MOOD publications

@article{nokey,

title = {Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates},

author = {Rhys P.D. Inward and Felix Jackson and Abhishek Dasgupta and Graham Lee and Anya Lindström Battle and Kris V. Parag and Moritz U.G. Kraemer},

url = {https://www.sciencedirect.com/science/article/pii/S1755436522000676},

doi = {10.1016/j.epidem.2022.100627},

issn = {1755-4365},

year  = {2023},

date = {2023-12-01},

urldate = {2023-12-01},

journal = {Epidemics},

volume = {41},

pages = {100627},

abstract = {SARS-CoV-2 case data are primary sources for estimating epidemiological parameters and for modelling the dynamics of outbreaks. Understanding biases within case-based data sources used in epidemiological analyses is important as they can detract from the value of these rich datasets. This raises questions of how variations in surveillance can affect the estimation of epidemiological parameters such as the case growth rates. We use standardised line list data of COVID-19 from Argentina, Brazil, Mexico and Colombia to estimate delay distributions of symptom-onset-to-confirmation, -hospitalisation and -death as well as hospitalisation-to-death at high spatial resolutions and throughout time. Using these estimates, we model the biases introduced by the delay from symptom-onset-to-confirmation on national and state level case growth rates (rt) using an adaptation of the Richardson-Lucy deconvolution algorithm. We find significant heterogeneities in the estimation of delay distributions through time and space with delay difference of up to 19 days between epochs at the state level. Further, we find that by changing the spatial scale, estimates of case growth rate can vary by up to 0.13 d−1. Lastly, we find that states with a high variance and/or mean delay in symptom-onset-to-diagnosis also have the largest difference between the rt estimated from raw and deconvolved case counts at the state level. We highlight the importance of high-resolution case-based data in understanding biases in disease reporting and how these biases can be avoided by adjusting case numbers based on empirical delay distributions. Code and openly accessible data to reproduce analyses presented here are available.},

keywords = {Epidemic models, Outbreak surveillance, SARS-CoV-2},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A social-ecological systems approach to tick bite and tick-borne disease risk management: Exploring collective action in the Occitanie region in southern France},

author = {Iyonna Zortman and Michel de Garine-Wichatitsky and Elena Arsevska and Timothée Dub and Wim Van Bortel and Estelle Lefrançois and Laurence Vial and Thomas Pollet and Aurélie Binot,},

url = {https://www.sciencedirect.com/science/article/pii/S2352771423001507},

doi = {https://doi.org/10.1016/j.onehlt.2023.100630},

issn = {2352-7714},

year  = {2023},

date = {2023-12-01},

journal = {One Health},

volume = {17},

pages = {100630},

abstract = {Ticks are amongst the most important zoonotic disease vectors affecting human and animal health worldwide. Tick-borne diseases (TBDs) are rapidly expanding geographically and in incidence, most notably in temperate regions of Europe where ticks are considered the principal zoonotic vector of Public Health relevance, as well as a major health and economic preoccupation in agriculture and equine industries. Tick-borne pathogen (TBP) transmission is contingent on complex, interlinked vector-pathogen-host dynamics, environmental and ecological conditions and human behavior. Tackling TBD therefore requires a better understanding of the interconnected social and ecological variables (i.e., the social-ecological system) that favor disease (re)-emergence. The One Health paradigm recognizes the interdependence of human, animal and environmental health and proposes an integrated approach to manage TBD. However, One Health interventions are limited by significant gaps in our understanding of the complex, systemic nature of TBD risk, in addition to a lack of effective, universally accepted and environmentally conscious tick control measures. Today individual prevention gestures are the most effective strategy to manage TBDs in humans and animals, making local communities important actors in TBD detection, prevention and management. Yet, how they engage and collaborate within a multi-actor TBD network has not yet been explored. Here, we argue that transdisciplinary collaborations that go beyond research, political and medical stakeholders, and extend to local community actors can aid in identifying relevant social-ecological risk indicators key for informing multi-level TBD detection, prevention and management measures. This article proposes a transdisciplinary social-ecological systems framework, based on participatory research approaches, to better understand the necessary conditions for local actor engagement to improve TBD risk. We conclude with perspectives for implementing this methodological framework in a case study in the south of France (Occitanie region), where multi-actor collaborations are mobilized to stimulate multi-actor collective action and identify relevant social-ecological indicators of TBD risk.},

