Spatial data of Ixodes ricinus instar abundance and nymph pathogen prevalence, Scandinavia, 2016-2017
| Autor: | Arnulf Soleng, Rene Bødker, Heidi Elisabeth Heggen Lindstedt, Lene Jung Kjær, Petter Kjellander, Madeleine Christensson, Laura Mark Jensen, Snorre Stuen, Katrine Mørk Paulsen, Malin Teräväinen, Audun Slettan, Kristin Skarsfjord Edgar, Lars Korslund, Åshild Kristine Andreassen, Kristine Klitgaard, Vivian Kjelland, Andreas Baum |
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| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Nymph Ixodes ricinus 030231 tropical medicine Zoology Library and Information Sciences Tick Scandinavian and Nordic Countries Education 03 medical and health sciences 0302 clinical medicine Abundance (ecology) parasitic diseases Animals lcsh:Science Author Correction Pathogen Ecosystem Ecological epidemiology 0303 health sciences Ecology biology Ixodes 030306 microbiology biology.organism_classification Computer Science Applications Habitat Instar lcsh:Q Statistics Probability and Uncertainty Bacterial infection Disease transmission Entomology Animal Distribution Information Systems VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480 |
| Zdroj: | Scientific Data Scientific Data, Vol 7, Iss 1, Pp 1-7 (2020) Jung Kjaer, L, Klitgaard, K, Soleng, A, Skarsfjord Edgar, K, Elisabeth Lindstedt, H H, Paulsen, K M, Kristine andreassen, Å, Korslund, L, Kjelland, V, Slettan, A, Stuen, S, Kjellander, P, Christensson, M, Teräväinen, M, Baum, A, Mark Jensen, L & Bødker, R 2020, ' Spatial data of Ixodes ricinus instar abundance and nymph pathogen prevalence, Scandinavia, 2016-2017 ', Scientific Data, vol. 7, 238 . https://doi.org/10.1038/s41597-020-00579-y Kjær, L J, Klitgaard, K, Soleng, A, Edgar, K S, Lindstedt, H E H, Paulsen, K M, Andreassen, Å K, Korslund, L, Kjelland, V, Slettan, A, Stuen, S, Kjellander, P, Christensson, M, Teräväinen, M, Baum, A, Jensen, L M & Bødker, R 2020, ' Spatial data of Ixodes ricinus instar abundance and nymph pathogen prevalence, Scandinavia, 2016–2017 ', Scientific Data, vol. 7, no. 1, 238 . https://doi.org/10.1038/s41597-020-00579-y |
| ISSN: | 2052-4463 |
| DOI: | 10.1038/s41597-020-00579-y |
| Popis: | ticks carry pathogens that can cause disease in both animals and humans, and there is a need to monitor the distribution and abundance of ticks and the pathogens they carry to pinpoint potential high risk areas for tick-borne disease transmission. In a joint Scandinavian study, we measured Ixodes ricinus instar abundance at 159 sites in southern Scandinavia in August-September, 2016, and collected 29,440 tick nymphs at 50 of these sites. We additionally measured abundance at 30 sites in August-September, 2017. We tested the 29,440 tick nymphs in pools of 10 in a Fluidigm real-time PCR chip to screen for 17 different tick-associated pathogens, 2 pathogen groups and 3 tick species. We present data on the geolocation, habitat type and instar abundance of the surveyed sites, as well as presence/absence of each pathogen in all analysed pools from the 50 collection sites and individual prevalence for each site. these data can be used alone or in combination with other data for predictive modelling and mapping of high-risk areas. Ticks carry pathogens that can cause disease in both animals and humans, and there is a need to monitor the distribution and abundance of ticks and the pathogens they carry to pinpoint potential high risk areas for tick-borne disease transmission. In a joint Scandinavian study, we measured Ixodes ricinus instar abundance at 159 sites in southern Scandinavia in August-September, 2016, and collected 29,440 tick nymphs at 50 of these sites. We additionally measured abundance at 30 sites in August-September, 2017. We tested the 29,440 tick nymphs in pools of 10 in a Fluidigm real-time PCR chip to screen for 17 different tick-associated pathogens, 2 pathogen groups and 3 tick species. We present data on the geolocation, habitat type and instar abundance of the surveyed sites, as well as presence/absence of each pathogen in all analysed pools from the 50 collection sites and individual prevalence for each site. These data can be used alone or in combination with other data for predictive modelling and mapping of high-risk areas. |
| Databáze: | OpenAIRE |
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