A big-data spatial, temporal and network analysis of bovine tuberculosis between wildlife (badgers) and cattle

  • Aristides MoustakasEmail author
  • Matthew R. Evans
Original Paper


Bovine tuberculosis (TB) poses a serious threat for agricultural industry in several countries, it involves potential interactions between wildlife and cattle and creates societal problems in terms of human-wildlife conflict. This study addresses connectedness network analysis, the spatial, and temporal dynamics of TB between cattle in farms and the European badger (Meles meles) using a large dataset generated by a calibrated agent based model. Results showed that infected network connectedness was lower in badgers than in cattle. The contribution of an infected individual to the mean distance of disease spread over time was considerably lower for badger than cattle; badgers mainly spread the disease locally while cattle infected both locally and across longer distances. The majority of badger-induced infections occurred when individual badgers leave their home sett, and this was positively correlated with badger population growth rates. Point pattern analysis indicated aggregation in the spatial pattern of TB prevalence in badger setts across all scales. The spatial distribution of farms that were not TB free was aggregated at different scales than the spatial distribution of infected badgers and became random at larger scales. The spatial cross correlation between infected badger setts and infected farms revealed that generally infected setts and farms do not coexist except at few scales. Temporal autocorrelation detected a two year infection cycle for badgers, while there was both within the year and longer cycles for infected cattle. Temporal cross correlation indicated that infection cycles in badgers and cattle are negatively correlated. The implications of these results for understanding the dynamics of the disease are discussed.


Network connectedness Point pattern analysis Individual based models Veterinary epidemiology Spatial analysis Temporal correlation 



Comments of three anonymous reviewers have been exceptionally thorough and helpful. This paper is part of the special issue in Spatio-temporal Data Mining in Ecological and Veterinary Epidemiology. AM has been the guest editor for the special issue and declares that this submission was handled by regular member of the editorial board.


  1. Abernethy D, Upton P, Higgins I, McGrath G, Goodchild A, Rolfe S, Broughan J, Downs S, Clifton-Hadley R, Menzies F (2013) Bovine tuberculosis trends in the UK and the Republic of Ireland, 1995–2010. Vet Rec 172:312CrossRefGoogle Scholar
  2. Alvarez J, Goede D, Morrison R, Perez A (2016) Spatial and temporal epidemiology of porcine epidemic diarrhea (PED) in the Midwest and Southeast regions of the United States. Prev Vet Med 123:155–160CrossRefGoogle Scholar
  3. Athira P, Sudheer K (2015) A method to reduce the computational requirement while assessing uncertainty of complex hydrological models. Stoch Env Res Risk Assess 29:847–859CrossRefGoogle Scholar
  4. Augustijn EW, Doldersum T, Useya J, Augustijn D (in press) Agent-based modelling of cholera diffusion. Stoch Environ Res Risk Assess. doi:  10.1007/s00477-015-1199-x
  5. Besag J (1977) Contribution to the discussion of Dr. Ripley’s paper. J R Stat Soc B 39:193–195Google Scholar
  6. BjØrnstad ON, Falck W (2001) Nonparametric spatial covariance functions: estimation and testing. Environ Ecol Stat 8:53–70CrossRefGoogle Scholar
  7. Böhm M, Hutchings MR, White PCL (2009) Contact networks in a wildlife-livestock host community: identifying high-risk individuals in the transmission of bovine TB among badgers and cattle. PLoS One 4:e5016CrossRefGoogle Scholar
  8. Bourne J, Donnelly CA, Cox DR, Gettinby G, McInerney JP, Morrison WI, Woodroffe R (2007) Bovine TB: the scientific evidence. DEFRA, London, p 289Google Scholar
  9. Brooks-Pollock E, Roberts GO, Keeling MJ (2014) A dynamic model of bovine tuberculosis spread and control in Great Britain. Nature 511:228–231CrossRefGoogle Scholar
