-
Predicting and mapping human risk of exposure to Ixodes ricinus nymphs using climatic and environmental data, Denmark, Norway and Sweden, 2016
- Lene Jung Kjær1 , Arnulf Soleng2 , Kristin Skarsfjord Edgar2 , Heidi Elisabeth H Lindstedt2 , Katrine Mørk Paulsen3,4 , Åshild Kristine Andreassen3 , Lars Korslund5 , Vivian Kjelland5,6 , Audun Slettan5 , Snorre Stuen7 , Petter Kjellander8 , Madeleine Christensson8 , Malin Teräväinen8 , Andreas Baum9 , Kirstine Klitgaard1 , René Bødker1
-
View Affiliations Hide AffiliationsAffiliations: 1 Department for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark, Lyngby, Denmark 2 Department of Pest Control, Norwegian Institute of Public Health, Oslo, Norway 3 Department of Virology, Norwegian Institute of Public Health, Oslo, Norway 4 Department of Production Animal Clinical Sciences, Norwegian University of Life Sciences, Oslo Norway 5 Department of Natural Sciences, University of Agder, Kristiansand, Norway 6 Sørlandet Hospital Health Enterprise, Research Unit, Kristiansand, Norway 7 Department of Production Animal Clinical Sciences, Section of Small Ruminant Research, Norwegian University of Life Sciences, Sandnes, Norway 8 Department of Ecology, Wildlife Ecology Unit, Swedish University of Agricultural Sciences, Grimsö, Sweden 9 Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, DenmarkLene Jung Kjærlenju sund.ku.dk
-
View Citation Hide Citation
Citation style for this article: Kjær Lene Jung, Soleng Arnulf, Edgar Kristin Skarsfjord, Lindstedt Heidi Elisabeth H, Paulsen Katrine Mørk, Andreassen Åshild Kristine, Korslund Lars, Kjelland Vivian, Slettan Audun, Stuen Snorre, Kjellander Petter, Christensson Madeleine, Teräväinen Malin, Baum Andreas, Klitgaard Kirstine, Bødker René. Predicting and mapping human risk of exposure to Ixodes ricinus nymphs using climatic and environmental data, Denmark, Norway and Sweden, 2016. Euro Surveill. 2019;24(9):pii=1800101. https://doi.org/10.2807/1560-7917.ES.2019.24.9.1800101 Received: 05 Mar 2018; Accepted: 01 Aug 2018
Abstract
Tick-borne diseases have become increasingly common in recent decades and present a health problem in many parts of Europe. Control and prevention of these diseases require a better understanding of vector distribution.
Our aim was to create a model able to predict the distribution of Ixodes ricinus nymphs in southern Scandinavia and to assess how this relates to risk of human exposure.
We measured the presence of I. ricinus tick nymphs at 159 stratified random lowland forest and meadow sites in Denmark, Norway and Sweden by dragging 400 m transects from August to September 2016, representing a total distance of 63.6 km. Using climate and remote sensing environmental data and boosted regression tree modelling, we predicted the overall spatial distribution of I. ricinus nymphs in Scandinavia. To assess the potential public health impact, we combined the predicted tick distribution with human density maps to determine the proportion of people at risk.
Our model predicted the spatial distribution of I. ricinus nymphs with a sensitivity of 91% and a specificity of 60%. Temperature was one of the main drivers in the model followed by vegetation cover. Nymphs were restricted to only 17.5% of the modelled area but, respectively, 73.5%, 67.1% and 78.8% of the human populations lived within 5 km of these areas in Denmark, Norway and Sweden.
The model suggests that increasing temperatures in the future may expand tick distribution geographically in northern Europe, but this may only affect a small additional proportion of the human population.
Article metrics loading...
Full text loading...
