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3. Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Kraemer, Moritz UG, Reiner, Robert C, Brady, Oliver J, Messina, Jane P, Gilbert, Marius, Pigott, David M, Yi, Dingdong, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Weaver, Nicole Davis, Bisanzio, Donal, Perkins, T Alex, Lai, Shengjie, Lu, Xin, Jones, Peter, Coelho, Giovanini E, Carvalho, Roberta G, Van Bortel, Wim, Marsboom, Cedric, Hendrickx, Guy, Schaffner, Francis, Moore, Chester G, Nax, Heinrich H, Bengtsson, Linus, Wetter, Erik, Tatem, Andrew J, Brownstein, John S, Smith, David L, Lambrechts, Louis, Cauchemez, Simon, Linard, Catherine, Faria, Nuno R, Pybus, Oliver G, Scott, Thomas W, Liu, Qiyong, Yu, Hongjie, Wint, GR William, Hay, Simon I, and Golding, Nick

Subjects
Microbiology, Biological Sciences, Prevention, Good Health and Well Being, Medical Microbiology
Abstract

In the version of this Article originally published, the affiliation for author Catherine Linard was incorrectly stated as '6Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK'. The correct affiliation is '9Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium'. The affiliation for author Hongjie Yu was also incorrectly stated as '11Department of Statistics, Harvard University, Cambridge, MA, USA'. The correct affiliation is '15School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China'. This has now been amended in all versions of the Article.

Published
2019

4. Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Kraemer, Moritz UG, Reiner, Robert C, Brady, Oliver J, Messina, Jane P, Gilbert, Marius, Pigott, David M, Yi, Dingdong, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Davis Weaver, Nicole, Bisanzio, Donal, Perkins, T Alex, Lai, Shengjie, Lu, Xin, Jones, Peter, Coelho, Giovanini E, Carvalho, Roberta G, Van Bortel, Wim, Marsboom, Cedric, Hendrickx, Guy, Schaffner, Francis, Moore, Chester G, Nax, Heinrich H, Bengtsson, Linus, Wetter, Erik, Tatem, Andrew J, Brownstein, John S, Smith, David L, Lambrechts, Louis, Cauchemez, Simon, Linard, Catherine, Faria, Nuno R, Pybus, Oliver G, Scott, Thomas W, Liu, Qiyong, Yu, Hongjie, Wint, GR William, Hay, Simon I, and Golding, Nick

Subjects
Microbiology, Biological Sciences, Rare Diseases, Vaccine Related, Prevention, Infectious Diseases, Emerging Infectious Diseases, Biodefense, Vector-Borne Diseases, Infection, Good Health and Well Being, Aedes, Animals, Arbovirus Infections, Arboviruses, Female, Humans, Mosquito Vectors, Medical Microbiology
Abstract

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Published
2019

7. VectorNet: collaborative mapping of arthropod disease vectors in Europe and surrounding areas since 2010

Author

Wint, G.R. William, primary, Balenghien, Thomas, additional, Berriatua, Eduardo, additional, Braks, Marieta, additional, Marsboom, Cedric, additional, Medlock, Jolyon, additional, Schaffner, Francis, additional, Van Bortel, Wim, additional, Alexander, Neil, additional, Alten, Bulent, additional, Czwienczek, Ewelina, additional, Dhollander, Sofie, additional, Ducheyne, Els, additional, Gossner, Celine M., additional, Hansford, Kayleigh, additional, Hendrickx, Guy, additional, Honrubia, Hector, additional, Matheussen, Tom, additional, Mihalca, Andrei Daniel, additional, Petric, Dusan, additional, Richardson, Jane, additional, Sprong, Hein, additional, Versteirt, Veerle, additional, and Briet, Olivier, additional

Published
2023
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10. VectorNet:collaborative mapping of arthropod disease vectors in Europe and surrounding areas since 2010

