MOOD publications

@article{nokey,

title = {Minimizing school disruption under high incidence conditions due to the Omicron variant in France, Switzerland, Italy in January 2022},

author = {Elisabetta Colosi and Giulia Bassignana and Alain Barrat and Bruno Lina and Philippe Vanhems and Julia Bielicki and Vittoria Colizza

},

url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2023.28.5.2200192#abstract_content},

doi = {10.2807/1560-7917.ES.2023.28.5.2200192},

year  = {2023},

date = {2023-02-02},

urldate = {2023-02-02},

abstract = {Background

As record cases of Omicron variant were registered in Europe in early 2022, schools remained a vulnerable setting undergoing large disruption.



Aim

Through mathematical modelling, we compared school protocols of reactive screening, regular screening, and reactive class closure implemented in France, in Baselland (Switzerland), and in Italy, respectively, and assessed them in terms of case prevention, testing resource demand, and schooldays lost.



Methods

We used a stochastic agent-based model of SARS-CoV-2 transmission in schools accounting for within- and across-class contacts from empirical contact data. We parameterised it to the Omicron BA.1 variant to reproduce the French Omicron wave in January 2022. We simulated the three protocols to assess their costs and effectiveness for varying peak incidence rates in the range experienced by European countries.



Results

We estimated that at the high incidence rates registered in France during the Omicron BA.1 wave in January 2022, the reactive screening protocol applied in France required higher test resources compared with the weekly screening applied in Baselland (0.50 vs 0.45 tests per student-week), but achieved considerably lower control (8% vs 21% reduction of peak incidence). The reactive class closure implemented in Italy was predicted to be very costly, leading to > 20% student-days lost.



Conclusions

At high incidence conditions, reactive screening protocols generate a large and unplanned demand in testing resources, for marginal control of school transmissions. Comparable or lower resources could be more efficiently used through weekly screening. Our findings can help define incidence levels triggering school protocols and optimise their cost-effectiveness.},

keywords = {Covid-19 (Coronavirus), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Global trends in antimicrobial use in food-producing animals: 2020 to 2030},

author = {Ranya Mulchandani and Yu Wang and Marius Gilbert and Thomas P Van Boeckel},

editor = {Ismail Ayoade Odetokun, University of Ilorin, NIGERIA},

url = {https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0001305#abstract0},

doi = {10.1371/journal.pgph.0001305},

year  = {2023},

date = {2023-02-01},

urldate = {2023-02-01},

journal = {PLOS Global Public Health},

volume = {3},

number = {2},

pages = {e0001305},

abstract = {Use of antimicrobials in farming has enabled the growth of intensive animal production and helped in meeting the global increase in demand for animal protein. However, the widespread use of veterinary antimicrobials drives antimicrobial resistance, with important consequences for animal health, and potentially human health. Global monitoring of antimicrobial use is essential: first, to track progress in reducing the reliance of farming on antimicrobials. Second, to identify countries where antimicrobial-stewardship efforts should be targeted to curb antimicrobial resistance. Data on usage of antimicrobials in food animals were collected from 42 countries. Multivariate regression models were used in combination with projections of animal counts for cattle, sheep, chicken, and pigs from the Food and Agriculture Organization to estimate global antimicrobial usage of veterinary antimicrobials in 2020 and 2030. Maps of animal densities were used to identify geographic hotspots of antimicrobial use. In each country, estimates of antimicrobial use (tonnes) were calibrated to match continental-level reports of antimicrobial use intensity (milligrams per kilogram of animal) from the World Organization for Animal Health, as well as country-level reports of antimicrobial use from countries that made this information publicly available. Globally, antimicrobial usage was estimated at 99,502 tonnes (95% CI 68,535–198,052) in 2020 and is projected, based on current trends, to increase by 8.0% to 107,472 tonnes (95% CI: 75,927–202,661) by 2030. Hotspots of antimicrobial use were overwhelmingly in Asia (67%), while <1% were in Africa. Findings indicate higher global antimicrobial usage in 2030 compared to prior projections that used data from 2017; this is likely associated with an upward revision of antimicrobial use in Asia/Oceania (~6,000 tonnes) and the Americas (~4,000 tonnes). National-level reporting of antimicrobial use should be encouraged to better evaluate the impact of national policies on antimicrobial use levels.},

keywords = {ASF (African Swine Fever), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Global patterns and drivers of influenza decline during the COVID-19 pandemic},

author = {Francesco Bonacina and Pierre-Yves Boëlle and Vittoria Colizza and Olivier Lopez and Maud Thomas and Chiara Poletto

},

url = {https://www.ijidonline.com/article/S1201-9712(22)00682-8/fulltext},

doi = {10.1016/j.ijid.2022.12.042},

year  = {2023},

date = {2023-01-03},

urldate = {2023-01-03},

abstract = {Objectives

The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers.

