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Article: The Spatial Distribution of Crimean-Congo Haemorrhagic Fever and Its Potential Vectors in Europe and Beyond.

Messina, Jane Paula / Wint, G R William

2023 Volume 14, Issue 9

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 ... ...

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
Language	English
Publishing date	2023-09-17
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662247-6
ISSN	2075-4450
ISSN	2075-4450
DOI	10.3390/insects14090771
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Using Random Forest to Improve the Downscaling of Global Livestock Census Data

Nicolas, Gaëlle / Robinson, Timothy P. / Wint, G.R. William / Conchedda, Giulia / Cinardi, Giuseppina / Gilbert, Marius

PLOS ONE

2023

Keywords	livestock ; data
Publishing date	2023-03-10T14:33:33Z
Publisher	Public Library of Science
Publishing country	fr
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Perspectives on modelling the distribution of ticks for large areas: so far so good?

Estrada-Peña, Agustín / Alexander, Neil / Wint, G R William

Parasites & vectors

2016 Volume 9, Page(s) 179

Abstract: Background: This paper aims to illustrate the steps needed to produce reliable correlative modelling for arthropod vectors, when process-driven models are unavailable. We use ticks as examples because of the (re)emerging interest in the pathogens they ... ...

Abstract	Background: This paper aims to illustrate the steps needed to produce reliable correlative modelling for arthropod vectors, when process-driven models are unavailable. We use ticks as examples because of the (re)emerging interest in the pathogens they transmit. We argue that many scientific publications on the topic focus on: (i) the use of explanatory variables that do not adequately describe tick habitats; (ii) the automatic removal of variables causing internal (statistical) problems in the models without considering their ecological significance; and (iii) spatial pattern matching rather than niche mapping, therefore losing information that could be used in projections. Methods: We focus on extracting information derived from modelling the environmental niche of ticks, as opposed to pattern matching exercises, as a first step in the process of identifying the ecological determinants of tick distributions. We perform models on widely reported species of ticks in Western Palaearctic to derive a set of covariates, describing the climate niche, reconstructing a Fourier transformation of remotely-sensed information. Results: We demonstrate the importance of assembling ecological information that drives the distribution of ticks before undertaking any mapping exercise, from which this kind of information is lost. We also show how customised covariates are more relevant to tick ecology than the widely used set of "Bioclimatic Indicators" ("Biovars") derived from interpolated datasets, and provide programming scripts to easily calculate them. We demonstrate that standard pre-tailored vegetation categories also fail to describe tick habitats and are best used to describe absence rather than presence of ticks, but could be used in conjunction with the climate based suitability models. Conclusions: We stress the better performance of climatic covariates obtained from remotely sensed information as opposed to interpolated explanatory variables derived from ground measurements which are flawed with internal issues affecting modelling performance. Extracting ecological conclusions from modelling projections is necessary to gain information about the variables driving the distribution of arthropod vectors. Mapping exercises should be a secondary aim in the study of the distribution of health threatening arthropods.
MeSH term(s)	Animals ; Climate ; Entomology/methods ; Models, Statistical ; Phylogeography ; Ticks/growth & development ; Ticks/physiology
Language	English
Publishing date	2016-03-31
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2409480-8
ISSN	1756-3305 ; 1756-3305
ISSN (online)	1756-3305
ISSN	1756-3305
DOI	10.1186/s13071-016-1474-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Potential effects of climate change on members of the Palaeotropical pitcher plant family Nepenthaceae.

Gray, Laura K / Clarke, Charles / Wint, G R William / Moran, Jonathan A

PloS one

2017 Volume 12, Issue 8, Page(s) e0183132

Abstract: Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of ... ...

Abstract	Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them.
MeSH term(s)	Climate Change ; Ecosystem ; Magnoliopsida/physiology ; Models, Biological ; Tropical Climate
Language	English
Publishing date	2017
Publishing country	United States
Document type	Journal Article
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0183132
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Article ; Online: Predictive gravity models of livestock mobility in Mauritania: The effects of supply, demand and cultural factors.

Nicolas, Gaëlle / Apolloni, Andrea / Coste, Caroline / Wint, G R William / Lancelot, Renaud / Gilbert, Marius

PloS one

2018 Volume 13, Issue 7, Page(s) e0199547

Abstract: Animal movements are typically driven by areas of supply and demand for animal products and by the seasonality of production and demand. As animals can potentially spread infectious diseases, disease prevention can benefit from a better understanding of ... ...

