their dispersal. In particular, a popular approach consists of parameterizing a discrete phylogeographic model as a generalized linear model to identify and analyse the predictors of the dispersal rates of viral lineages among discrete locations. However, such a full probabilistic inference is often computationally demanding and time-consuming. In the face of the increasing amount of viral genomes sequenced in epidemic outbreaks, there is a need for a fast exploration of covariates that might be relevant to consider in formal analyses. We here present PhyCovA (short for ‘Phylogeographic Covariate Analysis’), a web-based application allowing users to rapidly explore the association between candidate covariates and the number of phylogenetically informed transition events among locations. Specifically, PhyCovA takes as input a phylogenetic tree with discrete state annotations at the internal nodes, or reconstructs those states if not available, to subsequently conduct univariate and multivariate linear regression analyses, as well as an exploratory variable selection analysis. In addition, the application can also be used to generate and explore various visualizations related to the regression analyses or to the phylogenetic tree annotated by the ancestral state reconstruction. PhyCovA is freely accessible at https://evolcompvir-kuleuven.shinyapps.io/PhyCovA/ and also distributed in a dockerized form obtainable from https://hub.docker.com/repository/docker/timblokker/phycova. The source code and tutorial are available from the GitHub repository https://github.com/TimBlokker/PhyCovA.},

note = {veac015},

keywords = {BEAST, covariates, discrete phylogeography, generalized linear model, linear regression, pathogen spread, PhyCovA, visualization},

pubstate = {published},

tppubtype = {article}

}