  10. Brunton LA, Nicholson R, Ashton A, Alexander N, Wint W, Enticott G, Ward K, Broughan JM, Goodchild AV (2015) A novel approach to mapping and calculating the rate of spread of endemic bovine tuberculosis in England and Wales. Spat Spat Temp Epidemiol 13:41–50CrossRefGoogle Scholar
  11. Byrne AW, O’Keeffe J, Green S, Sleeman DP, Corner LAL, Gormley E, Murphy D, Martin SW, Davenport J (2012) Population estimation and trappability of the European badger (Meles meles): implications for tuberculosis management. PLoS One 7:e50807CrossRefGoogle Scholar
  12. Byrne AW, Acevedo P, Green S, O’Keeffe J (2014a) Estimating badger social-group abundance in the Republic of Ireland using cross-validated species distribution modelling. Ecol Ind 43:94–102CrossRefGoogle Scholar
  13. Byrne AW, Quinn JL, O’Keeffe JJ, Green S, Paddy Sleeman D, Wayne Martin S, Davenport J (2014b) Large-scale movements in European badgers: has the tail of the movement kernel been underestimated? J Anim Ecol 83:991–1001CrossRefGoogle Scholar
  14. Byrne AW, Kenny K, Fogarty U, O’Keeffe JJ, More SJ, McGrath G, Teeling M, Martin SW, Dohoo IR (2015) Spatial and temporal analyses of metrics of tuberculosis infection in badgers (Meles meles) from the Republic of Ireland: trends in apparent prevalence. Prev Vet Med 122:345–354CrossRefGoogle Scholar
  15. Caplan P (2012) Cull or vaccinate?: badger politics in Wales (respond to this article at Anthropol Today 28:17–21
  16. Carter SP, Delahay RJ, Smith GC, Macdonald DW, Riordan P, Etherington TR, Pimley ER, Walker NJ, Cheeseman CL (2007) Culling-induced social perturbation in Eurasian badgers Meles meles and the management of TB in cattle: an analysis of a critical problem in applied ecology. Proc R Soc B 274:2769–2777CrossRefGoogle Scholar
  17. Carter SP, Chambers MA, Rushton SP, Shirley MDF, Schuchert P, Pietravalle S, Murray A, Rogers F, Gettinby G, Smith GC, Delahay RJ, Hewinson RG, McDonald RA (2012) BCG vaccination reduces risk of tuberculosis infection in vaccinated badgers and unvaccinated badger cubs. PLoS One 7:e49833CrossRefGoogle Scholar
  18. Christakos G, Olea RA, Serre ML, Yu HL, Wang LL (2006) Interdisciplinary public health reasoning and epidemic modelling: the case of black death: the case of black death. Springer, BerlinGoogle Scholar
  19. Christakos G, Wang J-F, Wu J (2014) Space–time medical mapping and causation modeling. In: Christakos G, Wang J, Wu J (eds) Stochastic medical reasoning and environmental health exposure. World Scientific, Singapore, pp 249–292CrossRefGoogle Scholar
  20. Christley R, Robinson S, Lysons R, French N (2005) Network analysis of cattle movement in Great Britain. Proc Soc Vet Epidemiol Prev Med, pp 234–243Google Scholar
  21. Claridge J, Diggle P, McCann CM, Mulcahy G, Flynn R, McNair J, Strain S, Welsh M, Baylis M, Williams DJL (2012) Fasciola hepatica is associated with the failure to detect bovine tuberculosis in dairy cattle. Nat Commun 3:853CrossRefGoogle Scholar
  22. Clifton-Hadley R (1993) The use of a geographical information system (GIS) in the control and epidemiology of bovine tuberculosis in south-west England. In: Thrusfield MV (ed) Proceedings of the society for veterinary epidemiology and preventive medicine, RoslinGoogle Scholar
  23. Conlan AJK, McKinley TJ, Karolemeas K, Pollock EB, Goodchild AV, Mitchell AP, Birch CPD, Clifton-Hadley RS, Wood JLN (2012) Estimating the hidden burden of bovine tuberculosis in Great Britain. PLoS Comput Biol 8:e1002730CrossRefGoogle Scholar
  24. Cowie CE, Gortázar C, White PCL, Hutchings MR, Vicente J (2015) Stakeholder opinions on the practicality of management interventions to control bovine tuberculosis. Vet J 204:179–185CrossRefGoogle Scholar
  25. DEFRA (2014) Request for information: bovine TB control costs. REF: 6505.
  26. DEFRA (2015) Monthly publication of national statistics on the incidence of tuberculosis (TB) in cattle to end September 2015 for Great Britain.