Abstract	Animal movements are typically driven by areas of supply and demand for animal products and by the seasonality of production and demand. As animals can potentially spread infectious diseases, disease prevention can benefit from a better understanding of the factors influencing movements patterns in space and time. In Mauritania, an important cultural event, called the Tabaski (Aïd el Kebir) strongly affects timing and structure of movements, and due to the arid and semi-arid climatic conditions, the season can also influence movement patterns. In order to better characterize the animal movements patterns, a survey was carried out in 2014, and those data were analysed here using social network analysis (SNA) metrics and used to train predictive gravity models. More specifically, we aimed to contrast the movements structure by ruminant species, season (Tabaski vs. Non-Tabaski) and mode of transport (truck vs. foot). The networks differed according to the species, and to the season, with a changed proportion of truck vs. foot movements. The gravity models were able to predict the probability of a movement link between two locations with moderate to good accuracy (AUC ranging from 0.76 to 0.97), according to species, seasons, and mode of transport, but we failed to predict the traded volume of those trade links. The significant predictor variables of a movement link were the human and sheep population at the source and origin, and the distance separating the locations. Though some improvements would be needed to predict traded volumes and better account for the barriers to mobility, the results provide useful predictions to inform epidemiological models in space and time, and, upon external validation, could be useful to predict movements at a larger regional scale.
MeSH term(s)	Algorithms ; Animal Migration ; Animals ; Biodiversity ; Geography ; Humans ; Livestock ; Logistic Models ; Mauritania ; Models, Theoretical ; Population Dynamics
Language	English
Publishing date	2018-07-18
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0199547
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Using imperfect data in predictive mapping of vectors: a regional example of Ixodes ricinus distribution.

Ribeiro, Rita / Eze, Jude I / Gilbert, Lucy / Wint, G R William / Gunn, George / Macrae, Alastair / Medlock, Jolyon M / Auty, Harriet

Parasites & vectors

2019 Volume 12, Issue 1, Page(s) 536

Abstract: Background: Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term ... ...

Abstract	Background: Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term geographically extensive distribution tick data are limited, mapping often relies on datasets collected for other purposes. We compared the modelled distributions derived from three datasets with information on I. ricinus distribution (quantitative I. ricinus count data from scientific surveys; I. ricinus presence-only data from public submissions; and a combined I. ricinus dataset from multiple sources) to assess which could be reliably used to inform Public Health strategy. The outputs also illustrate the strengths and limitations of these three types of data, which are commonly used in mapping tick distributions. Methods: Using the Integrated Nested Laplace algorithm we predicted I. ricinus abundance and presence-absence in Scotland and tested the robustness of the predictions, accounting for errors and uncertainty. Results: All models fitted the data well and the covariate predictors for I. ricinus distribution, i.e. deer presence, temperature, habitat, index of vegetation, were as expected. Differences in the spatial trend of I. ricinus distribution were evident between the three predictive maps. Uncertainties in the spatial models resulted from inherent characteristics of the datasets, particularly the number of data points, and coverage over the covariate range used in making the predictions. Conclusions: Quantitative I. ricinus data from scientific surveys are usually considered to be gold standard data and we recommend their use where high data coverage can be achieved. However in this study their value was limited by poor data coverage. Combined datasets with I. ricinus distribution data from multiple sources are valuable in addressing issues of low coverage and this dataset produced the most appropriate map for national scale decision-making in Scotland. When mapping vector distributions for public-health decision making, model uncertainties and limitations of extrapolation need to be considered; these are often not included in published vector distribution maps. Further development of tools to better assess uncertainties in the models and predictions are necessary to allow more informed interpretation of distribution maps.
MeSH term(s)	Animal Distribution ; Animals ; Arthropod Vectors ; Data Accuracy ; Data Analysis ; Deer ; Ecosystem ; Ixodes ; Models, Statistical ; Public Health ; Scotland ; Tick-Borne Diseases/prevention & control ; Tick-Borne Diseases/transmission
Language	English
Publishing date	2019-11-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2409480-8
ISSN	1756-3305 ; 1756-3305
ISSN (online)	1756-3305
ISSN	1756-3305
DOI	10.1186/s13071-019-3784-1
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Article ; Online: VectorNet: collaborative mapping of arthropod disease vectors in Europe and surrounding areas since 2010.

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

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin

2023 Volume 28, Issue 26

Abstract: BackgroundArthropod 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 ... ...