keywords = {One Health},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Outdoor recreation, tick borne encephalitis incidence and seasonality in Finland, Norway and Sweden during the COVID-19 pandemic (2020/2021)},

author = {Solveig Jore, Hildegunn Viljugrein, Marika Hjertqvist, Timothée Dub and Henna Mäkelä},

url = {https://doi.org/10.1080/20008686.2023.2281055},

doi = {10.1080/20008686.2023.2281055},

year  = {2023},

date = {2023-11-18},

journal = {Infection Ecology & Epidemiology},

volume = {13},

number = {1},

pages = {2281055},

abstract = {During the pandemic outdoor activities were encouraged to mitigate transmission risk while providing safe spaces for social interactions. Human behaviour, which may favour or disfavour, contact rates between questing ticks and humans, is a key factor impacting tick-borne encephalitis (TBE) incidence. We analyzed annual and weekly TBE cases in Finland, Norway and Sweden from 2010 to 2021 to assess trend, seasonality, and discuss changes in human tick exposure imposed by COVID-19. We compared the pre-pandemic incidence (2010–2019) with the pandemic incidence (2020–2021) by fitting a generalized linear model (GLM) to incidence data. Pre-pandemic incidence was 1.0, 0.29 and 2.8 for Finland, Norway and Sweden, respectively, compared to incidence of 2.2, 1.0 and 3.9 during the pandemic years. However, there was an increasing trend for all countries across the whole study period. Therefore, we predicted the number of cases in 2020/2021 based on a model fitted to the annual cases in 2010–2019. The incidences during the pandemic were 1.3 times higher for Finland, 1.7 times higher for Norway and no difference for Sweden. When social restrictions were enforced to curb the spread of SARS-CoV-2 there were profound changes in outdoor recreational behavior. Future consideration of public health interventions that promote outdoor activities may increase exposure to vector-borne diseases. },

keywords = {COVID-19, Public Health, seasonality, TBE, tick-borne encephalitis},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Ecological and environmental factors affecting the risk of tick-borne encephalitis in Europe, 2017 to 2021},

author = {Francesca Dagostin, Valentina Tagliapietra, Giovanni Marini, Claudia Cataldo, Maria Bellenghi, Scilla Pizzarelli, Rosaria Rosanna Cammarano, William Wint, Neil S Alexander, Markus Neteler, Julia Haas, Timothée Dub, Luca Busani, Annapaola Rizzoli

},

url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2023.28.42.2300121},

doi = {10.2807/1560-7917.ES.2023.28.42.2300121},

year  = {2023},

date = {2023-10-19},

abstract = {Background

Tick-borne encephalitis (TBE) is a disease which can lead to severe neurological symptoms, caused by the TBE virus (TBEV). The natural transmission cycle occurs in foci and involves ticks as vectors and several key hosts that act as reservoirs and amplifiers of the infection spread. Recently, the incidence of TBE in Europe has been rising in both endemic and new regions.



Aim

In this study we want to provide comprehensive understanding of the main ecological and environmental factors that affect TBE spread across Europe.



Methods

We searched available literature on covariates linked with the circulation of TBEV in Europe. We then assessed the best predictors for TBE incidence in 11 European countries by means of statistical regression, using data on human infections provided by the European Surveillance System (TESSy), averaged between 2017 and 2021.



Results

We retrieved data from 62 full-text articles and identified 31 different covariates associated with TBE occurrence. Finally, we selected eight variables from the best model, including factors linked to vegetation cover, climate, and the presence of tick hosts.