  27. Delahay RJ, Langton S, Smith GC, Clifton-Hadley RS, Cheeseman CL (2000) The spatio-temporal distribution of Mycobacterium bovis (bovine tuberculosis) infection in a high-density badger population. J Anim Ecol 69:428–441CrossRefGoogle Scholar
  28. Desouza K, Yuan L (2013) Towards evidence-driven policy design: complex adaptive systems and computational modeling. Annu Rev Policy Des 1:1–19Google Scholar
  29. Donnelly CA, Nouvellet P (2013) The contribution of badgers to confirmed tuberculosis in cattle in high-incidence areas in England. PLoS Curr Outbreaks. doi: 10.1371/currents.outbreaks.097a904d3f3619db2fe78d24bc776098 Google Scholar
  30. Donnelly CA, Woodroffe R (2015) Bovine tuberculosis: badger-cull targets unlikely to reduce TB. Nature 526:640CrossRefGoogle Scholar
  31. Donnelly CA, Woodroffe R, Cox DR, Bourne FJ, Cheeseman CL, Clifton-Hadley RS, Wei G, Gettinby G, Gilks P, Jenkins H, Johnston WT, Le Fevre AM, McInerney JP, Morrison WI (2006) Positive and negative effects of widespread badger culling on tuberculosis in cattle. Nature 439:843–846CrossRefGoogle Scholar
  32. Donnelly CA, Wei G, Johnston WT, Cox DR, Woodroffe R, Bourne FJ, Cheeseman CL, Clifton-Hadley RS, Gettinby G, Gilks P, Jenkins HE, Le Fevre AM, McInerney JP, Morrison ES (2007) Impacts of widespread badger culling on cattle tuberculosis: concluding analysis from a large-scale field trial. Int J Infect Dis 11:300–308CrossRefGoogle Scholar
  33. Donnelly CA, Bento AI, Goodchild AV, Downs SH (2015) Exploration of the power of routine surveillance data to assess the impacts of industry-led badger culling on bovine tuberculosis incidence in cattle herds. Vet Rec 177:417CrossRefGoogle Scholar
  34. Drewe J, O’Connor H, Weber N, McDonald R, Delahay R (2013) Patterns of direct and indirect contact between cattle and badgers naturally infected with tuberculosis. Epidemiol Infect 141:1467–1475CrossRefGoogle Scholar
  35. Eisinger D, Thulke H-H (2008) Spatial pattern formation facilitates eradication of infectious diseases. J Appl Ecol 45:415–423CrossRefGoogle Scholar
  36. Enticott G (2001) Calculating nature: the case of badgers, bovine tuberculosis and cattle. J Rural Stud 17:149–164CrossRefGoogle Scholar
  37. Enticott G (2015) Public attitudes to badger culling to control bovine tuberculosis in rural Wales. Eur J Wildl Res 61:387–398CrossRefGoogle Scholar
  38. Enticott G, Maye D, Carmody P, Naylor R, Ward K, Hinchliffe S, Wint W, Alexander N, Elgin R, Ashton A, Upton P, Nicholson R, Goodchild T, Brunton L, Broughan J (2015) Farming on the edge: farmer attitudes to bovine tuberculosis in newly endemic areas. Vet Rec 177:439CrossRefGoogle Scholar