Author

Wint, G. R.William, Balenghien, Thomas, Berriatua, Eduardo, Braks, Marieta, Marsboom, Cedric, Medlock, Jolyon, Schaffner, Francis, Van Bortel, Wim, Alexander, Neil, Alten, Bulent, Czwienczek, Ewelina, Dhollander, Sofie, Ducheyne, Els, Gossner, Celine M., Hansford, Kayleigh, Hendrickx, Guy, Honrubia, Hector, Matheussen, Tom, Mihalca, Andrei Daniel, Petric, Dusan, Richardson, Jane, Sprong, Hein, Versteirt, Veerle, Briet, Olivier, Bødker, René, Wint, G. R.William, Balenghien, Thomas, Berriatua, Eduardo, Braks, Marieta, Marsboom, Cedric, Medlock, Jolyon, Schaffner, Francis, Van Bortel, Wim, Alexander, Neil, Alten, Bulent, Czwienczek, Ewelina, Dhollander, Sofie, Ducheyne, Els, Gossner, Celine M., Hansford, Kayleigh, Hendrickx, Guy, Honrubia, Hector, Matheussen, Tom, Mihalca, Andrei Daniel, Petric, Dusan, Richardson, Jane, Sprong, Hein, Versteirt, Veerle, Briet, Olivier, and Bødker, René

Abstract

Background: Arthropod vectors such as ticks, mosquitoes, sandflies and biting midges are of public and veterinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas. Aim: We aim to describe the methodology underlying VectorNet maps, encourage standardisation and evaluate output. Methods: Vector distribution and surveillance activity data have been collected since 2010 from a combination of literature searches, field-survey data by entomologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively validated during data entry and mapping processes. Results: As of 2021, the VectorNet archive consisted of ca 475,000 records relating to> 330 species. Maps for 42 species are routinely produced online at subnational administrative unit resolution. On VectorNet maps, there are relatively few areas where surveillance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5–10 times as many records overall, although three species are better represented in the other databases. In addition, VectorNet maps show where species are absent. VectorNet’s impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public. Conclusion: VectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.

Published
2023

11. VectorNet: Collaborative mapping of arthropod disease vectors in Europe and surrounding areas since 2010

Author

Wint, William, Balenghien, Thomas, Berriatua, Eduardo, Braks, Marieta, Marsboom, Cedric, Medlock, Jolyon, Schaffner, Francis, Van Bortel, Wim, Alexander, Neil, Alten, Bulent, Czwienczek, Ewelina, Dhollander, Sofie, Ducheyne, Els, Gossner, Céline M., Hansford, Kayleigh M., Hendrickx, Guy, Honrubia, Hector, Matheussen, Tom, Mihalca, Andrei Daniel, Petric, Dusan, Richardson, Jane, Sprong, Hein, Versteirt, Veerle, Briët, Olivier, Wint, William, Balenghien, Thomas, Berriatua, Eduardo, Braks, Marieta, Marsboom, Cedric, Medlock, Jolyon, Schaffner, Francis, Van Bortel, Wim, Alexander, Neil, Alten, Bulent, Czwienczek, Ewelina, Dhollander, Sofie, Ducheyne, Els, Gossner, Céline M., Hansford, Kayleigh M., Hendrickx, Guy, Honrubia, Hector, Matheussen, Tom, Mihalca, Andrei Daniel, Petric, Dusan, Richardson, Jane, Sprong, Hein, Versteirt, Veerle, and Briët, Olivier

Abstract

Background: Arthropod vectors such as ticks, mosquitoes, sandflies and biting midges are of public and veterinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas. Aim: We aim to describe the methodology underlying VectorNet maps, encourage standardisation and evaluate output. Methods: Vector distribution and surveillance activity data have been collected since 2010 from a combination of literature searches, field-survey data by entomologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively validated during data entry and mapping processes. Results: As of 2021, the VectorNet archive consisted of ca 475,000 records relating to > 330 species. Maps for 42 species are routinely produced online at subnational administrative unit resolution. On VectorNet maps, there are relatively few areas where surveillance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5–10 times as many records overall, although three species are better represented in the other databases. In addition, VectorNet maps show where species are absent. VectorNet's impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public. Conclusion: VectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.