Discussion

The existing literature is heterogeneous, both in study design and covariate types. Here, we summarised and statistically validated the covariates affecting the variability of TBEV across Europe. The analysis of the factors enhancing disease emergence is a fundamental step towards the identification of potential hotspots of viral circulation. Hence, our results can support modelling efforts to estimate the risk of TBEV infections and help decision-makers implement surveillance and prevention campaigns.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The Spatial Distribution of Crimean–Congo Haemorrhagic Fever and Its Potential Vectors in Europe and Beyond},

author = {Messina, Jane Paula, and G. R. William Wint},

url = {https://www.mdpi.com/2075-4450/14/9/771},

doi = {10.3390/insects14090771},

year  = {2023},

date = {2023-09-17},

journal = {Insects},

volume = {14},

number = {771},

abstract = {Crimean–Congo haemorrhagic fever (CCHF) is considered to be spreading across the globe, with many countries reporting new human CCHF cases in recent decades including Georgia, Türkiye, Albania, and, most recently, Spain. We update a human CCHF distribution map produced in 2015 to include global disease occurrence records to June 2022, and we include the recent records for Europe. The predicted distributions are based on long-established spatial modelling methods and are extended to include all European countries and the surrounding areas. The map produced shows the environmental suitability for the disease, taking into account the distribution of the most important known and potential tick vectors Hyalomma marginatum and Hyalomma lusitanicum, without which the disease cannot occur. This limits the disease’s predicted distribution to the Iberian Peninsula, the Mediterranean seaboard, along with Türkiye and the Caucasus, with a more patchy suitability predicted for inland Greece, the southern Balkans, and extending north to north-west France and central Europe. These updated CCHF maps can be used to identify the areas with the highest probability of disease and to therefore target areas where mitigation measures should currently be focused.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Reporting delays of chikungunya cases during the 2017 outbreak in Lazio region, Italy},

author = {Mattia Manica, Giovanni Marini, Angelo Solimini, Giorgio Guzzetta, Piero Poletti, Paola Scognamiglio, Chiara Virgillito, Alessandra della Torre, Stefano Merler, Roberto Rosà, Francesco Vairo, Beniamino Caputo

},

url = {https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0011610},

doi = {10.1371/journal.pntd.0011610},

year  = {2023},

date = {2023-09-14},

abstract = {Background

Emerging arboviral diseases in Europe pose a challenge due to difficulties in detecting and diagnosing cases during the initial circulation of the pathogen. Early outbreak detection enables public health authorities to take effective actions to reduce disease transmission. Quantification of the reporting delays of cases is vital to plan and assess surveillance and control strategies. Here, we provide estimates of reporting delays during an emerging arboviral outbreak and indications on how delays may have impacted onward transmission.



Methodology/principal findings

Using descriptive statistics and Kaplan-Meyer curves we analyzed case reporting delays (the period between the date of symptom onset and the date of notification to the public health authorities) during the 2017 Italian chikungunya outbreak. We further investigated the effect of outbreak detection on reporting delays by means of a Cox proportional hazard model. We estimated that the overall median reporting delay was 15.5 days, but this was reduced to 8 days after the notification of the first case. Cases with symptom onset after outbreak detection had about a 3.5 times higher reporting rate, however only 3.6% were notified within 24h from symptom onset. Remarkably, we found that 45.9% of identified cases developed symptoms before the detection of the outbreak.