  39. Eurostat (2009) Farm Structure Survey in the United Kingdom—2007. In: Statistics in focus.
  40. Evans MR, Bithell M, Cornell SJ, Dall SRX, Díaz S, Emmott S, Ernande B, Grimm V, Hodgson DJ, Lewis SL, Mace GM, Morecroft M, Moustakas A, Murphy E, Newbold T, Norris KJ, Petchey O, Smith M, Travis JMJ, Benton TG (2013) Predictive systems ecology. Proc R Soc B 280:20131452CrossRefGoogle Scholar
  41. Evans MR, Benton TG, Grimm V, Lessells CM, O’Malley MA, Moustakas A, Weisberg M (2014) Data availability and model complexity, generality, and utility: a reply to Lonergan. Trends Ecol Evol 29:302–303CrossRefGoogle Scholar
  42. Fan J, Han F, Liu H (2014) Challenges of big data analysis. Natl Sci Rev 1:293–314CrossRefGoogle Scholar
  43. Gilbert M, Mitchell A, Bourn D, Mawdsley J, Clifton-Hadley RS, Wint W (2005) Cattle movements and bovine tuberculosis in Great Britain. Nature 435:491–496CrossRefGoogle Scholar
  44. Goodchild AV, Downs SH, Upton P, Wood JLN, de la Rua-Domenech R (2015) Specificity of the comparative skin test for bovine tuberculosis in Great Britain. Vet Rec 177:258CrossRefGoogle Scholar
  45. Gopal R, Goodchild A, Hewinson G, de la Rua Domenech R, Clifton-Hadley R (2006) Introduction of bovine tuberculosis to north-east England by bought-in cattle. Vet Rec 159:265–271CrossRefGoogle Scholar
  46. Jenkins HE, Woodroffe R, Donnelly CA (2010) The duration of the effects of repeated widespread badger culling on cattle tuberculosis following cessation of culling. PLoS One 5:e9090CrossRefGoogle Scholar
  47. Judge J, Wilson GJ, Macarthur R, Delahay RJ, McDonald RA (2014) Density and abundance of badger social groups in England and Wales in 2011–2013. Sci Rep 4:3809CrossRefGoogle Scholar
  48. King D, Roper TJ, Young D, Woolhouse MEJ, Collins DA, Wood P (2007) Tuberculosis in cattle and badgers: a report by the Chief Scientific Advisor, Sir David King, LondonGoogle Scholar
  49. King HC, Murphy A, James P, Travis E, Porter D, Hung Y-J, Sawyer J, Cork J, Delahay RJ, Gaze W (2015) The variability and seasonality of the environmental reservoir of Mycobacterium bovis shed by wild European badgers. Sci Rep 5:12318CrossRefGoogle Scholar
  50. Knox E, Bartlett M (1964) The detection of space-time interactions. J R Stat Soc Ser C 13:25–30Google Scholar
  51. Krackhardt D (1994) Graph theoretical dimensions of informal organizations. Comput Organ Theory 89:123–140Google Scholar
  52. Krebs JR, Anderson R, Clutton-Brock T, Morrison I, Young D, Donnelly CA, Frost S, Woodroffe R (1997) Bovine tuberculosis in cattle and badgers. Report to the Rt Hon Dr Jack Cunningham MP by The Independent Scientific Review Group, LondonGoogle Scholar
  53. Krebs JR, Anderson RM, Clutton-Brock T, Donnelly CA, Frost S, Morrison WI, Woodroffe R, Young D (1998) Badgers and bovine TB: conflicts between conservation and health. Science 279:817–818CrossRefGoogle Scholar
  54. Lange M, Siemen H, Blome S, Thulke HH (2014) Analysis of spatio-temporal patterns of African swine fever cases in Russian wild boar does not reveal an endemic situation. Prev Vet Med 117:317–325CrossRefGoogle Scholar
  55. Little T, Naylor P, Wilesmith J (1982) Laboratory study of Mycobacterium bovis infection in badgers and calves. Vet Rec 111:550–557Google Scholar
  56. Lonergan M (2014) Data availability constrains model complexity, generality, and utility: a response to Evans et al. Trends Ecol Evol 29:301–302CrossRefGoogle Scholar
  57. Louca M, Vogiatzakis IN, Moustakas A (2015) Modelling the combined effects of land use and climatic changes: coupling bioclimatic modelling with Markov-chain cellular automata in a case study in Cyprus. Ecol Inform 30:241–249CrossRefGoogle Scholar
  58. Macdonald DW, Feber RE (2015) Wildlife conservation on farmland volume 2: conflict in the countryside. Oxford University Press, OxfordCrossRefGoogle Scholar
  59. Macdonald DW, Newman C, Buesching CD, Johnson PJ (2008) Male-biased movement in a high-density population of the Eurasian Badger (Meles meles). J Mammal 89:1077–1086CrossRefGoogle Scholar