Methods

The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors.

Results

During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The “zero-COVID” countries experienced the greatest decline.

Conclusion

Our findings set the stage for interpreting the resurgence of influenza worldwide.},

keywords = {Covid-19 (Coronavirus), HPAI (Avian Influenza), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Epidemiological and Evolutionary Analysis of West Nile Virus Lineage 2 in Italy},

author = {Giulia Mencattelli and Andrea Silverj and Federica Iapaolo and Carla Ippoliti and Liana Teodori and Annapia Di Gennaro and Valentina Curini and Luca Candeloro and Annamaria Conte and Andrea Polci and Daniela Morelli and Maria Gabriella Perrotta and Giovanni Marini and Roberto Rosà and Federica Monaco and Nicola Segata and Annapaola Rizzoli and Omar Rota-Stabelli and Giovanni Savini and West Nile Working Group},

url = {https://www.mdpi.com/1999-4915/15/1/35},

doi = {10.3390/v15010035},

issn = {1999-4915},

year  = {2022},

date = {2022-12-22},

urldate = {2022-12-22},

journal = {Viruses},

volume = {15},

number = {35},

abstract = {West Nile virus (WNV) is a mosquito-borne virus potentially causing serious illness in humans and other animals. Since 2004, several studies have highlighted the progressive spread of WNV Lineage 2 (L2) in Europe, with Italy being one of the countries with the highest number of cases of West Nile disease reported. In this paper, we give an overview of the epidemiological and genetic features characterising the spread and evolution of WNV L2 in Italy, leveraging data obtained from national surveillance activities between 2011 and 2021, including 46 newly assembled genomes that were analysed under both phylogeographic and phylodynamic frameworks. In addition, to better understand the seasonal patterns of the virus, we used a machine learning model predicting areas at high-risk of WNV spread. Our results show a progressive increase in WNV L2 in Italy, clarifying the dynamics of interregional circulation, with no significant introductions from other countries in recent years. Moreover, the predicting model identified the presence of suitable conditions for the 2022 earlier and wider spread of WNV in Italy, underlining the importance of using quantitative models for early warning detection of WNV outbreaks. Taken together, these findings can be used as a reference to develop new strategies to mitigate the impact of the pathogen on human and other animal health in endemic areas and new regions.},

keywords = {OpenDataSet, WNV (West Nile Virus)},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Assessing spread risk of COVID-19 in early 2020},

author = {Shengjie Lai and Isaac Bogoch and Nick Ruktanonchai and Alexander Watts and Xin Lu and Weizhong Yang and Hongjie Yu and Kamran Khan and Andrew J Tatem

},

url = {https://www.sciencedirect.com/science/article/pii/S2666764922000340?via%3Dihub},

doi = {10.1016/j.dsm.2022.08.004},

year  = {2022},

date = {2022-12-08},

urldate = {2022-12-08},

volume = {5},

issue = {4},

abstract = {A novel coronavirus emerged in late 2019, named as the coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO). This study was originally conducted in January 2020 to estimate the potential risk and geographic range of COVID-19 spread at the early stage of the transmission. A series of connectivity and risk analyses based on domestic and international travel networks were conducted using historical aggregated mobile phone data and air passenger itinerary data. We found that the cordon sanitaire of the primary city was likely to have occurred during the latter stages of peak population numbers leaving the city, with travellers departing into neighbouring cities and other megacities in China. We estimated that there were 59,912 international air passengers, of which 834 (95% uncertainty interval: 478–1,349) had COVID-19 infection, with a strong correlation seen between the predicted risks of importation and the number of imported cases found. Given the limited understanding of emerging infectious diseases in the very early stages of outbreaks, our approaches and findings in assessing travel patterns and risk of transmission can help guide public health preparedness and intervention design for new COVID-19 waves caused by variants of concern and future pandemics to effectively limit transmission beyond its initial extent.



