Predicting ectotherm disease vector spread-benefits from multidisciplinary approaches and directions forward

Naturwissenschaften

Volumn 100, Issue 5, 2013, Pages 395-405

  Thomas, Stephanie Margarete ^a   Beierkuhnlein, Carl ^a  

^a UNIVERSITY OF BAYREUTH   (Germany)

Author keywords

Arthropod vectors; Climate change; Global change; Species distribution model; Zoonoses

Indexed keywords

ARTHROPOD; CLIMATE CHANGE; DATA ACQUISITION; DECISION ANALYSIS; DISEASE INCIDENCE; DISEASE VECTOR; ECTOTHERMY; GLOBAL CHANGE; INTERPOLATION; REPRODUCTION; RISK ASSESSMENT; SPECIES INVENTORY;

ANIMAL; ARTICLE; DISEASE CARRIER; HOST PATHOGEN INTERACTION; INTERDISCIPLINARY COMMUNICATION; PHYSIOLOGY; PUBLICATION; REGRESSION ANALYSIS; RESEARCH; RISK ASSESSMENT; STATISTICS; THEORETICAL MODEL;

ANIMALS; DISEASE VECTORS; HOST-PATHOGEN INTERACTIONS; INTERDISCIPLINARY COMMUNICATION; MODELS, THEORETICAL; PERIODICALS AS TOPIC; REGRESSION ANALYSIS; RESEARCH; RISK ASSESSMENT;

ARTHROPODA;

EID: 84877737882     PISSN: 00281042     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00114-013-1039-0     Document Type: Article

References (66)