Published
2023

12. Constraints of using historical data for modelling the spatial distribution of helminth parasites in ruminants

Author

Hendrickx Alizée, Marsboom Cedric, Rinaldi Laura, Vineer Hannah Rose, Morgoglione Maria Elena, Sotiraki Smaragda, Cringoli Giuseppe, Claerebout Edwin, and Hendrickx Guy

Subjects
dicrocoelium dendriticum, ruminants, italy, distribution, prevalence, spatial modeling, Infectious and parasitic diseases, RC109-216
Abstract

Dicrocoelium dendriticum is a trematode that infects ruminant livestock and requires two different intermediate hosts to complete its lifecycle. Modelling the spatial distribution of this parasite can help to improve its management in higher risk regions. The aim of this research was to assess the constraints of using historical data sets when modelling the spatial distribution of helminth parasites in ruminants. A parasitological data set provided by CREMOPAR (Napoli, Italy) and covering most of Italy was used in this paper. A baseline model (Random Forest, VECMAP®) using the entire data set was first used to determine the minimal number of data points needed to build a stable model. Then, annual distribution models were computed and compared with the baseline model. The best prediction rate and statistical output were obtained for 2012 and the worst for 2016, even though the sample size of the former was significantly smaller than the latter. We discuss how this may be explained by the fact that in 2012, the samples were more evenly geographically distributed, whilst in 2016 most of the data were strongly clustered. It is concluded that the spatial distribution of the input data appears to be more important than the actual sample size when computing species distribution models. This is often a major issue when using historical data to develop spatial models. Such data sets often include sampling biases and large geographical gaps. If this bias is not corrected, the spatial distribution model outputs may display the sampling effort rather than the real species distribution.

Published
2021
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14. Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, primary, Siljander, Mika, additional, Lindén, Andreas, additional, Sormunen, Jani J., additional, Aalto, Juha, additional, Hendrickx, Guy, additional, Kallio, Eva, additional, Vajda, Andrea, additional, Gregow, Hilppa, additional, Henttonen, Heikki, additional, Marsboom, Cedric, additional, Korhonen, Essi M., additional, Sironen, Tarja, additional, Pellikka, Petri, additional, and Vapalahti, Olli, additional

Published
2022
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16. VectorNet: Putting vectors on the map

Author

Braks, Marieta, Schaffner, Francis, Medlock, Jolyon, Berriatua, Eduardo, Balenghien, Thomas, Mihalca, Andrei Daniel, Hendrickx, Guy, Marsboom, Cedric, Van Bortel, Wim, Smallegange, Renate C., Sprong, Hein, Gossner, Céline M., Czwienczek, Ewelina, Dhollander, Sofie, Briët, Olivier, Wint, William, Braks, Marieta, Schaffner, Francis, Medlock, Jolyon, Berriatua, Eduardo, Balenghien, Thomas, Mihalca, Andrei Daniel, Hendrickx, Guy, Marsboom, Cedric, Van Bortel, Wim, Smallegange, Renate C., Sprong, Hein, Gossner, Céline M., Czwienczek, Ewelina, Dhollander, Sofie, Briët, Olivier, and Wint, William

Abstract

Public and animal health authorities face many challenges in surveillance and control of vector-borne diseases. Those challenges are principally due to the multitude of interactions between vertebrate hosts, pathogens, and vectors in continuously changing environments. VectorNet, a joint project of the European Food Safety Authority (EFSA) and the European Centre for Disease Prevention and Control (ECDC) facilitates risk assessments of VBD threats through the collection, mapping and sharing of distribution data for ticks, mosquitoes, sand flies, and biting midges that are vectors of pathogens of importance to animal and/or human health in Europe. We describe the development and maintenance of this One Health network that celebrated its 10th anniversary in 2020 and the value of its most tangible outputs, the vector distribution maps, that are freely available online and its raw data on request. VectorNet encourages usage of these maps by health professionals and participation, sharing and usage of the raw data by the network and other experts in the science community. For the latter, a more complete technical description of the mapping procedure will be submitted elsewhere.

Published
2022

17. VectorNet: Putting Vectors on the Map

Author

Braks, Marieta, primary, Schaffner, Francis, additional, Medlock, Jolyon M., additional, Berriatua, Eduardo, additional, Balenghien, Thomas, additional, Mihalca, Andrei Daniel, additional, Hendrickx, Guy, additional, Marsboom, Cedric, additional, Van Bortel, Wim, additional, Smallegange, Renate C., additional, Sprong, Hein, additional, Gossner, Céline M., additional, Czwienczek, Ewelina, additional, Dhollander, Sofie, additional, Briët, Olivier, additional, and Wint, William, additional

Published
2022
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18. Additional file 6 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 6: Figure S5. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on environmental data.

Published
2022
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19. Additional file 4 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 4: Figure S4. The relative contributions of the explanatory variables in the data set of (a) host only, (b) environment only based on the mean ensemble model.

Published
2022
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20. Additional file 7 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 7: Figure S6. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on host data.