},

keywords = {Covid-19 (Coronavirus), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A quantitative assessment of epidemiological parameters required to investigate COVID-19 burden},

author = {Agnese Zardini and Margherita Galli and Marcello Tirani and Danilo Cereda and Mattia Manica and Filippo Trentini and Giorgio Guzzetta and Valentina Marziano and Raffaella Piccarreta and Alessia Melegaro and Marco Ajelli and Piero Poletti and Stefano Merler},

url = {https://www.sciencedirect.com/science/article/pii/S1755436521000748},

doi = {10.1016/j.epidem.2021.100530},

issn = {1755-4365},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

journal = {Epidemics},

volume = {37},

pages = {100530},

abstract = {Solid estimates describing the clinical course of SARS-CoV-2 infections are still lacking due to under-ascertainment of asymptomatic and mild-disease cases. In this work, we quantify age-specific probabilities of transitions between stages defining the natural history of SARS-CoV-2 infection from 1965 SARS-CoV-2 positive individuals identified in Italy between March and April 2020 among contacts of confirmed cases. Infected contacts of cases were confirmed via RT-PCR tests as part of contact tracing activities or retrospectively via IgG serological tests and followed-up for symptoms and clinical outcomes. In addition, we provide estimates of time intervals between key events defining the clinical progression of cases as obtained from a larger sample, consisting of 95,371 infections ascertained between February and July 2020. We found that being older than 60 years of age was associated with a 39.9% (95%CI: 36.2–43.6%) likelihood of developing respiratory symptoms or fever ≥ 37.5 °C after SARS-CoV-2 infection; the 22.3% (95%CI: 19.3–25.6%) of the infections in this age group required hospital care and the 1% (95%CI: 0.4–2.1%) were admitted to an intensive care unit (ICU). The corresponding proportions in individuals younger than 60 years were estimated at 27.9% (95%CI: 25.4–30.4%), 8.8% (95%CI: 7.3–10.5%) and 0.4% (95%CI: 0.1–0.9%), respectively. The infection fatality ratio (IFR) ranged from 0.2% (95%CI: 0.0–0.6%) in individuals younger than 60 years to 12.3% (95%CI: 6.9–19.7%) for those aged 80 years or more; the case fatality ratio (CFR) in these two age classes was 0.6% (95%CI: 0.1–2%) and 19.2% (95%CI: 10.9–30.1%), respectively. The median length of stay in hospital was 10 (IQR: 3–21) days; the length of stay in ICU was 11 (IQR: 6–19) days. The obtained estimates provide insights into the epidemiology of COVID-19 and could be instrumental to refine mathematical modeling work supporting public health decisions.},

keywords = {Covid-19 (Coronavirus)},

pubstate = {published},

tppubtype = {article}

}

@article{@article{MARINI2022100462,

title = {Modelling the West Nile virus force of infection in the European human population},

author = {Giovanni Marini and Andrea Pugliese and William Wint and Neil S. Alexander and Annapaola Rizzoli and Roberto Rosà},

url = {https://www.sciencedirect.com/science/article/pii/S2352771422000945},

doi = {https://doi.org/10.1016/j.onehlt.2022.100462},

issn = {2352-7714},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

journal = {One Health},

volume = {15},

pages = {100462},

abstract = {West Nile virus (WNV) is among the most recent emerging mosquito-borne pathogens in Europe where each year hundreds of human cases are recorded. We developed a relatively simple technique to model the WNV force of infection (FOI) in the human population to assess its dependence on environmental and human demographic factors. To this aim, we collated WNV human case-based data reported to the European Surveillance System from 15 European Countries during the period 2010–2021. We modelled the regional WNV FOI for each year through normal distributions and calibrated the constituent parameters, namely average (peak timing), variance and overall intensity, to observed cases. Finally, we investigated through regression models how these parameters are associated to a set of climatic, environmental and human demographic covariates. Our modelling approach shows good agreement between expected and observed epidemiological curves. We found that FOI magnitude is positively associated with spring temperature and larger in more anthropogenic semi-natural areas, while FOI peak timing is negatively related to summer temperature. Unsurprisingly, FOI is estimated to be greater in regions with a larger fraction of elderly people, who are more likely to contract severe infections. Our results confirm that temperature plays a key role in shaping WNV transmission in Europe and provide some interesting hints on how human presence and demography might affect WNV burden. This simple yet reliable approach could be easily adopted for early warning and to address epidemiological investigations of other vector-borne diseases, especially where eco-epidemiological data are scarce.},

keywords = {WNV (West Nile Virus)},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Optimization of adult mosquito trap settings to monitor populations of Aedes and Culex mosquitoes, vectors of arboviruses in La Reunion},

