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Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations

  • V. RODRÍGUEZ-PRIETO (a1), M. VICENTE-RUBIANO (a1), A. SÁNCHEZ-MATAMOROS (a1) (a2), C. RUBIO-GUERRI (a1), M. MELERO (a1), B. MARTÍNEZ-LÓPEZ (a1) (a3), M. MARTÍNEZ-AVILÉS (a1), L. HOINVILLE (a4), T. VERGNE (a5), A. COMIN (a6), B. SCHAUER (a7), F. DÓREA (a6), D. U. PFEIFFER (a5) and J. M. SÁNCHEZ-VIZCAÍNO (a1)...

Summary

In this globalized world, the spread of new, exotic and re-emerging diseases has become one of the most important threats to animal production and public health. This systematic review analyses conventional and novel early detection methods applied to surveillance. In all, 125 scientific documents were considered for this study. Exotic (n = 49) and re-emerging (n = 27) diseases constituted the most frequently represented health threats. In addition, the majority of studies were related to zoonoses (n = 66). The approaches found in the review could be divided in surveillance modalities, both active (n = 23) and passive (n = 5); and tools and methodologies that support surveillance activities (n = 57). Combinations of surveillance modalities and tools (n = 40) were also found. Risk-based approaches were very common (n = 60), especially in the papers describing tools and methodologies (n = 50). The main applications, benefits and limitations of each approach were extracted from the papers. This information will be very useful for informing the development of tools to facilitate the design of cost-effective surveillance strategies. Thus, the current literature review provides key information about the advantages, disadvantages, limitations and potential application of methodologies for the early detection of new, exotic and re-emerging diseases.

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Copyright

Corresponding author

* Author for correspondence: Mr V. Rodríguez-Prieto, VISAVET Centre and Animal Health Department, Veterinary School, Complutense University of Madrid, Madrid, Spain.

References

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1. Coker, R, et al. Towards a conceptual framework to support one-health research for policy on emerging zoonoses. Lancet Infectious Diseases 2011; 11: 326331.
2. Lloyd-Smith, JO, et al. Epidemic dynamics at the human-animal interface. Science 2009; 326: 13621367.
3. Cutler, SJ, Fooks, AR, van der Poel, WHM. Public health threat of new, reemerging, and neglected zoonoses in the industrialized world. Emerging Infectious Diseases 2010; 16: 17.
4. Hoffmann, B, et al. Novel orthobunyavirus in Cattle, Europe, 2011. Emerging Infectious Diseases 2012; 18: 469472.
5. Rabinowitz, P, et al. Animals as sentinels of bioterrorism agents. Emerging Infectious Diseases 2006; 12: 647652.
6. National Research Council. Global Infectious Disease Surveillance and Detection: Assessing the Challenges – Finding Solutions, Workshop Summary. Washington DC: The National Academies Press, 2007.
7. Hoinville, LJ, et al. Proposed terms and concepts for describing and evaluating animal-health surveillance systems. Preventive Veterinary Medicine 2013; 112: 112.
8. Binder, S, et al. Emerging infectious diseases: public health issues for the 21st century. Science 1999; 284: 13111313.
9. Emanuel, EJ. The lessons of SARS. Annals of Internal Medicine 2003; 139: 589591.
10. Kuiken, T, et al. Public health. Pathogen surveillance in animals. Science 2005; 309: 16801681.
11. Kitching, RP, Thrusfield, M, Taylor, NM. Use and abuse of mathematical models: an illustration from the 2001 foot and mouth disease epidemic in the United Kingdom. Revue Scientifique et Technique de l'Office International des Epizooties 2006; 25: 293311.
12. Kellar, JA. Portrait of the national veterinary service as a surveillance continuum. Preventive Veterinary Medicine 2005; 67: 109115.
13. Tataryn, J, Berezowski, J, Campbell, J. Animal disease surveillance. Large Animal Veterinary Rounds 2007; 7: 15.
14. Morse, SS. Public health surveillance and infectious disease detection. Biosecurity and Bioterrorism 2012; 10: 616.
15. Wagner, MM, et al. The emerging science of very early detection of disease outbreaks. Journal of Public Health Management and Practice 2001; 7: 5159.