1. Andreo V, Glass G, Shields T, Provensal C, Polop J (2011) Modeling potential distribution of Oligoryzomys longicaudatus, the Andes Virus (Genus: Hantavirus) reservoir, in Argentina. Eco Health 3:332-348
2. Barbazan P, Guiserix M, Boonyuan W, Tuntaprasart W, Pontier D, Gonzalez JP (2010) Modelling the effect of temperature on transmission of dengue. Med Vet Entomol 24:66-73
3. Beltrán-Alcrudo D (2013) Dealing with the Biocomplexity of EIDs: An Ecosystem Heath Approach. International Meeting on Emerging Diseases and Surveillance IMED 15/02-18/02/13, Vienna, Austria. http://imed.isid.org/ downloads/FinalProgram.pdf. Accessed 15 March 2013
4. Benedict MQ (2007) Spread of the tiger: global risk of invasion by the mosquito Aedes albopictus. Vector-Borne Zoonotic Dis 7:76-85
5. Bergquist R (2011) New tools for epidemiology: a space odyssey. Mem Inst Oswaldo Cruz 106:892-900
6. Braks M, van der Giessen J, Kretzschmar M, van Pelt W, Scholte E-J, Reusken C, Zeller H, van Bortel W, Sprong H (2011) Towards an integrated approach in surveillance of vector-borne diseases in Europe. Parasites Vectors 4:192
7. Breiman L (2001) Random forests. Mach Learn J 45:5-32
8. Brotons L, Thuiller W, Araujo M, Hirzel A (2004) Presence-absence versus presence-only modelling methods for predicting bird habitat suitability. Ecography 27:437-448
9. Brunsdon C, Fotheringham AS, Charlton ME (1996) Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Anal 28:281-298
10. Dormann CF, McPherson JM, Araújo MB, Bivand R, Bolliger J, Carl G, Davies RG, Hirzel A, Jetz W, Kissling WD, Kühn I, Ohlemüller W, Peres-Neto PR, Reineking B, Schröder B, Schurr FM, Wilson R (2007) Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30:609-628
11. Dormann CF, Schymanski SJ, Cabral J, Chuine I, Graham C, Hartig F et al (2012) Correlation and process in species distribution models: bridging a dichotomy. J Biogeogr 39:2119-2131
12. Eisen L, Eisen RJ (2011) Using geographic information systems and decision support systems for the prediction, prevention, and control of vector-borne diseases. Annu Rev Entomol 1:41-61
13. Elith J, Leathwick JR, Hastie T (2008) A working guide to boosted regression trees. J Anim Ecol 77:802-813
14. Elith J, Kearney M, Phillips SJ (2010) The art of modelling range-shifting species. Methods Ecol Evol 1:330-342
15. European Centre for Disease Prevention and Control ECDC (2012) Guidelines for the surveillance of invasive mosquitoes. Stockholm ECDC
16. European Network for Arthropod Vector Surveillance for Human Public Health VBORNET (2012) Network of medical entomologists and public health experts http://www.vbornet.eu/index.php. Accessed 12 July 2012
17. Fischer D, Moeller P, Thomas SM, Naucke TJ, Beierkuhnlein C (2011a) Combining climatic projections and dispersal ability: a method for estimating the responses of sandfly vector species to climate change. PLoS Negl Trop Dis 11:e1407
18. Fischer D, Thomas SM, Niemitz F, Reineking B, Beierkuhnlein C (2011b) Projection of climatic suitability for Aedes albopictus Skuse (Culicidae) in Europe under climate change conditions. Glob Planet Change 78:54-64
19. Fitzpatrick MC, Hargrove W (2009) The projection of species distribution models and the problem of non-analog climate. Biodivers Conserv 18:2255-2261
20. Fort J, Porter WP, Grémillet D (2009) Thermodynamic modelling predicts energetic bottleneck for seabirds wintering in the northwest Atlantic. J Exp Biol 212:2483-2490
21. González C, Rebollar-Téllez EA, Ibáñez-Bernal S, Becker-Fauser I, Martínez-Meyer E, Peterson AT, Sánchez-Cordero V (2011) Current knowledge of Leishmania vectors in Mexico: how geographic distributions of species relate to transmission areas. Am J Trop Med Hyg 85:839-846
22. Gubbins S, Carpenter S, Baylis M, Wood JL, Mellor PS (2008) Assessing the risk of bluetongue to UK livestock: uncertainty and sensitivity analyses of a temperature-dependent model for the basic reproduction number. J R Soc Interface 20:363-371
23. Haining R, Kerry R, Oliver MA (2010) Geography, spatial data analysis, and geostatistics: an overview. Geographical Anal 42:7-31
24. 0) for vector-borne diseases: a case study on bluetongue virus. Epidemics 3:153-161
25. Hartemink N, Vanwambeke SO, Heesterbeek H, Rogers D, Morley D et al (2011) Integrated mapping of establishment risk for emerging vector-borne infections: a case study of canine leishmaniasis in Southwest France. PLoS One 6:e20817
26. Heffernan JM, Smith RJ, Wahl LM (2005) Perspectives on the basic reproductive ratio. J R Soc Interface 2:281-293
27. Hongoh V, Hoen AG, Aenishaenslin C, Waaub J-P, Bélanger D, Michel P, Consortium TL-MCDA (2011) Spatially explicit multi-criteria decision analysis for managing vector-borne diseases. Int J Health Geogr 10:70
28. IPCC (2012) In: Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL, Mastrandrea MD, Mach KJ, Plattner GK, Allen SK, Tignor M, Midgley PM (eds) Managing the risks of extreme events and disasters to advance climate change adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, p 582
29. Jaeschke A, Bittner T, Reinieking B, Beierkuhnlein C (2012) Can they keep up with climate change? Integrating specific dispersal abilities of protected Odonata in species distribution modelling. Insect Conserv Divers 6:93-103
30. Johnson PTJ, Hoverman JT (2012) Parasite diversity and coinfection determine pathogen infection success and host fitness. Proc Natl Acad Sci USA 23:9006-9011
31. Juliano SA, Lounibos P (2005) Ecology of invasive mosquitoes: effects on resident species and on human health. Ecol Lett 5:558-574