author = { Iris Claudel and Ronan Brouazin and Renaud Lancelot and Louis-Clément Gouagna and Marlène Dupraz and Thierry Baldet and Jérémy Bouyer},

url = {https://www.nature.com/articles/s41598-022-24191-9},

doi = {10.1038/s41598-022-24191-9},

year  = {2022},

date = {2022-11-15},

urldate = {2022-11-15},

journal = {Nature Communications},

number = {19544},

issue = {12},

abstract = {Competent arbovirus vectors are found in the culicid mosquito fauna of south-west Indian Ocean (SWIO) islands. In La Reunion, Aedes albopictus and Aedes aegypti mosquitoes are known vectors of dengue and chikungunya viruses. Culex quinquefasciatus is a potential vector of Rift Valley fever and West Nile viruses. To prepare a vector-control field trial against Ae. aegypti, this study aimed at identifying the best trapping strategy to catch adult Ae. aegypti, using BG-Sentinel traps (Biogents, Germany). It was implemented in two sites in southern La Reunion. Catches of Ae. albopictus and Cx. quinquefasciatus mosquitoes were also recorded. A Latin square design was used to estimate the detection probability and the apparent daily density—according to the BG-Sentinel trapping strategy: none, carbon dioxide (CO2), a commercial attractant—BG-Lure (Biogents, Germany), or both. The use of CO2 alone was associated with a higher detection probability for Ae. aegypti and Cx. quinquefasciatus mosquitoes, as well as a large increase in their apparent density. Traps with BG-Lure—alone or in combination with CO2, did not improve the detection probability of Ae. aegypti and Cx. quinquefasciatus mosquitoes. The same result was found for male Ae. albopictus. For females, baiting BG-Sentinel traps with CO2 or BG-Lure had no significant effect. The same apparent densities were found for Ae. aegypti and Ae. albopictus mosquitoes in both study sites—where Ae. aegypti mosquitoes were found at very low densities during previous surveys.},

keywords = {OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022},

author = {Paola Stefanelli and Filippo Trentini and Daniele Petrone and Alessia Mammone and Luigiana Ambrosio and Mattia Manica and Giorgio Guzzetta and Valeria d'Andrea and Valentina Marziano and Agnese Zardini and Carla Grane Molina and Marco Ajelli and Angela Di Martino and Flavia Riccardo and Antonino Bella and Monica Sane Schepisi and Francesco Maraglino and Piero Poletti amd Anna Teresa Palamara and Silvio Brusaferro and Giovanni Rezza and Patrizio Pezzotti Patrizio and Stefano Merler and the Genomic SARS–CoV–2 National Surveillance Working Group, the Italian Integrated Surveillance of COVID–19 Study Group

},

url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2022.27.45.2200125#html_fulltext},

doi = {10.2807/1560-7917.ES.2022.27.45.2200125},

year  = {2022},

date = {2022-11-10},

urldate = {2022-11-10},

abstract = {Background

The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.



Aim

To comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.



Methods

We analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.



Results

Omicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9–80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7–3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers’ decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.



Conclusion

Estimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.},

keywords = {Covid-19 (Coronavirus)},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Optimization of oviposition trap settings to monitor populations of Aedes mosquitoes, vectors of arboviruses in La Reunion},

author = {Ronan Brouazin and Iris Claudel and Renaud Lancelot and Guillaume Dupuy and Louis-Clément Gouagna and Marlène Dupraz and Theirry Baldet and Jérémy Bouyer},