16. Doherr, MG, Audige, L. Monitoring and surveillance for rare health-related events: a review from the veterinary perspective. Philosophical Transactions of the Royal Society of London, Series B 2001; 356: 10971106.
17. Thurmond, MC. Conceptual foundations for infectious disease surveillance. Journal of Veterinary Diagnostic Investigation 2003; 15: 501514.
18. Stark, KD, et al. Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: review of current approaches. BMC Health Services Research. Published online: 28 February 2006 . doi:10.1186/1472-6963-6-20.
19. Grindlay, DJ, Brennan, ML, Dean, RS. Searching the veterinary literature: a comparison of the coverage of veterinary journals by nine bibliographic databases. Journal of Veterinary Medical Education 2012; 39: 404412.
20. Marfin, AA, et al. Widespread West Nile virus activity, eastern United States, 2000. Emerging Infectious Diseases 2001; 7: 730765.
21. Reisen, AWK, et al. Persistence and amplification of St. Louis encephalitis virus in the Coachella valley of California, 2000–2001. Journal of Medical Entomology 2002; 39: 793805.
22. Giovannini, A, et al. Bluetongue virus surveillance in a newly infected area. Veterinaria Italiana 2004; 40: 188197.
23. Goffredo, M, et al. Entomological surveillance for bluetongue on Malta: first report of Culicoides imicola Kieffer. Veterinaria Italiana 2004; 40: 278281.
24. Purse, BV, et al. Spatial and temporal distribution of bluetongue and its Culicoides vectors in Bulgaria. Medical and Veterinary Entomology 2006; 20: 335344.
25. Racloz, V, et al. Establishment of an early warning system against bluetongue virus in Switzerland. Schweizer Archiv für Tierheilkunde 2006; 148: 593598.
26. Linthicum, KJ, et al. A Rift Valley fever risk surveillance system for Africa using remotely sensed data: potential for use on other continents. Veterinaria Italiana 2007; 43: 663674.
27. Racloz, V, et al. Use of mapping and statistical modelling for the prediction of bluetongue occurrence in Switzerland based on vector biology. Veterinaria Italiana 2007; 43: 513518.
28. Meiswinkel, R, et al. The 2006 outbreak of bluetongue in northern Europe – the entomological perspective. Preventive Veterinary Medicine 2008; 87: 5563.
29. Ogden, NH, et al. Active and passive surveillance and phylogenetic analysis of Borrelia burgdorferi elucidate the process of Lyme disease risk emergence in Canada. Environmental Health Perspectives 2010; 118: 909914.
30. Racloz, V, et al. Estimating the temporal and spatial risk of bluetongue related to the incursion of infected vectors into Switzerland. BMC Veterinary Research 2008; 10: 110.
31. Mehlhorn, H, et al. Bluetongue disease in Germany (2007–2008: monitoring of entomological aspects. Parasitology Research 2009; 105: 313319.
32. Ogden, NH, et al. Risk maps for range expansion of the Lyme disease vector, Ixodes scapularis, in Canada now and with climate change. International Journal of Health Geographics 2008; 7: 24.
33. Alba, A, et al. The ecological surveillance of West Nile virus in Catalonia: in continuous evolution. Epidémiologie et Santé Animale 2011; 59–60: 137139.
34. Capelli, G, et al. First report in Italy of the exotic mosquito species Aedes (Finlaya) koreicus, a potential vector of arboviruses and filariae. Parasites & Vectors 2011; 4: 188.
35. Savini, G, et al. Usutu virus in Italy: an emergence or a silent infection? Veterinary Microbiology 2011; 151: 264274.
36. Ba, Y, et al. Re-emergence of Rift Valley Fever virus in Barkedji (Senegal, West Africa) in 2002–2003: identification of new vectors and epidemiological implications. Journal of the American Mosquito Control Association 2012; 28: 170178.
37. Van den Hurk, AF, et al. Evolution of mosquito-based arbovirus surveillance systems in Australia. Journal of Biomedicine and Biotechnology. Published online: 11 March 2012 . doi:10.1155/2012/325659.
38. Ward, MP, et al. Infection of cattle with bluetongue viruses in Queensland, Australia: results of a sentinel herd study, 1990–1992. Veterinary Microbiology 1995; 45: 3544.