  60. McKay MD, Beckman RJ, Conover WJ (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21:239–245Google Scholar
  61. Mitchell A, Bourn D, Mawdsley J, Wint W, Clifton-Hadley R, Gilbert M (2005) Characteristics of cattle movements in Britain: an analysis of records from the cattle tracing system. Anim Sci 80:265–273CrossRefGoogle Scholar
  62. Moustakas A (2015) Fire acting as an increasing spatial autocorrelation force: implications for pattern formation and ecological facilitation. Ecol Complex 21:142–149CrossRefGoogle Scholar
  63. Moustakas A, Evans MR (2013) Integrating evolution into ecological modelling: accommodating phenotypic changes in agent based models. PLoS One 8:e71125CrossRefGoogle Scholar
  64. Moustakas A, Evans M (2015) Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB). Stoch Environ Res Risk Assess 29:623–635CrossRefGoogle Scholar
  65. Moustakas A, Evans MR (2016) Regional and temporal characteristics of bovine tuberculosis of cattle in Great Britain. Stoch Environ Res Risk Assess 30:989–1003CrossRefGoogle Scholar
  66. Mullen EM, MacWhite T, Maher PK, Kelly DJ, Marples NM, Good M (2015) The avoidance of farmyards by European badgers Meles meles in a medium density population. Appl Anim Behav Sci 171:170–176CrossRefGoogle Scholar
  67. Najafabadi MM, Villanustre F, Khoshgoftaar TM, Seliya N, Wald R, Muharemagic E (2015) Deep learning applications and challenges in big data analytics. J Big Data 2:1–21CrossRefGoogle Scholar
  68. Naylor R, Manley W, Maye D, Enticott G, Ilbery B, Hamilton-Webb A (2015) The framing of public knowledge controversies in the media: a comparative analysis of the portrayal of badger vaccination in the english national, Regional and Farming Press. Sociol Ruralis Google Scholar
  69. Nisbet MC, Markowitz EM (2015) Expertise in an age of polarization evaluating scientists’ political awareness and communication behaviors. Ann Am Acad Polit Soc Sci 658:136–154CrossRefGoogle Scholar
  70. O’Mahony DT (2015) Badger (Meles meles) contact metrics in a medium-density population. Mamm Biol Zeitschrift für Säugetierkunde 80:484–490CrossRefGoogle Scholar
  71. O’Hagan MJH, Matthews DI, Laird C, McDowell SWJ (in press) Farmer beliefs about bovine tuberculosis control in Northern Ireland. Vet J  10.1016/j.tvjl.2015.10.038
  72. Parlane NA, Buddle BM (2015) Immunity and Vaccination against tuberculosis in Cattle. Curr Clin Microbiol Rep 2:44–53CrossRefGoogle Scholar
  73. Pfeiffer DU, Stevens KB (2015) Spatial and temporal epidemiological analysis in the big data era. Prev Vet Med 122:213–220CrossRefGoogle Scholar
  74. Porphyre T, McKenzie J, Stevenson MA (2011) Contact patterns as a risk factor for bovine tuberculosis infection in a free-living adult brushtail possum Trichosurus vulpecula population. Prev Vet Med 100:221–230CrossRefGoogle Scholar
  75. R Development Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0Google Scholar
  76. Reis S, Seto E, Northcross A, Quinn NWT, Convertino M, Jones RL, Maier HR, Schlink U, Steinle S, Vieno M, Wimberly MC (2015) Integrating modelling and smart sensors for environmental and human health. Environ Model Softw 74:238–246CrossRefGoogle Scholar
  77. Ribeiro-Lima J, Enns EA, Thompson B, Craft ME, Wells SJ (2015) From network analysis to risk analysis: an approach to risk-based surveillance for bovine tuberculosis in Minnesota, US. Prev Vet Med 118:328–340CrossRefGoogle Scholar
  78. Schmitt SM, Fitzgerald SD, Cooley TM, Bruning-Fann CS, Sullivan L, Berry D, Carlson T, Minnis RB, Payeur JB, Sikarskie J (1997) Bovine tuberculosis in free-ranging white-tailed deer from Michigan. J Wildl Dis 33:749–758CrossRefGoogle Scholar
  79. Schumm P, Scoglio C, Scott HM (2015) An estimation of cattle movement parameters in the Central States of the US. Comput Electron Agric 116:191–200CrossRefGoogle Scholar
  80. Smith GC, Cheeseman CL (2007) Efficacy of trapping during the initial proactive culls in the randomised badger culling trial. Vet Rec 160:723–726CrossRefGoogle Scholar