Conclusions/significance

These results suggest that efforts should be undertaken to improve the early detection and identification of arboviral cases, as well as the management of vector species to mitigate the impact of long reporting delays.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Dissemination of information in event-based surveillance, a case study of Avian Influenza},

author = {Valentin S, Boudoua B, Sewalk K, Arınık N, Roche M, Lancelot R, et al.},

url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0285341},

doi = {10.1371/journal.pone.0285341},

year  = {2023},

date = {2023-09-05},

journal = {PLoS ONE},

abstract = {Event-Based Surveillance (EBS) tools, such as HealthMap and PADI-web, monitor online news reports and other unofficial sources, with the primary aim to provide timely information to users from health agencies on disease outbreaks occurring worldwide. In this work, we describe how outbreak-related information disseminates from a primary source, via a secondary source, to a definitive aggregator, an EBS tool, during the 2018/19 avian influenza season. We analysed 337 news items from the PADI-web and 115 news articles from HealthMap EBS tools reporting avian influenza outbreaks in birds worldwide between July 2018 and June 2019. We used the sources cited in the news to trace the path of each outbreak. We built a directed network with nodes representing the sources (characterised by type, specialisation, and geographical focus) and edges representing the flow of information. We calculated the degree as a centrality measure to determine the importance of the nodes in information dissemination. We analysed the role of the sources in early detection (detection of an event before its official notification) to the World Organisation for Animal Health (WOAH) and late detection. A total of 23% and 43% of the avian influenza outbreaks detected by the PADI-web and HealthMap, respectively, were shared on time before their notification. For both tools, national and local veterinary authorities were the primary sources of early detection. The early detection component mainly relied on the dissemination of nationally acknowledged events by online news and press agencies, bypassing international reporting to the WAOH. WOAH was the major secondary source for late detection, occupying a central position between national authorities and disseminator sources, such as online news. PADI-web and HealthMap were highly complementary in terms of detected sources, explaining why 90% of the events were detected by only one of the tools. We show that current EBS tools can provide timely outbreak-related information and priority news sources to improve digital disease surveillance.



Figures},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The values and risks of an Intergovernmental Panel for One Health to strengthen pandemic prevention, preparedness, and response},

author = {Alexandre Hobeika PhD , Maxime Henri Tibault Stauffer MSc , Timothée Dub MD , Wim van Bortel PhD , Martin Beniston PhD , Salome Bukachi PhD , Gian Luca Burci PhD , Lisa Crump PhD , Prof Wanda Markotter PhD , Ludovico Pasquale Sepe PhD , Enrichetta Placella MSc , Benjamin Roche PhD , Oumy Thiongane PhD , Zhanyun Wang PhD , Frédérique Guérin PhD , Esther van Kleef PhD},

doi = {10.1016/S2214-109X(23)00246-2},

year  = {2023},

date = {2023-08-15},

journal = {The values and risks of an Intergovernmental Panel for One Health to strengthen pandemic prevention, preparedness, and response},

volume = {11},

issue = {8},

pages = {1301-1307},

abstract = {The COVID-19 pandemic has shown the need for better global governance of pandemic prevention, preparedness, and response (PPR) and has emphasised the importance of organised knowledge production and uptake. In this Health Policy, we assess the potential values and risks of establishing an Intergovernmental Panel for One Health (IPOH). Similar to the Intergovernmental Panel on Climate Change, an IPOH would facilitate knowledge uptake in policy making via a multisectoral approach, and hence support the addressing of infectious disease emergence and re-emergence at the human–animal–environment interface. The potential benefits to pandemic PPR include a clear, unified, and authoritative voice from the scientific community, support to help donors and institutions to prioritise their investments, evidence-based policies for implementation, and guidance on defragmenting the global health system. Potential risks include a scope not encompassing all pandemic origins, unclear efficacy in fostering knowledge uptake by policy makers, potentially inadequate speed in facilitating response efforts, and coordination challenges among an already dense set of stakeholders. We recommend weighing these factors when designing institutional reforms for a more effective global health system.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Epidemic intelligence activities among national public and animal health agencies: a European cross-sectional study},

author = {Dub, T., Mäkelä, H., Van Kleef, E. et al.},

url = {https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-023-16396-y#citeas},

doi = {10.1186/s12889-023-16396-y},

year  = {2023},

date = {2023-08-04},

journal = {BMC Public Health},

volume = {23},

number = {1488},

abstract = {Epidemic Intelligence (EI) encompasses all activities related to early identification, verification, analysis, assessment, and investigation of health threats. It integrates an indicator-based (IBS) component using systematically collected surveillance data, and an event-based component (EBS), using non-official, non-verified, non-structured data from multiple sources.