39. Eidson, M, et al. Crow deaths as a sentinel surveillance system for West Nile virus in the northeastern United States, 1999. Emerging Infectious Diseases 2001; 7: 615620.
40. Globig, A, et al. Ducks as sentinels for avian influenza in wild birds. Emerging Infectious Diseases 2009; 15: 16331636.
41. Verdugo, C, Cardona, CJ, Carpenter, TE. Simulation of an early warning system using sentinel birds to detect a change of a low pathogenic avian influenza virus (LPAIV) to high pathogenic avian influenza virus (HPAIV). Preventive Veterinary Medicine 2009; 88: 109119.
42. Shimoda, H, et al. Dogs as sentinels for human infection with Japanese encephalitis virus. Emerging Infectious Diseases 2010; 16: 11371139.
43. Ziegler, U, et al. Sentinel birds in wild-bird resting sites as potential indicators for West Nile virus infections in Germany. Archives of Virology 2010; 155: 965969.
44. Menzies, FD, et al. Risk assessment, targeted surveillance and policy formulation: practical experiences with bluetongue. Epidémiologie et Santé Animale 2011; 59–60: 113115.
45. García-Bocanegra, I, et al. Use of sentinel serosurveillance of mules and donkeys in the monitoring of West Nile virus infection. Veterinary Journal 2012; 194: 262264.
46. Buscaglia, C, et al. Avian influenza surveillance in backyard poultry of Argentina. Avian Diseases 2007; 51: 467469.
47. De Clercq, K, et al. Emergence of bluetongue serotypes in Europe, part 2: the occurrence of a BTV-11 strain in Belgium. Transboundary and Emerging Diseases 2009; 56: 355361.
48. Lv, S, et al. Invasive snails and an emerging infectious disease: results from the first national survey on Angiostrongylus cantonensis in China. PLoS Neglected Tropical Diseases 2009; 3: 18.
49. Wilking, H, et al. Chances and limitations of wild bird monitoring for the avian influenza virus H5N1 – detection of pathogens highly mobile in time and space. PLoS ONE 2009; 4: e6639.
50. Cummings, KJ, et al. Salmonella enterica serotype Cerro among dairy cattle in New York: an emerging pathogen? Foodborne Pathogens and Disease 2010; 7: 659665.
51. Bryan, HM, et al. Exposure to infectious agents in dogs in remote coastal British Columbia: possible sentinels of diseases in wildlife and humans. Canadian Journal of Veterinary Research 2011; 75: 1117.
52. Nwankiti, OO, et al. A pilot study for targeted surveillance of bovine spongiform encephalopathy in Nigeria. Transboundary and Emerging Diseases 2012; 60: 279283.
53. Radaellii, MC, et al. How to deal with an emerging vector-borne disease when it broke into a free area: the experience of bluetongue (BT) surveillance in Piedmont region. Epidémiologie et Santé Animale 2011; 59–60: 179181.
54. Schuler, KL, et al. Expansion of an exotic species and concomitant disease outbreaks: pigeon paramyxovirus in free-ranging Eurasian collared doves. EcoHealth 2012; 9: 163170.
55. Slavec, B, et al. Surveillance of influenza A viruses in wild birds in Slovenia from 2006 to 2010. Avian Diseases 2012; 56: 9991005.
56. Smith, KM, et al. Zoonotic viruses associated with illegally imported wildlife products. PLoS ONE 2012; 7: e29505.
57. Ziegler, U, et al. Monitoring of West Nile Virus infections in Germany. Zoonoses and Public Health 2012; 59: 95101.
58. Soumare, B, et al. Screening for Rift Valley fever infection in northern Somalia: a GIS based survey method to overcome the lack of sampling frame. Veterinary Microbiology 2007; 121: 249256.
59. Alba, A, et al. Assessment of different surveillance systems for avian influenza in commercial poultry in Catalonia (North-Eastern Spain). Preventive Veterinary Medicine 2011; 97: 107118.
60. Phoutrides, E, et al. The utility of animal surveillance in the detection of West Nile virus activity in Puerto Rico, 2007. Vector-Borne and Zoonotic Diseases 2011; 11: 447450.