  81. Smith CM, Downs SH, Mitchell A, Hayward AC, Fry H, Le Comber SC (2015) Spatial targeting for bovine tuberculosis control: can the locations of infected cattle be used to find infected badgers? PLoS One 10:e0142710CrossRefGoogle Scholar
  82. Stoyan D, Stoyan H (1994) Fractals, random shapes and point fields: methods of geometrical statistics. Wiley, ChichesterGoogle Scholar
  83. Torgerson P, Torgerson D (2008) Does risk to humans justify high cost of fighting bovine TB? Nature 455:1029CrossRefGoogle Scholar
  84. Touloudi A, Valiakos G, Athanasiou LV, Birtsas P, Giannakopoulos A, Papaspyropoulos K, Kalaitzis C, Sokos C, Tsokana CN, Spyrou V, Petrovska L, Billinis C (2015) A serosurvey for selected pathogens in Greek European wild boar. Vet Rec Open 2:e000077CrossRefGoogle Scholar
  85. Tweddle NE, Livingstone P (1994) Bovine tuberculosis control and eradication programs in Australia and New Zealand. Vet Microbiol 40:23–39CrossRefGoogle Scholar
  86. Venables WN, Ripley BD (2002) Modern applied statistics with S, 4th edn. Springer, New York. ISBN 0-387-95457-0CrossRefGoogle Scholar
  87. Vicente J, Delahay RJ, Walker NJ, Cheeseman CL (2007) Social organization and movement influence the incidence of bovine tuberculosis in an undisturbed high-density badger Meles meles population. J Anim Ecol 76:348–360CrossRefGoogle Scholar
  88. Vordermeier HM, Jones GJ, Buddle BM, Hewinson RG, Villarreal-Ramos B (2016) Bovine tuberculosis in cattle: vaccines, DIVA tests, and host biomarker discovery. Annu Rev Anim Biosci 4:87–109CrossRefGoogle Scholar
  89. Walpole J, Papin JA, Peirce SM (2013) Multiscale computational models of complex biological systems. Annu Rev Biomed Eng 15:137–154CrossRefGoogle Scholar
  90. Weber N, Carter SP, Dall SRX, Delahay RJ, McDonald JL, Bearhop S, McDonald RA (2013) Badger social networks correlate with tuberculosis infection. Curr Biol 23:R915–R916CrossRefGoogle Scholar
  91. Wiegand T, Moloney KA (2004) Rings, circles, and null-models for point pattern analysis in ecology. Oikos 104:209–229CrossRefGoogle Scholar
  92. Woodroffe R, Donnelly CA, Johnston WT, Bourne FJ, Cheeseman CL, Clifton-Hadley RS, Cox DR, Gettinby G, Hewinson RG, Fevre AML, McInerney JP, Morrison WI (2005) Spatial association of Mycobacterium bovis infection in cattle and badgers Meles meles. J Appl Ecol 42:852–862CrossRefGoogle Scholar
  93. Woodroffe R, Donnelly CA, Cox DR, Bourne FJ, Cheeseman CL, Delahay RJ, Gettinby G, McInerney JP, Morrison WI (2006a) Effects of culling on badger Meles meles spatial organisation: implications for the control of bovine tuberculosis. J Appl Ecol 43:1–10CrossRefGoogle Scholar
  94. Woodroffe R, Donnelly CA, Jenkins HE, Johnston WT, Cox DR, Bourne FJ, Cheeseman CL, Delahay RJ, Clifton-Hadley RS, Gettinby G, Gilks P, Hewinson RG, McInerney JP, Morrison WI (2006b) Culling and cattle controls influence tuberculosis risk for badgers. Proc Natl Acad Sci 103:14713–14717CrossRefGoogle Scholar
  95. Woodroffe R, Gilks P, Johnston WT, Le Fevre AM, Cox DR, Donnelly CA, Bourne FJ, Cheeseman CL, Gettinby G, McInerney JP, Morrison WI (2008) Effects of culling on badger abundance: implications for tuberculosis control. J Zool 274:28–37Google Scholar
  96. Woodroffe R, Donnelly CA, Wei G, Cox D, Bourne FJ, Burke T, Butlin RK, Cheeseman C, Gettinby G, Gilks P (2009) Social group size affects Mycobacterium bovis infection in European badgers (Meles meles). J Anim Ecol 78:818–827CrossRefGoogle Scholar
  97. Wright DM, Reid N, Ian Montgomery W, Allen AR, Skuce RA, Kao RR (2015) Herd-level bovine tuberculosis risk factors: assessing the role of low-level badger population disturbance. Sci Rep 5:13062CrossRefGoogle Scholar
  98. Zhang H, Jin X, Wang L, Zhou Y, Shu B (2015) Multi-agent based modeling of spatiotemporal dynamical urban growth in developing countries: simulating future scenarios of Lianyungang city, China. Stoch Environ Res Risk Assess 29:63–78CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Biological and Chemical SciencesQueen Mary University of LondonLondonUK

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