Published
2022
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21. Additional file 5 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 5: Table S1. The number of times each model contributed to the final ensemble in different data sets.

Published
2022
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22. Additional file 3 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 3: Figure S3. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. persulcatus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.

Published
2022
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23. Additional file 8 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 8: Figure S7. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus based on combined host and environmental data, and habitat suitability data for the other tick species.

Published
2022
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24. Additional file 2 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 2: Figure S2. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. ricinus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.

Published
2022
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25. Additional file 1 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland

Author

Uusitalo, Ruut, Siljander, Mika, Lindén, Andreas, Sormunen, Jani J., Aalto, Juha, Hendrickx, Guy, Kallio, Eva, Vajda, Andrea, Gregow, Hilppa, Henttonen, Heikki, Marsboom, Cedric, Korhonen, Essi M., Sironen, Tarja, Pellikka, Petri, and Vapalahti, Olli

Abstract

Additional file 1: Figure S1. (a) The sampling strategy for new collections in 2021 was created based on the following criteria. Subdivisions of landscape areas (Area1–Area4), CORINE land cover 2018, a 5-km buffer around existing I. persulcatus occurrences (grey circles), and a 500-m buffer around roads were used to delimit the four sampling areas (light grey lines). For each sampling area, a random sample of 25 collection locations was created depending on the relative shares of forest and meadow categories in each area. (b) The map showing the 2021 results indicates the locations where I. ricinus was found with B. burgdorferi (s.l.)-positive locations.

Published
2022
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26. Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data

Author

Uusitalo, Ruut, Siljander, Mika, Culverwell, C. Lorna, Hendrickx, Guy, Lindén, Andreas, Dub, Timothée, Aalto, Juha, Sane, Jussi, Marsboom, Cedric, Suvanto, Maija T., Vajda, Andrea, Gregow, Hilppa, Korhonen, Essi M., Huhtamo, Eili, Pellikka, Petri, Vapalahti, Olli, Department of Geosciences and Geography, Department of Virology, Veterinary Biosciences, Medicum, Earth Change Observation Laboratory (ECHOLAB), HUSLAB, Viral Zoonosis Research Unit, BioGeoClimate Modelling Lab, Helsinki One Health (HOH), Helsinki Institute of Sustainability Science (HELSUS), Veterinary Microbiology and Epidemiology, and Olli Pekka Vapalahti / Principal Investigator

Subjects
NORTHERN, TRANSMISSION, MOSQUITOS, UNCERTAINTY, Mosquito Vectors, vector-borne disease, WEST-NILE-VIRUS, Pogosta disease, DISEASE, Article, South Africa, Aedes, EPIDEMIOLOGY, Animals, predictive mapping, Finland, mosquitoes, 11832 Microbiology and virology, OCKELBO VIRUS, Alphavirus Infections, 3142 Public health care science, environmental and occupational health, disease modelling, Europe, CULEX-PIPIENS, Medicine, TORRENTIUM, Sindbis virus infection, Sindbis Virus
Abstract

Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes cinereus, Culex pipiens, Cx. torrentium and Culiseta morsitans are documented vectors. As specific treatments are not available for SINV infections, and joint symptoms may persist, the public health burden is considerable in endemic areas. To predict the environmental suitability for SINV infections in Finland, we applied a suite of geospatial and statistical modeling techniques to disease occurrence data. Using an ensemble approach, we first produced environmental suitability maps for potential SINV vectors in Finland. These suitability maps were then combined with grouse densities and environmental data to identify the influential determinants for SINV infections and to predict the risk of Pogosta disease in Finnish municipalities. Our predictions suggest that both the environmental suitability for vectors and the high risk of Pogosta disease are focused in geographically restricted areas. This provides evidence that the presence of both SINV vector species and grouse densities can predict the occurrence of the disease. The results support material for public-health officials when determining area-specific recommendations and deliver information to health care personnel to raise awareness of the disease among physicians.