32. Kearney MR, Wintle BA, Porter WP (2010) Correlative and mechanistic models of species distribution provide congruent forecasts under climate change. Conserv Lett 3:203-213
33. Keesing F, Holt RD, Ostfeld RS (2006) Effects of species diversity on disease risk. Ecol Lett 4:485-498
34. Kindlmann P, Burel F (2008) Connectivity measures: a review. Landsc Ecol 23:879-890
35. Lambin EF, Tran A, Vanwambeke SO, Linard C, Soti V (2010) Pathogenic landscapes: interactions between land, people, disease vectors, and their animal hosts. Int J Health Geogr 1:54
36. Le Comber SC, Stevenson MD (2012) From Jack the Ripper to epidemiology and ecology. Trends Ecol Evol 6:307-308
37. Lin CH, Wen TH (2011) Using geographically weighted regression (GWR) to explore spatial varying relationships of immature mosquitoes and human densities with the incidence of dengue. Int J Environ Res Public Health 8:2798-2815
38. Linard C, Ponçon N, Fontenille D, Lambin EF (2009) A multi-agent simulation to assess the risk of malaria re-emergence in southern France. Ecol Model 220:160-174
39. Machado-Machado EA (2011) Empirical mapping of suitability to dengue fever in Mexico using species distribution modeling. Appl Geogr 33:82-93
40. Medley KA (2010) Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models. Glob Ecol Biogeogr 19:122-133
41. Mendoza GA, Martins H (2006) Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigm. For Ecol Manage 230:1-22
42. Moore CG (2008) Interdisciplinary research in the ecology of vector-borne diseases: opportunities and needs. J Vector Ecol 33:218-224
43. Neteler M (2010) Spatio-temporal reconstruction of satellite-based temperature maps and their application to the prediction of tick and mosquito disease vector distribution in Northern Italy. Dissertation. Leibniz University of Hannover, Germany. 145 pp
44. Ostfeld RS, Glass G, Keesing F (2005) Spatial epidemiology: An emerging (or re-emerging) discipline. Trends Ecol Evol 20:328-336
45. Paaijmans KP, Blanford S, Bell AS, Blanford JR, Read AF, Thomas MB (2010) Influence of climate on malaria transmission depends on daily temperature variation. Proc Natl Acad Sci USA 107:15135-15139
46. Patil AP, Gething PW, Piel FB, Hay SI (2011) Bayesian geostatistics in health cartography: the perspective of malaria. Trends Parasitol 6:246-253
47. Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361-371
48. Peters J, De Baets B, Van Doninck J, Calvete C, Lucientes J, De Clercq EM, Ducheyne E, Verhoest NE (2011) Absence reduction in entomological surveillance data to improve niche-based distribution models for Culicoides imicola. Prev Vet Med 100:15-28
49. Peterson AT (2003) Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects. Int J Parasit 33:919-931
50. Peterson AT (2008) Biogeography of diseases: a framework for analysis. Naturwissenschaften 6:483-491
51. Remais J, Akullian A, Ding L, Seto E (2010) Analytical methods for quantifying environmental connectivity for the control and surveillance of infectious disease spread. J R Soc Interface 49:1181-1193
52. Rocchini D, Neteler M (2012) Let the four freedoms paradigm apply to ecology. Trends Ecol Evol 6:310-311
53. Rosenthal J (2009) Climate change and the geographic distribution of infectious diseases. EcoHealth 6:489-495
54. Rubel F, Brugger K, Hantel M, Chvala-Mannsberger S, Bakonyi T, Weissenböck H, Nowotny N (2008) Explaining Usutu virus dynamics in Austria: model development and calibration. Prev Vet Med 85:166-186
55. Simmons C, Farrar J, van Vinh CN, Wills B (2012) Dengue. N Engl J Med 366:1423-1432
56. Sumilo D, Bormane A, Asokliene L, Vasilenko V, Golovljova I, Avsic-Zupanc T, Hubalek Z, Randolph SE (2008) Socio-economic factors in the differential upsurge of tick-borne encephalitis in Central and Eastern Europe. Rev Med Virol 18:81-95
57. Tjaden N, Thomas SM, Fischer D, Beierkuhnlein C (2013) Extrinsic incubation period of dengue: Knowledge, backlog and applications of temperature-dependence. Plos Neglect Trop Dis. accepted
58. Tsoar A, Allouche O, Steinitz O, Rotem D, Kadmon R (2007) A comparative evaluation of presence-only methods for modelling species distribution. Divers Distrib 13:397-405
59. Van Bortel W, Boyer S, Dekoninck W, Grootaert P, Hance T, Hendrickx G, Takken W, Versteirt H (2007) The MODIRISK project: a large scale survey on mosquito biodiversity as a basis for risk assessment and control. 4th European Mosquito Control Association (EMCA) Conference, Session 3: Climatic change and mosquito control, 11-14 September 2007, Prague, Czech Republic
60. Van der Meer F (2012) Remote-sensing image analysis and geostatistics. Int J Remote Sens 33:5644-5676
61. VanderWal J, Shoo LP, Graham C, Williams SE (2009) Selecting pseudo-absence data for presence-only distribution modeling: how far should stray from what you know? Ecol Model 220:589-594
62. Veloz SD (2009) Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models. J Biogeogr 36:2290-2299
63. Weaver SC, Reisen WK (2010) Present and future arboviral threats. Antiviral Res 2:328-345
64. Wilcox BA, Colwell RR (2005) Emerging and reemerging infectious diseases: biocomplexity as an interdisciplinary paradigm. EcoHealth 2:244-257
65. World Health Organisation WHO and, European Mosquito Control Association EMCA (2011) Guidelines for the control of invasive mosquitoes and associated vector-borne diseases on the European continent. First Draft. Speyer, Germany, 30-31 May 2011. http://www.emca-online.eu/documents/visitors/WHO2011.pdf. Accessed 12 July 2012
66. Zeimes CB, Olsson GE, Ahlm C, Vanwambeke SO (2012) Modelling zoonotic diseases in humans: comparison of methods for hantavirus in Sweden. Int J Health Geogr 11:39