61. Boadella, M, et al. Do wild ungulates allow improved monitoring of flavivirus circulation in Spain? Vector-Borne and Zoonotic Diseases 2012; 12: 490495.
62. Lelli, R, et al. West Nile transmission in resident birds in Italy. Transboundary and Emerging Diseases 2012; 59: 421428.
63. Makgatho, CN, McCrindle, CME, Owen, JH. Participatory rural appraisal to investigate constraints in reporting cattle mortalities in the Odi district of North West Province, South Africa. Journal of the South African Veterinary Association 2005; 76: 209213.
64. Mariner, JC, et al. Institutionalization of participatory disease surveillance in Pakistan. Tropicultura 1998; 23: 4752.
65. Ali, SN, et al. Participatory surveillance of livestock diseases in district Karachi – Pakistan. International Journal of Agriculture and Biology 2007; 8: 652656.
66. Forbes, RN, Sanson, RL, Morris, RS. Application of subjective methods to the determination of the likelihood and consequences of the entry of foot-and-mouth disease into New Zealand. New Zealand Veterinary Journal 1994; 42: 8188.
67. Pultorak, E, et al. Zoological institution participation in a West Nile virus surveillance system: implications for public health. Public Health 2011; 125: 592599.
68. Scotch, M, Rabinowitz, P, Brandt, C. State-level zoonotic disease surveillance in the United States. Zoonoses and Public Health 2011; 58: 523528.
69. Bala, A, et al. Participatory surveillance of livestock and poultry diseases in Agidi development area of Nasarawa state Nigeria. Scientific Journal of Veterinary Advances 2012; 1: 3841.
70. Ogundipe, GAT. The roles of veterinary quarantine services in monitoring the movements of animals and disease prevention in Nigeria. Nigerian Veterinary Journal 2002; 23: 115.
71. Balança, G, Hars, J. Bird reservoirs and indicators of the West Nile fever in France. Game and Wildlife Science 2004; 21: 539551.
72. Ouagal, M, et al. Comparison between active and passive surveillance within the network of epidemiological surveillance of animal diseases in Chad. Acta Tropica 2010; 116: 147151.
73. Rockx, B, et al. Syndromic surveillance in the Netherlands for the early detection of West Nile virus epidemics. Vector-Borne and Zoonotic Diseases 2012; 6: 161169.
74. Leblond, A, Hendrikx, P, Sabatier, P. West Nile virus outbreak detection using syndromic monitoring in horses. Vector-Borne and Zoonotic Diseases 2007; 7: 403410.
75. Hernández-Jover, M, et al. Evaluation of post-farm-gate passive surveillance in swine for the detection of foot and mouth disease in Australia. Preventive Veterinary Medicine 2011; 100: 171186.
76. Walker, JG, Ogola, E, Knobel, D. Piloting mobile phone-based syndromic surveillance of livestock diseases in Kenya. Epidémiologie et Santé Animale 2011; 59–60: 1921.
77. Odoi, A, et al. Application of an automated surveillance data-analysis system in a laboratory-based early-warning system for detection of an abortion outbreak in mares. American Journal of Veterinary Research 2001; 70: 247256.
78. Van Metre, DC, et al. Development of a syndromic surveillance system for detection of disease among livestock entering an auction market. Journal of the American Medical Association 2009; 234: 658664.
79. Amezcua, M del R, et al. Evaluation of a veterinary-based syndromic surveillance system implemented for swine. Canadian Journal of Veterinary Research 2010; 74: 241251.
80. Robertson, C, et al. Mobile phone-based infectious disease surveillance system, Sri Lanka. Emerging Infectious Diseases 2010: 16: 15241531.
81. Dórea, FC, et al. Syndromic surveillance using veterinary laboratory diagnostic test requests. Epidémiologie et Santé Animale 2011; 59–60: 128130.
82. Veldhuis, A, et al. The Belgian MoSS: a monitoring and surveillance system for the early detection and identification of (re-)emerging animal diseases. Epidémiologie et Santé Animale 2011; 59–60: 190192.
83. Weber, WD, et al. Development of an animal health monitoring system based on abattoir condemnation data. Epidémiologie et Santé Animale 2011; 59–60: 131133.