References
-
Pfäffle M, Littwin N, Muders SV, Petney TN. The ecology of tick-borne diseases. Int J Parasitol. 2013;43(12-13):1059-77. https://doi.org/10.1016/j.ijpara.2013.06.009 PMID: 23911308
-
Jore S, Vanwambeke SO, Viljugrein H, Isaksen K, Kristoffersen AB, Woldehiwet Z, et al. Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin. Parasit Vectors. 2014;7(1):11. https://doi.org/10.1186/1756-3305-7-11 PMID: 24401487
-
Skarphédinsson S, Jensen PM, Kristiansen K. Survey of tickborne infections in Denmark. Emerg Infect Dis. 2005;11(7):1055-61. https://doi.org/10.3201/eid1107.041265 PMID: 16022780
-
Jaenson TGT, Jaenson DGE, Eisen L, Petersson E, Lindgren E. Changes in the geographical distribution and abundance of the tick Ixodes ricinus during the past 30 years in Sweden. Parasit Vectors. 2012;5(1):8. https://doi.org/10.1186/1756-3305-5-8 PMID: 22233771
-
Jore S, Viljugrein H, Hofshagen M, Brun-Hansen H, Kristoffersen AB, Nygård K, et al. Multi-source analysis reveals latitudinal and altitudinal shifts in range of Ixodes ricinus at its northern distribution limit. Parasit Vectors. 2011;4(1):84. https://doi.org/10.1186/1756-3305-4-84 PMID: 21595949
-
Estrada-Peña A, de la Fuente J. The ecology of ticks and epidemiology of tick-borne viral diseases. Antiviral Res. 2014;108:104-28. https://doi.org/10.1016/j.antiviral.2014.05.016 PMID: 24925264
-
Medlock JM, Hansford KM, Bormane A, Derdakova M, Estrada-Peña A, George J-C, et al. Driving forces for changes in geographical distribution of Ixodes ricinus ticks in Europe. Parasit Vectors. 2013;6(1):1-11. https://doi.org/10.1186/1756-3305-6-1 PMID: 23281838
-
Andreassen A, Jore S, Cuber P, Dudman S, Tengs T, Isaksen K, et al. Prevalence of tick borne encephalitis virus in tick nymphs in relation to climatic factors on the southern coast of Norway. Parasit Vectors. 2012;5(1):177. https://doi.org/10.1186/1756-3305-5-177 PMID: 22913287
-
Lindgren E, Gustafson R. Tick-borne encephalitis in Sweden and climate change. Lancet. 2001;358(9275):16-8. https://doi.org/10.1016/S0140-6736(00)05250-8 PMID: 11454371
-
Public Health Agency of Sweden. TBE (Tick Borne Encephalitis) 2016. Solna: Folkhälsomyndigheten; 2017. Available from: https://www.folkhalsomyndigheten.se/folkhalsorapportering-statistik/statistikdatabaser-och-visualisering/sjukdomsstatistik/tick-borne-encephalitis-tbe/arsrapporter-och-kommentarer/2016/.
-
Paulsen KM, Pedersen BN, Soleng A, Okbaldet YB, Pettersson JH-O, Dudman SG, et al. Prevalence of tick-borne encephalitis virus in Ixodes ricinus ticks from three islands in north-western Norway. APMIS. 2015;123(9):759-64. https://doi.org/10.1111/apm.12412 PMID: 26126504
-
Soleng A, Edgar KS, Paulsen KM, Pedersen BN, Okbaldet YB, Skjetne IEB, et al. Distribution of Ixodes ricinus ticks and prevalence of tick-borne encephalitis virus among questing ticks in the Arctic Circle region of northern Norway. Ticks Tick Borne Dis. 2018;9(1):97-103. https://doi.org/10.1016/j.ttbdis.2017.10.002 PMID: 29030314
-
Jaenson TGT, Lindgren E. The range of Ixodes ricinus and the risk of contracting Lyme borreliosis will increase northwards when the vegetation period becomes longer. Ticks Tick Borne Dis. 2011;2(1):44-9. https://doi.org/10.1016/j.ttbdis.2010.10.006 PMID: 21771536
-
Jaenson TGT, Eisen L, Comstedt P, Mejlon HA, Lindgren E, Bergström S, et al. Risk indicators for the tick Ixodes ricinus and Borrelia burgdorferi sensu lato in Sweden. Med Vet Entomol. 2009;23(3):226-37. https://doi.org/10.1111/j.1365-2915.2009.00813.x PMID: 19712153
-
Zeimes CB, Olsson GE, Hjertqvist M, Vanwambeke SO. Shaping zoonosis risk: landscape ecology vs. landscape attractiveness for people, the case of tick-borne encephalitis in Sweden. Parasit Vectors. 2014;7(1):370. https://doi.org/10.1186/1756-3305-7-370 PMID: 25128197
-
European Centre for Disease Prevention and Control (ECDC). Country profile: Sweden. Tick-borne encephalitis (TBE). Stockholm: ECDC; 2012. Available from: https://ecdc.europa.eu/en/publications-data/country-profile-sweden-tick-borne-encephalitis-tbe