We described current EI practices in Europe by conducting a survey of national Public Health (PH) and Animal Health (AH) agencies. We included generic questions on the structure, mandate and scope of the institute, on the existence and coordination of EI activities, followed by a section where respondents provided a description of EI activities for three diseases out of seven disease models. Out of 81 gatekeeper agencies from 41 countries contacted, 34 agencies (42%) from 26 (63%) different countries responded, out of which, 32 conducted EI activities. Less than half (15/32; 47%) had teams dedicated to EI activities and 56% (18/34) had Standard Operating Procedures (SOPs) in place. On a national level, a combination of IBS and EBS was the most common data source. Most respondents monitored the epidemiological situation in bordering countries, the rest of Europe and the world. EI systems were heterogeneous across countries and diseases. National IBS activities strongly relied on mandatory laboratory-based surveillance systems. The collection, analysis and interpretation of IBS information was performed manually for most disease models. Depending on the disease, some respondents did not have any EBS activity. Most respondents conducted signal assessment manually through expert review. Cross-sectoral collaboration was heterogeneous. More than half of the responding institutes collaborated on various levels (data sharing, communication, etc.) with neighbouring countries and/or international structures, across most disease models.



Our findings emphasise a notable engagement in EI activities across PH and AH institutes of Europe, but opportunities exist for better integration, standardisation, and automatization of these efforts. A strong reliance on traditional IBS and laboratory-based surveillance systems, emphasises the key role of in-country laboratories networks. EI activities may benefit particularly from investments in cross-border collaboration, the development of methods that can automatise signal assessment in both IBS and EBS data, as well as further investments in the collection of EBS data beyond scientific literature and mainstream media.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Epidemic intelligence activities among national public and animal health agencies: a European cross-sectional study},

author = {Timothee Dub, Henna Mäkelä, Esther Van Kleef, Agnes Leblond, Alizé Mercier, Viviane Hénaux, Fanny Bouyer, Aurelie Binot, Oumy Thiongane, Renaud Lancelot, Valentina Delconte, Lea Zamuner, Wim Van Bortel & Elena Arsevska

},

url = {https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-023-16396-y#article-info},

doi = {10.1186/s12889-023-16396-y},

year  = {2023},

date = {2023-08-04},

abstract = {Epidemic Intelligence (EI) encompasses all activities related to early identification, verification, analysis, assessment, and investigation of health threats. It integrates an indicator-based (IBS) component using systematically collected surveillance data, and an event-based component (EBS), using non-official, non-verified, non-structured data from multiple sources.



We described current EI practices in Europe by conducting a survey of national Public Health (PH) and Animal Health (AH) agencies. We included generic questions on the structure, mandate and scope of the institute, on the existence and coordination of EI activities, followed by a section where respondents provided a description of EI activities for three diseases out of seven disease models. Out of 81 gatekeeper agencies from 41 countries contacted, 34 agencies (42%) from 26 (63%) different countries responded, out of which, 32 conducted EI activities. Less than half (15/32; 47%) had teams dedicated to EI activities and 56% (18/34) had Standard Operating Procedures (SOPs) in place. On a national level, a combination of IBS and EBS was the most common data source. Most respondents monitored the epidemiological situation in bordering countries, the rest of Europe and the world. EI systems were heterogeneous across countries and diseases. National IBS activities strongly relied on mandatory laboratory-based surveillance systems. The collection, analysis and interpretation of IBS information was performed manually for most disease models. Depending on the disease, some respondents did not have any EBS activity. Most respondents conducted signal assessment manually through expert review. Cross-sectoral collaboration was heterogeneous. More than half of the responding institutes collaborated on various levels (data sharing, communication, etc.) with neighbouring countries and/or international structures, across most disease models.