Published
2021

28. List of contributors

Author

Abbaszadeh Tehrani, Nadia, AbdelRahman, Mohamed A.E., Al-Rawabdeh, Abdulla, Antoniadi, Sylvia, Antoniou, Vyron, Awawdeh, Muheeb, Chalkias, Christos, Demertzi, Isidora Isis, Detsikas, Spyridon E., Faka, Antigoni, Ghrefat, Habes, Hendrickx, Emilie, Hendrickx, Guy, Howari, Fares, Huang, Xiao, Ieronimidi, Emmanouela, Janalipour, Milad, Jiang, Bin, Kalogeropoulos, Kleomenis, Karagiannopoulou, Katerina, Karymbalis, Efthimios, Kontoes, Charalampos, Kourkouli, Penelope, Koutsoyiannis, Demetris, Li, Xiao, Louka, Panagiota, Mamasis, Nikos, Marsboom, Cedric, Nicolas, Gaëlle, Oikonomou, Emmanouil, Petri, Mina, Petropoulos, George P., Pissias, Evangelos, Polykretis, Christos, Psarogiannis, Athanasios, Shami, Farzaneh, Stathopoulos, Nikolaos, Tariq, Aqil, Tsatsaris, Andreas, Tselka, Ioanna, Tsesmelis, Demetrios E., Tsouni, Alexia, Venail, Roger, Yang, Di, Zoka, Melpomeni, and Zou, Lei

Published
2023
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29. Supplementary material 2 from: Vrebos D, Staes J, Broekx S, de Nocker L, Gabriels K, Hermy M, Liekens I, Marsboom C, Ottoy S, Van Der Biest K, van Orshoven J, Meire P (2020) Facilitating spatially-explicit assessments of ecosystem service delivery to support land use planning. One Ecosystem 5: e50540. https://doi.org/10.3897/oneeco.5.e50540

Author

Vrebos, Dirk, primary, Staes, Jan, additional, Broekx, Steven, additional, de Nocker, Leo, additional, Gabriels, Karen, additional, Hermy, Martin, additional, Liekens, Inge, additional, Marsboom, Cedric, additional, Ottoy, Sam, additional, Van Der Biest, Katrien, additional, van Orshoven, Jos, additional, and Meire, Patrick, additional

Published
2020
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30. Supplementary material 3 from: Vrebos D, Staes J, Broekx S, de Nocker L, Gabriels K, Hermy M, Liekens I, Marsboom C, Ottoy S, Van Der Biest K, van Orshoven J, Meire P (2020) Facilitating spatially-explicit assessments of ecosystem service delivery to support land use planning. One Ecosystem 5: e50540. https://doi.org/10.3897/oneeco.5.e50540

Author

Vrebos, Dirk, primary, Staes, Jan, additional, Broekx, Steven, additional, de Nocker, Leo, additional, Gabriels, Karen, additional, Hermy, Martin, additional, Liekens, Inge, additional, Marsboom, Cedric, additional, Ottoy, Sam, additional, Van Der Biest, Katrien, additional, van Orshoven, Jos, additional, and Meire, Patrick, additional

Published
2020
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32. Supplementary material 1 from: Vrebos D, Staes J, Broekx S, de Nocker L, Gabriels K, Hermy M, Liekens I, Marsboom C, Ottoy S, Van Der Biest K, van Orshoven J, Meire P (2020) Facilitating spatially-explicit assessments of ecosystem service delivery to support land use planning. One Ecosystem 5: e50540. https://doi.org/10.3897/oneeco.5.e50540

Author

Vrebos, Dirk, primary, Staes, Jan, additional, Broekx, Steven, additional, de Nocker, Leo, additional, Gabriels, Karen, additional, Hermy, Martin, additional, Liekens, Inge, additional, Marsboom, Cedric, additional, Ottoy, Sam, additional, Van Der Biest, Katrien, additional, van Orshoven, Jos, additional, and Meire, Patrick, additional