-
Fomsgaard A, Christiansen C, Bødker R. First identification of tick-borne encephalitis in Denmark outside of Bornholm, August 2009. Euro Surveill. 2009;14(36):1-2. PMID: 19758543
-
Fomsgaard A, Fertner ME, Essbauer S, Nielsen AY, Frey S, Lindblom P, et al. Tick-borne encephalitis virus, Zealand, Denmark, 2011. Emerg Infect Dis. 2013;19(7):1171-3. https://doi.org/10.3201/eid1907.130092 PMID: 23764123
-
Randolph SE. The shifting landscape of tick-borne zoonoses: tick-borne encephalitis and Lyme borreliosis in Europe. Philos Trans R Soc Lond B Biol Sci. 2001;356(1411):1045-56. https://doi.org/10.1098/rstb.2001.0893 PMID: 11516382
-
Hvidsten D, Stordal F, Lager M, Rognerud B, Kristiansen B-E, Matussek A, et al. Borrelia burgdorferi sensu lato-infected Ixodes ricinus collected from vegetation near the Arctic Circle. Ticks Tick Borne Dis. 2015;6(6):768-73. https://doi.org/10.1016/j.ttbdis.2015.07.002 PMID: 26187417
-
Lindström A, Jaenson TGT. Distribution of the common tick, Ixodes ricinus (Acari: Ixodidae), in different vegetation types in southern Sweden. J Med Entomol. 2003;40(4):375-8. https://doi.org/10.1603/0022-2585-40.4.375 PMID: 14680099
-
Landbo AS, Flöng PT. Borrelia burgdorferi infection in Ixodes ricinus from habitats in Denmark. Med Vet Entomol. 1992;6(2):165-7. https://doi.org/10.1111/j.1365-2915.1992.tb00596.x PMID: 1421487
-
Jensen PM, Hansen H, Frandsen F, Per Moestrup Jensen, Hanna Hansen. Spatial risk assessment for Lyme borreliosis in Denmark. Scand J Infect Dis. 2000;32(5):545-50. https://doi.org/10.1080/003655400458857 PMID: 11055662
-
Mehl R. The distribution and host relations of Norwegian ticks (Acari, Ixodides). Fauna Norv Ser B. 1983;31:46-58.
-
Estrada-Peña A, Farkas R, Jaenson TGT, Koenen F, Madder M, Pascucci I, et al. Association of environmental traits with the geographic ranges of ticks (Acari: Ixodidae) of medical and veterinary importance in the western Palearctic. A digital data set. Exp Appl Acarol. 2013;59(3):351-66. https://doi.org/10.1007/s10493-012-9600-7 PMID: 22843316
-
Brownstein JS, Holford TR, Fish D. A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States. Environ Health Perspect. 2003;111(9):1152-7. https://doi.org/10.1289/ehp.6052 PMID: 12842766
-
Estrada-Peña A. Geostatistics and remote sensing as predictive tools of tick distribution: a cokriging system to estimate Ixodes scapularis (Acari: Ixodidae) habitat suitability in the United States and Canada from advanced very high resolution radiometer satellite imagery. J Med Entomol. 1998;35(6):989-95. https://doi.org/10.1093/jmedent/35.6.989 PMID: 9835691
-
Sinka ME, Rubio-Palis Y, Manguin S, Patil AP, Temperley WH, Gething PW, et al. The dominant Anopheles vectors of human malaria in the Americas: occurrence data, distribution maps and bionomic précis. Parasit Vectors. 2010;3(1):72. https://doi.org/10.1186/1756-3305-3-72 PMID: 20712879
-
Elith J, Leathwick JR, Hastie T. A working guide to boosted regression trees. J Anim Ecol. 2008;77(4):802-13. https://doi.org/10.1111/j.1365-2656.2008.01390.x PMID: 18397250
-
Van Doninck J, De Baets B, Peters J, Hendrickx G, Ducheyne E, Verhoest N. Modelling the spatial distribution of Culicoides imicola: climatic versus remote sensing data. Remote Sens. 2014;6(7):6604-19. https://doi.org/10.3390/rs6076604
-
Ducheyne E, Miranda Chueca MA, Lucientes J, Calvete C, Estrada R, Boender GJ, et al. Abundance modelling of invasive and indigenous Culicoides species in Spain. Geospat Health. 2013;8(1):241-54. https://doi.org/10.4081/gh.2013.70 PMID: 24258899
-
Lühken R, Gethmann JM, Kranz P, Steffenhagen P, Staubach C, Conraths FJ, et al. Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany. Geospat Health. 2016;11(2):405. https://doi.org/10.4081/gh.2016.405 PMID: 27245797
-