url = {https://www.nature.com/articles/s41598-022-23137-5#citeas},

doi = {10.1038/s41598-022-23137-5},

year  = {2022},

date = {2022-11-02},

urldate = {2022-11-02},

journal = {Nature Communications},

number = {18450},

issue = {Sci Rep 12},

abstract = {Several dengue epidemics recently occurred in La Reunion, an island harboring two dengue viruses (DVs) vectors: Aedes albopictus, and Ae. aegypti, the former being the main local DV vector. Aedes aegypti shows a peculiar ecology, compared to other tropical populations of the same species. This study aimed to provide researchers and public-health users with locally validated oviposition traps (ovitraps) to monitor Aedes populations. A field experiment was performed in Saint-Joseph to assess the effect of different settings on the detection probability and apparent density of Aedes mosquitoes. Black plastic ovitraps were identified as the best choice. Vacoa trees (Pandanus utilis) were the only observed breeding sites for Ae. aegypti, shared with Ae. albopictus. They were the experimental units in a Latin square design with three factors: trap position in the trees (ground vs canopy), oviposition surface in the trap (blotting paper vs. vacoa leaf), and addition of organic matter to the trap water. The latter factor was found unimportant. On the ground, Ae. aegypti eggs were only found with vacoa leaves as the oviposition surface. Their detection and apparent density increased when ovitraps were located in the tree canopy. The main factor for Ae. albopictus was the oviposition surface, with a preference for blotting paper. In all trap settings, their detection was close to 100%. Larval survival was lower for a high egg density, combined with blotting paper as the oviposition surface. When monitoring mixed Aedes populations in La Reunion, we recommend using black plastic ovitraps, placed at 1.50-to-2.00-m high in vacoa trees, with vacoa leaves as the oviposition surface.},

keywords = {OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Elaboration of a new framework for fine-grained epidemiological annotation},

author = {Sarah Valentin and Elena Arsevska and al.

},

url = {https://www.nature.com/articles/s41597-022-01743-2},

doi = {10.1038/s41597-022-01743-2},

year  = {2022},

date = {2022-10-26},

urldate = {2022-10-26},

abstract = {Event-based surveillance (EBS) gathers information from a variety of data sources, including online news articles. Unlike the data from formal reporting, the EBS data are not structured, and their interpretation can overwhelm epidemic intelligence (EI) capacities in terms of available human resources. Therefore, diverse EBS systems that automatically process (all or part of) the acquired nonstructured data from online news articles have been developed. These EBS systems (e.g., GPHIN, HealthMap, MedISys, ProMED, PADI-web) can use annotated data to improve the surveillance systems. This paper describes a framework for the annotation of epidemiological information in animal disease-related news articles. We provide annotation guidelines that are generic and applicable to both animal and zoonotic infectious diseases, regardless of the pathogen involved or its mode of transmission (e.g., vector-borne, airborne, by contact). The framework relies on the successive annotation of all the sentences from a news article. The annotator evaluates the sentences in a specific epidemiological context, corresponding to the publication date of the news article.



},

keywords = {OpenDataSet, Text mining},

pubstate = {published},

tppubtype = {article}

}

@article{@article{2022b,

title = {Two Years of Genomic Surveillance in Belgium during the SARS-CoV-2 Pandemic to Attain Country-Wide Coverage and Monitor the Introduction and Spread of Emerging Variants},

author = {Lize Cuypers and Simon Dellicour and Samuel L. Hong and Barney l. Potter and Bruno Verhasselt and Nick Vereecke and Laurens Lambrechts and Keith Durkin and Vincent Bours and Sofieke Klamer and Guillaume Bayon-Vicente and Carl Vael and Kevin K. Ariën and Ricardo De Mendonca and Oriane Soetens and Charlotte Michel and Bertrand Bearzatto and Reinout Naesens and Jeremie Gras and Anne Vankeerberghen and Veerle Matheeussen and Geert Martens and Dagmar Obbels and Ann Lemmens and Bea Van den Poel and Ellen Van Even and Klara De Rauw and Luc Waumans and Marijke Reynders and Jonathan Degosserie and Piet Maes and Emmanuel André and Guy Baele},

url = {https://www.mdpi.com/1999-4915/14/10/2301},

doi = {https://doi.org/10.3390/v14102301},

issn = {1999-4915},

year  = {2022},

date = {2022-10-20},

urldate = {2022-10-20},

journal = {Viruses},

volume = {14},

number = {10},

pages = {2301},

abstract = {An adequate SARS-CoV-2 genomic surveillance strategy has proven to be essential for countries to obtain a thorough understanding of the variants and lineages being imported and successfully established within their borders. During 2020, genomic surveillance in Belgium was not structurally implemented but performed by individual research laboratories that had to acquire the necessary funds themselves to perform this important task. At the start of 2021, a nationwide genomic surveillance consortium was established in Belgium to markedly increase the country’s genomic sequencing efforts (both in terms of intensity and representativeness), to perform quality control among participating laboratories, and to enable coordination and collaboration of research projects and publications. We here discuss the genomic surveillance efforts in Belgium before and after the establishment of its genomic sequencing consortium, provide an overview of the specifics of the consortium, and explore more details regarding the scientific studies that have been published as a result of the increased number of Belgian SARS-CoV-2 genomes that have become available.},

keywords = {Covid-19 (Coronavirus)},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients},

