https://doi.org/10.4081/gh.2015.347
Mapping and modelling helminth infections in ruminants in Europe: experience from GLOWORM
Submitted: 19 March 2015
Accepted: 19 March 2015
Published: 19 March 2015
Accepted: 19 March 2015
Abstract Views: 2207
PDF: 1319
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
How to Cite
Rinaldi, L., Hendrickx, G., Cringoli, G., Biggeri, A., Ducheyne, E., Catelan, D., … Vercruysse, J. (2015). Mapping and modelling helminth infections in ruminants in Europe: experience from GLOWORM. Geospatial Health, 9(2), 257–259. https://doi.org/10.4081/gh.2015.347
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Thandi Kapwata, Michael T. Gebreslasie, Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa , Geospatial Health: Vol. 11 No. 3 (2016)
- Manuel O. Espinosa, Francisco Polop, Camilo H. Rotela, Marcelo Abril, Carlos M. Scavuzzo, Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme , Geospatial Health: Vol. 11 No. 3 (2016)
- Nicola A. Wardrop, Matthew Geary, Patrick E. Osborne, Peter M. Atkinson, Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology , Geospatial Health: Vol. 9 No. 1 (2014)
- Olga De Cos, Valentín Castillo-Salcines, David Cantarero-Prieto, A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain , Geospatial Health: Vol. 17 No. s1 (2022): Special issue on COVID-19
- Robert Bergquist, Climate and the distribution of vector-borne diseases: what's in store? , Geospatial Health: Vol. 12 No. 1 (2017)
- Andrew J. Chamberlin, Isabel J. Jones, Andrea J. Lund, Nicolas Jouanard, Gilles Riveau, Raphaël Ndione, Susanne H. Sokolow, Chelsea L. Wood, Kevin D. Lafferty, Giulio A. De Leo, Visualization of schistosomiasis snail habitats using light unmanned aerial vehicles , Geospatial Health: Vol. 15 No. 2 (2020)
- Pandji Wibawa Dhewantara, Andri Ruliansyah, M. Ezza Azmi Fuadiyah, Endang Puji Astuti, Mutiara Widawati, Space-time scan statistics of 2007-2013 dengue incidence in Cimahi city, Indonesia , Geospatial Health: Vol. 10 No. 2 (2015)
- Jose Antonio Quesada, Inmaculada Melchor, Andreu Nolasco, Point process methods in epidemiology: application to the analysis of human immunodeficiency virus/acquired immunodeficiency syndrome mortality in urban areas , Geospatial Health: Vol. 12 No. 1 (2017)
- Robert Bergquist, Behzad Kiani, Samuel Manda, First year with COVID-19: Assessment and prospects , Geospatial Health: Vol. 15 No. 2 (2020)
- Seïdinan I. Traoré, Louise Y. Achi, Stefanie J. Krauth, Moussa Sanogo, Jakob Zinsstag, Jürg Utzinger, Eliézer K. N'Goran, Distribution of bovine Fasciola gigantica (Cobbold, 1885) in the district des Savanes, northern Côte d'Ivoire , Geospatial Health: Vol. 16 No. 2 (2021)
<< < 12 13 14 15 16 17 18 19 20 21 > >>
You may also start an advanced similarity search for this article.