84. Vourc, G, et al. Detecting emerging diseases in farm animals through clinical observations. Emerging Infectious Diseases 2006; 12: 204210.
85. Alsaaod, M, Buescher, W. Using information systems in dairy farming for prevention health management. In Proceedings of the 14th International Congress of the International Society for Animal Hygiene (ISAH), Sustainable Animal Husbandry: Prevention is Better than Cure, Volume 1. Vechta: International Society for Animal Hygiene (ISAH), 2009, pp. 517520.
86. Lutz, J, et al. Using infrared thermal imaging for mass screening of production animals for early detection of febrile diseases. Epidémiologie et Santé Animale 2011; 59–60: 169170.
87. Hyder, K, et al. Use of spatiotemporal analysis of laboratory submission data to identify potential outbreaks of new or emerging diseases in cattle in Great Britain. BMC Veterinary Research 2011; 7: 14.
88. Mostashari, F, et al. Dead bird clusters as an early warning system for West Nile virus activity. Emerging Infectious Diseases 2003; 9: 641646.
89. Conte, A, et al. The use of a web-based interactive geographical information system for the surveillance of bluetongue in Italy. Revue Scientifique et Technique de l'Office International des Epizooties 2005; 24: 857868.
90. Gosselin, P, et al. The integrated system for public health monitoring of West Nile virus (ISPHM-WNV: a real-time GIS for surveillance and decision-making. International Journal of Health Geographics 2005; 4: 21.
91. Tachiiri, K, et al. Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia. International Journal of Health Geographics 2007; 21: 121.
92. Maroney, SA, et al. The evolution of internet-based map server applications in the United States Department of Agriculture, Veterinary Services. Veterinaria Italiana 2007; 43: 723730.
93. Martin, V, et al. Perspectives on using remotely-sensed imagery in predictive veterinary epidemiology and global early warning systems. Veterinaria Italiana 2007; 2: 314.
94. Shuai, J, et al. Development of a geographic information-driven real-time surveillance system for disease surveillance. Veterinaria Italiana 2007; 43: 451461.
95. Snow, LC, et al. Risk-based surveillance for H5N1 avian influenza virus in wild birds in Great Britain. Veterinary Record 2007; 161: 775781.
96. Bayot, B, et al. An online operational alert system for the early detection of shrimp epidemics at the regional level based on real-time production. Aquaculture 2008; 277: 164173.
97. Iannetti, S, et al. An integrated web system to support veterinary activities related to the management of information in epidemic emergencies. Epidémiologie et Santé Animale 2011; 59–60: 4951.
98. Martinez, M, et al. Evaluating surveillance in wild birds by the application of risk assessment of avian influenza introduction into Spain. Epidemiology and Infection 2011; 139: 9198.
99. Pinto, J, et al. An integrated tool for global disease surveillance early warning and disease control. Epidémiologie et Santé Animale 2011; 59–60: 5254.
100. Brown, EBE, et al. Assessing the risks of West Nile virus-infected mosquitoes from transatlantic aircraft: implications for disease emergence in the United Kingdom. Vector-Borne and Zoonotic Diseases 2012; 12: 310320.
101. Recuenco, S, Blanton, JD, Rupprecht, CE. A spatial model to forecast raccoon rabies emergence. Vector-Borne and Zoonotic Diseases 2012; 12: 126137.
102. Rodríguez-Prieto, V, et al. Identification of suitable areas for West Nile virus outbreaks in equid populations for application in surveillance plans: the example of the Castile and Leon region of Spain. Epidemiology and Infection 2012; 140: 16171631.
103. Thomas-Bachli, AL, et al. Suitability and limitations of portion-specific abattoir data as part of an early warning system for emerging diseases of swine in Ontario. BMC Veterinary Research 2012; 8: 3.
104. Thrush, MA, Peeler, EJ. A model to approximate lake temperature from gridded daily air temperature records and its application in risk assessment for the establishment of fish diseases in the UK. Transboundary and Emerging Diseases 2012; 60: 460471.
105. Carpenter, TE, Chrièl, M, Greiner, M. An analysis of an early-warning system to reduce abortions in dairy cattle in Denmark incorporating both financial and epidemiologic aspects. Preventive Veterinary Medicine 2007; 78: 111.