author = {Bronner P Gonçalves and Matthew Hall and Waasila Jassat and Valeria Balan and Srinivas Murthy and Christiana Kartsonaki and Malcolm G Semple and Amanda Rojek and Joaquín Baruch and Luis Felipe Reyes and Abhishek Dasgupta and Jake Dunning and Barbara Wanjiru Citarella and Mark Pritchard and Alejandro Martín-Quiros and Uluhan SiliJ Kenneth Baillie and Diptesh Aryal and Yaseen Arabi and Aasiyah Rashan and Andrea AnghebenJanice CaoiliFrançois Martin CarrierEwen M HarrisonJoan Gómez-JunyentClaudia Figueiredo-MelloJames Joshua DouglasMohd Basri Mat Nor and Yock Ping Chow and Xin Ci Wong and Silvia Bertagnolio and Soe Soe Thwin and Anca Streinu-Cercel and Leonardo Salazar and Asgar Rishu and Rajavardhan Rangappa and David SY Ong and Madiha Hashmi and Gail Carson and Janet Diaz and Rob Fowler and Moritz UG Kraemer and Evert-Jan Wils and Peter Horby and Laura Merson and Piero L Olliaro and ISARIC Clinical Characterisation Group},

url = {https://elifesciences.org/articles/80556},

doi = {https://doi.org/10.7554/eLife.80556},

year  = {2022},

date = {2022-10-05},

urldate = {2022-10-05},

journal = {elife},

abstract = {Background:

Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings.



Methods:

Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries.



Results:

Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61–0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population.



Conclusions:

Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.},

keywords = {Covid-19 (Coronavirus), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades},

author = {Raphaëlle Klitting and Liana E. Kafetzopoulou and Wim Thiery and Gytis Dudas and Sophie Gryseels and Anjali Kotamarthi and Bram Vranckenand Karthik Gangavarapu and Mambu Momoh and John Demby Sandi and Augustine Goba and Foday Alhasan and Donald S. Grant and Sylvanus Okogbenin and Ephraim Ogbaini-Emovo and Robert F. Garry and Allison R. Smither and Mark Zeller and Matthias G. Pauthner and Michelle McGraw and Laura D. Hughes and Sophie Duraffour and Stephan Günther and Marc A. Suchard and Philippe Lemey and Kristian G. Andersen and Simon Dellicour},

url = {https://www.nature.com/articles/s41467-022-33112-3#citeas},

doi = {https://doi.org/10.1038/s41467-022-33112-3},

year  = {2022},

date = {2022-09-27},

urldate = {2022-09-27},

journal = {Nature Communications},

volume = {13},

number = {5596},

abstract = {Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades.},

keywords = {OpenDataSet},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Emergence of an early SARS-CoV-2 epidemic in the United States},

author = {Mark Zeller and Karthik Gangavarapu and Catelyn Anderson and Allison R. Smither and John A. Vanchiere and Rebecca Rose and Daniel J. Snyder and Gytis Dudas and Alexander Watts and Nathaniel L. Matteson and Refugio Robles-Sikisaka and Maximilian Marshall and Amy K. Feehan and Gilberto Sabino-Santos and Antoinette R. Bell-Kareem and Laura D. Hughes and Manar Alkuzweny and Patricia Snarski and Julia Garcia-Diaz and Rona S. Scott and Lilia I. Melnik and Raphaëlle Klitting and Michelle McGraw and Pedro Belda-Ferre and Peter DeHoff and Shashank Sathe and Clarisse Marotz and Nathan D. Grubaugh and David J. Nolan and Arnaud C. Drouin and Kaylynn J. Genemaras and Karissa Chao and Sarah Topol and Emily Spencer and Laura Nicholson and Stefan Aigner and Gene W. Yeo and Lauge Farnaes and Charlotte A. Hobbs and Louise C. Laurent and Rob Knight and Emma B. Hodcroft and Kamran Khan and Dahlene N. Fusco and Vaughn S. Cooper and Phillipe Lemey and Lauren Gardner and Susanna L. Lamers and Jeremy P. Kamil and Robert F. Garry and Marc A. Suchard and Kristian G. Andersen},

url = {https://www.sciencedirect.com/science/article/pii/S0092867421008898},

doi = {10.1016/j.cell.2021.07.030},

issn = {0092-8674},

year  = {2022},

date = {2022-09-16},

urldate = {2022-09-16},

journal = {Cell},

volume = {184},

issue = {19},

pages = {4939-4952.e15},

abstract = {The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.},

keywords = {Covid-19 (Coronavirus), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}