Our findings emphasise a notable engagement in EI activities across PH and AH institutes of Europe, but opportunities exist for better integration, standardisation, and automatization of these efforts. A strong reliance on traditional IBS and laboratory-based surveillance systems, emphasises the key role of in-country laboratories networks. EI activities may benefit particularly from investments in cross-border collaboration, the development of methods that can automatise signal assessment in both IBS and EBS data, as well as further investments in the collection of EBS data beyond scientific literature and mainstream media.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {SNEToolkit: Spatial Named Entities disambiguation Toolki},

author = {Rodrique Kafando, Rémy Decoupes, Mathieu Roche, Maguelonne Teisseire},

url = {https://www.softxjournal.com/article/S2352-7110(23)00176-0/fulltext},

doi = {10.1016/j.softx.2023.101480},

year  = {2023},

date = {2023-07-31},

abstract = {“Can you tell me where San Jose is located?” “Uh! Do you know that there are more than 1700 locations named San Jose in the world?” The official name of a location is often not the name with which we are familiar. Spatial named entity (SNE) disambiguation is the process of identifying and assigning precise coordinates to a place name that can be identified in a text. This task is not always straightforward, especially when the place name in question is ambiguous for various reasons. In this context, we are interested in the disambiguation of spatial named entities that can be identified in a textual document on a country level. The solution that we propose is based on a set of techniques that allow us to disambiguate the spatial entity considering the context in which it is mentioned from a certain number of characteristics that are specific to it. The solution uses as input a textual document and extricates the named entities identified therein while associating them with the correct coordinates. SNE disambiguation is designed to support the process of fast exploration of spatiotemporal data analysis, most often for event tracking. The proposed approach was tested on 1360 SNEs extracted from the GeoVirus dataset. The results show that SNEToolkit outperformed the baseline, the standard Geonames geocoder, with a recall value of 0.911 against a recall value of 0.871 for the baseline. A flexible Python package is provided for end users.

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Animal disease surveillance: How to represent textual data for classifying epidemiological information},

author = {Sarah Valentin, Rémy Decoupes, Renaud Lancelot, 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},

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}

}

@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},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@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, Eugenio Valdano, Claudio Castellano, Marion Debin, Charly Kengne-Kuetche, Clément Turbelin, Harold Noël, Joshua S. Weitz, Daniela Paolotti, Lisa Hermans, Niel Hens, 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},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{nokey,

title = {An Evaluation Framework For Comparing Epidemic Intelligence Systems},

author = {Nejat Arinik; Roberto Interdonato; Mathieu Roche; Maguelonne Teisseire

},

url = {https://ieeexplore.ieee.org/document/10082884},

doi = {10.1109/ACCESS.2023.3262462},

year  = {2023},

date = {2023-03-27},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Polygon vector map distortion for increasing the readability ofone-to-many flow maps},

author = {Laëtitia Viau, Arnaud Sallaberry, Nancy Rodriguez, Jean-François Girres & 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},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Estimating rodent population abundance using early climatic predictors},

author = {Marini, Giovanni and Arnoldi, Daniele and Rizzoli, Annapaola and Tagliapietra, Valentina},

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 = {Apodemus flavicollis, Climate, early warning, Rodent density},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {An annotated dataset for event-based surveillance of antimicrobial resistance},

author = {Nejat Arınık, Wim Van Bortel, Bahdja Boudoua, Luca Busani, Rémy Decoupes, Roberto Interdonato, Rodrique Kafando, Esther van Kleef, Mathieu Roche, Mehtab Alam Syed, 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},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Gender gap reduction and the one health benefits Author links open overlay panel},

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},

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 = {eco health, education, empowerment, Gender gap, Gender-specific roles, One Health},

pubstate = {published},

tppubtype = {article}

}