Peters J, De Baets B, Van Doninck J, Calvete C, Lucientes J, De Clercq EM, et al. Absence reduction in entomological surveillance data to improve niche-based distribution models for Culicoides imicola. Prev Vet Med. 2011;100(1):15-28. https://doi.org/10.1016/j.prevetmed.2011.03.004 PMID: 21496932
-
Medley KA. Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models. Glob Ecol Biogeogr. 2010;19(1):122-33. https://doi.org/10.1111/j.1466-8238.2009.00497.x
-
Khatchikian C, Sangermano F, Kendell D, Livdahl T. Evaluation of species distribution model algorithms for fine-scale container-breeding mosquito risk prediction. Med Vet Entomol. 2011;25(3):268-75. https://doi.org/10.1111/j.1365-2915.2010.00935.x PMID: 21198711
-
Furlanello C, Neteler M, Merler S, Menegon S, Fontanari S, Donini A, et al. GIS and the random forest predictor: integration in R for tick-borne disease risk assessment. Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003).20-22 Mar 2003. Vienna, Austria. Available from: https://www.r-project.org/conferences/DSC-2003/Proceedings/FurlanelloEtAl.pdf
-
Springer YP, Jarnevich CS, Barnett DT, Monaghan AJ, Eisen RJ. Modeling the present and future geographic distribution of the lone star tick, Amblyomma americanum (Ixodida: Ixodidae), in the continental United States. Am J Trop Med Hyg. 2015;93(4):875-90. https://doi.org/10.4269/ajtmh.15-0330 PMID: 26217042
-
Adalsteinsson SA, D’Amico V, Shriver WG, Brisson D, Buler JJ. Scale-dependent effects of nonnative plant invasion on host-seeking tick abundance. Peters DPC, editor. Ecosphere. 2016;7(3):e01317.
-
Messina JP, Pigott DM, Golding N, Duda KA, Brownstein JS, Weiss DJ, et al. The global distribution of Crimean-Congo hemorrhagic fever. Trans R Soc Trop Med Hyg. 2015;109(8):503-13. https://doi.org/10.1093/trstmh/trv050 PMID: 26142451
-
Horobik V, Keesing F, Ostfeld RS. Abundance and Borrelia burgdorferi-infection prevalence of nymphal Ixodes scapularis ticks along forest–field edges. EcoHealth. 2006;3(4):262-8. https://doi.org/10.1007/s10393-006-0065-1
-
Jackson LE, Hilborn ED, Thomas JC. Towards landscape design guidelines for reducing Lyme disease risk. Int J Epidemiol. 2006;35(2):315-22. https://doi.org/10.1093/ije/dyi284 PMID: 16394113
-
Glass GE, Schwartz BS, Morgan JM 3rd, Johnson DT, Noy PM, Israel E. Environmental risk factors for Lyme disease identified with geographic information systems. Am J Public Health. 1995;85(7):944-8. https://doi.org/10.2105/AJPH.85.7.944 PMID: 7604918
-
Eisen RJ, Lane RS, Fritz CL, Eisen L. Spatial patterns of Lyme disease risk in California based on disease incidence data and modeling of vector-tick exposure. Am J Trop Med Hyg. 2006;75(4):669-76. https://doi.org/10.4269/ajtmh.2006.75.669 PMID: 17038692
-
MODIS v5: Temporal Fourier Analysis (TFA). Imagery update 2001-12. PALE-Blu Data Portal; 2014. Available from: https://www.edenextdata.com/?q=content/modis-v5-temporal-fourier-analysis-tfa-imagery-update-2001-12
-
Corine land cover 2006 raster data. Copernicus programme; 2010. Available from: https://www.eea.europa.eu/data-and-maps/data/clc-2006-raster
-
R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing; 2017. Available from: http://www.R-project.org/
-
Socioeconomic Data and Applications Center. Gridded Population of the World (GPW), v4. New York: Columbia University. [Accessed: 12 Aug 2017. Available from: http://sedac.ciesin.columbia.edu/data/collection/gpw-v4
-
Bernes C. Biologisk mångfald i Sverige. [Biological diversity in Sweden]. Stockholm: Naturvårdsverket; 2011. Swedish.
-
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol. 2005;25(15):1965-78. https://doi.org/10.1002/joc.1276
-
Food and Agriculture Organization (FAO), International Institute for Applied Systems Analysis (IIASA), ISRIC-World Soil Information, Institute of Soil Science, Chinese Academy of Sciences, Joint Research Centre of the European Commission. Harmonized world soil database v 1.2. Rome: FAO and Laxenburg: IIASA; 2009.
Data & Media loading...
Supplementary data
-
-
Supplement
-