Published
2020
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33. Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Kraemer, Moritz U G; https://orcid.org/0000-0001-8838-7147, Reiner, Robert C, Brady, Oliver J, Messina, Jane P, Gilbert, Marius, Pigott, David M, Yi, Dingdong, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Davis Weaver, Nicole; https://orcid.org/0000-0002-7205-9621, Bisanzio, Donal, Perkins, T Alex, Lai, Shengjie, Lu, Xin, Jones, Peter, Coelho, Giovanini E, Carvalho, Roberta G, Van Bortel, Wim; https://orcid.org/0000-0002-6644-518X, Marsboom, Cedric, Hendrickx, Guy, Schaffner, Francis, Moore, Chester G, Nax, Heinrich H; https://orcid.org/0000-0003-1261-8134, Bengtsson, Linus, Wetter, Erik; https://orcid.org/0000-0002-5821-6651, Tatem, Andrew J, Brownstein, John S, Smith, David L; https://orcid.org/0000-0003-4367-3849, et al, Kraemer, Moritz U G; https://orcid.org/0000-0001-8838-7147, Reiner, Robert C, Brady, Oliver J, Messina, Jane P, Gilbert, Marius, Pigott, David M, Yi, Dingdong, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Davis Weaver, Nicole; https://orcid.org/0000-0002-7205-9621, Bisanzio, Donal, Perkins, T Alex, Lai, Shengjie, Lu, Xin, Jones, Peter, Coelho, Giovanini E, Carvalho, Roberta G, Van Bortel, Wim; https://orcid.org/0000-0002-6644-518X, Marsboom, Cedric, Hendrickx, Guy, Schaffner, Francis, Moore, Chester G, Nax, Heinrich H; https://orcid.org/0000-0003-1261-8134, Bengtsson, Linus, Wetter, Erik; https://orcid.org/0000-0002-5821-6651, Tatem, Andrew J, Brownstein, John S, Smith, David L; https://orcid.org/0000-0003-4367-3849, and et al

Abstract

The global population at risk from mosquito-borne diseases—including dengue, yellow fever, chikungunya and Zika—is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Published
2019

39. Planning for Ecosystem Services: the ECOPLAN toolbox

Author

Staes, Jan, Vrebos, Dirk, Marsboom, Cedric, Biest, Katrien Van Der, Boerema, Annelies, Broekx, Steven, Liekens, Inge, Nocker, Leo De, Kerchove, Ruben Van De, Delalieux, Stephanie, Bennetsen, Elina, Landuyt, Dries, Verheyden, Wim, Meyer, Rolinde De, Mortelmans, Dieter, Keune, Hans, Jacobs, Sander, Tirry, Diederik, Jacxsens, Paul, Ottoy, Sam, Gabriels, Karen, Dangol, Anuja, Turkelboom, Francis, Goethals, Peter, Orshoven, Jos Van, Hermy, Martin, and Meire, Patrick

Published
2016
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41. Initiating a collaborative monitoring system to survey Maltese orchids

Author

Cutajar, Simone, Thomas Sebrechts, Bennett, Charles, Scholier, Tiffany, Festjens, Felien, Marsboom, Cedric, Mifsud, Stephen, Burdekin, Oliver, Jocque, Merlijn, and Th International Congress On Biodiversity 'man, Natural Habitats And Euro-Mediterranean Biodiversity'

Subjects
Orchids -- Malta
Abstract

Orchids have always garnered the interest of enthusiastic amateurs and nonprofessional researchers as a charismatic species group and have become a flagship for Mediterranean flora. At the same time they are a decent indicator for biodiversity and environmental quality through their association with specific pollinators and mycorrhizal fungi. Historical records for orchids occurring in the Maltese Islands number some 30 different species, but there is little to no comprehensive data on their abundance and distribution., peer-reviewed

42. Seasonality and timing of peak abundance of <em>Aedes albopictus</em> in Europe: Implications to public and animal health.

Author

Petrić M, Ducheyne E, Gossner CM, Marsboom C, Nicolas G, Venail R, Hendrickx G, and Schaffner F

Subjects
Animals, Europe, Mosquito Vectors, Population Dynamics, Seasons, Aedes
Abstract

Aedes albopictus is a known vector of dengue and chikungunya. Understanding the population dynamics characteristics of vector species is of pivotal importance to optimise surveillance and control activities, to estimate risk for pathogen-transmission, and thus to enhance support of public health decisions. In this paper we used a seasonal activity model to simulate the start (spring hatching) and end (autumn diapause) of the vector season. In parallel, the peak abundance of the species was assessed using both VectorNet field survey data complemented with field studies obtained from literature across the Mediterranean Basin. Our results suggest that spring hatching of eggs in the current distribution area can start at the beginning of March in southern Europe and in April in western Europe. In northern Europe, where the species is not (yet) present, spring hatching would occur from late April to late May. Aedes albopictus can remain active up to 41 weeks in southern Europe whilst the climatic conditions in northern Europe are limiting its potential activity to a maximum of 23 weeks. The peak of egg density is found during summer months from end of July until end of September. During these two months the climatic conditions for species development are optimal, which implies a higher risk for arbovirus transmission by Ae. albopictus and occurrence of epidemics.

Published
2021
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