Abstract	BackgroundArthropod 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.AimWe 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.ResultsAs 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.ConclusionVectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.
MeSH term(s)	Humans ; Animals ; Arthropods ; Mosquito Vectors ; Disease Vectors ; Arthropod Vectors ; Europe/epidemiology
Language	English
Publishing date	2023-06-20
Publishing country	Sweden
Document type	Journal Article
ZDB-ID	1338803-4
ISSN	1560-7917 ; 1025-496X
ISSN (online)	1560-7917
ISSN	1025-496X
DOI	10.2807/1560-7917.ES.2023.28.26.2200666
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Article: Using imperfect data in predictive mapping of vectors: a regional example of Ixodes ricinus distribution

Ribeiro, Rita / Eze, Jude I / Gilbert, Lucy / Wint, G. R. William / Gunn, George / Macrae, Alastair / Medlock, Jolyon M / Auty, Harriet

Parasites & vectors. 2019 Dec., v. 12, no. 1

2019

Abstract: BACKGROUND: Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term ... ...

Abstract	BACKGROUND: Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term geographically extensive distribution tick data are limited, mapping often relies on datasets collected for other purposes. We compared the modelled distributions derived from three datasets with information on I. ricinus distribution (quantitative I. ricinus count data from scientific surveys; I. ricinus presence-only data from public submissions; and a combined I. ricinus dataset from multiple sources) to assess which could be reliably used to inform Public Health strategy. The outputs also illustrate the strengths and limitations of these three types of data, which are commonly used in mapping tick distributions. METHODS: Using the Integrated Nested Laplace algorithm we predicted I. ricinus abundance and presence–absence in Scotland and tested the robustness of the predictions, accounting for errors and uncertainty. RESULTS: All models fitted the data well and the covariate predictors for I. ricinus distribution, i.e. deer presence, temperature, habitat, index of vegetation, were as expected. Differences in the spatial trend of I. ricinus distribution were evident between the three predictive maps. Uncertainties in the spatial models resulted from inherent characteristics of the datasets, particularly the number of data points, and coverage over the covariate range used in making the predictions. CONCLUSIONS: Quantitative I. ricinus data from scientific surveys are usually considered to be gold standard data and we recommend their use where high data coverage can be achieved. However in this study their value was limited by poor data coverage. Combined datasets with I. ricinus distribution data from multiple sources are valuable in addressing issues of low coverage and this dataset produced the most appropriate map for national scale decision-making in Scotland. When mapping vector distributions for public-health decision making, model uncertainties and limitations of extrapolation need to be considered; these are often not included in published vector distribution maps. Further development of tools to better assess uncertainties in the models and predictions are necessary to allow more informed interpretation of distribution maps.
Keywords	Ixodes ricinus ; Lyme disease ; algorithms ; data collection ; decision making ; deer ; habitats ; model uncertainty ; models ; monitoring ; prediction ; public health ; risk management ; surveys ; temperature ; ticks ; vegetation ; Scotland
Language	English
Dates of publication	2019-12
Size	p. 536.
Publishing place	BioMed Central
Document type	Article
ZDB-ID	2409480-8
ISSN	1756-3305
ISSN	1756-3305
DOI	10.1186/s13071-019-3784-1
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Using Random Forest to Improve the Downscaling of Global Livestock Census Data.

Nicolas, Gaëlle / Robinson, Timothy P / Wint, G R William / Conchedda, Giulia / Cinardi, Giuseppina / Gilbert, Marius

PloS one

2016 Volume 11, Issue 3, Page(s) e0150424

Abstract: Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the ...

Abstract	Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW) database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version). The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF) instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita) could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2). RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0) will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural and agricultural populations.
MeSH term(s)	Animals ; Databases, Factual ; Livestock ; Models, Theoretical
Language	English
Publishing date	2016-03-15
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0150424
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010.

Gilbert, Marius / Nicolas, Gaëlle / Cinardi, Giusepina / Van Boeckel, Thomas P / Vanwambeke, Sophie O / Wint, G R William / Robinson, Timothy P

Scientific data

2018 Volume 5, Page(s) 180227

Abstract: Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the ...

Abstract	Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.
MeSH term(s)	Agriculture/statistics & numerical data ; Animals ; Buffaloes ; Cattle ; Chickens ; Ducks ; Goats ; Horses ; Livestock ; Population Density ; Sheep ; Swine
Language	English
Publishing date	2018-10-30
Publishing country	England
Document type	Dataset ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2775191-0
ISSN	2052-4463 ; 2052-4463
ISSN (online)	2052-4463
ISSN	2052-4463
DOI	10.1038/sdata.2018.227
Database	MEDical Literature Analysis and Retrieval System OnLINE

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