106. Broil, S, et al. Establishing an additional surveillance system for the control of classical swine fever (CSF) in domestic pigs in Rhineland-Palatinate, Germany. Epidémiologie et Santé Animale 2011; 59–60: 9899.
107. European Food Safety Authority (EFSA). Assessment of different monitoring strategies for early detection of FMD incursion in a free wild boar population area: a simulation modelling approach. EFSA Journal 2012; 10: 2656.
108. Ely, ER, et al. Evaluation of methods for measuring coverage and representativeness of an early-warning disease surveillance system. Veterinary Record 2012; 171: 423.
109. Perrin, JB, et al. Assessment of the utility of routinely collected cattle census and disposal data for syndromic surveillance. Preventive Veterinary Medicine 2012; 105: 244252.
110. Alton, GD, et al. Factors associated with whole carcass condemnation rates in provincially-inspected abattoirs in Ontario 2001–2007: implications for food animal syndromic surveillance. BMC Veterinary Research 2010; 6: 42.
111. Ludwig, A, et al. Risk factors associated with West Nile virus mortality in American crow populations in southern Quebec. Journal of Wildlife Diseases 2010; 46: 195208.
112. Kosmider, RD, et al. Detecting new and emerging diseases on livestock farms using an early detection system. Epidemiology and Infection 2011; 139: 14761485.
113. Malladi, S, et al. Moving-average trigger for early detection of rapidly increasing mortality in caged table-egg layers. Avian Diseases 2011; 55: 603610.
114. Mintiens, K, et al. Feasibility of applying syndrome surveillance algorithms to animal health and production data to improve emerging animal disease surveillance. Epidémiologie et Santé Animale 2011; 59–60: 171173.
115. Saegerman, C, Porter, SR, Humblet, M. The use of modelling to evaluate and adapt strategies for animal disease control. Revue Scientifique et Technique de l'Office International des Epizooties 2011; 30: 555569.
116. Alton, GD, et al. Suitability of bovine portion condemnations at provincially-inspected abattoirs in Ontario Canada for food animal syndromic surveillance. BMC Veterinary Research 2012, 8: 88.
117. O'Sullivan, TL, et al. Identifying an outbreak of a novel swine disease using test requests for porcine reproductive and respiratory syndrome as a syndromic surveillance tool. BMC Veterinary Research 2012; 8: 1.
118. Kloeze, H, et al. Effective animal health disease surveillance using a network-enabled approach. Transboundary and Emerging Diseases 2010; 57: 414419.
119. Robertson, C, et al. A hidden Markov Model for analysis of Frontline veterinary data for emerging zoonotic disease surveillance. PLoS ONE 2011; 6: e24833.
120. Sanson, RL, Thornton, RN. A modelling approach to the quantification of the benefits of a national surveillance programme. Preventive Veterinary Medicine 1997; 30: 3747.
121. Gonzales, JL, et al. A sero-surveillance programme for early detection of low pathogenic avian influenza outbreaks in layer chickens. Epidémiologie et Santé Animale 2011; 59–60: 161162.
122. Bajardi, P, et al. Optimizing surveillance for livestock disease spreading through animal movements. Journal of the Royal Society Interface 2012; 9: 28142825.
123. Comin, A, et al. Evaluating surveillance strategies for the early detection of low pathogenicity avian influenza infections. PLoS ONE 2012; 7: e35956.
124. Souza Monteiro, DM, et al. Robust surveillance of animal diseases: an application to the detection of bluetongue disease. Preventive Veterinary Medicine 2012; 105: 1724.
125. Hadorn, DC, Stärk, KDC. Evaluation and optimization of surveillance systems for rare and emerging infectious diseases. Veterinary Research 2008; 39: 112.
126. Bartels, CJM, van Schaik, G, Kock, P. Validity assessment of the cattle health surveillance system in the Netherlands. Epidémiologie et Santé Animale 2011; 59–60: 308311.
127. Goutard, FL, et al. Optimizing early detection of avian influenza H5N1 in backyard and free-range poultry production systems in Thailand. Preventive Veterinary Medicine 2012; 105: 223234.
128. Pan, L, et al. A neural network-based method for risk factor analysis of West Nile virus. Risk Analysis 2008; 28: 487496.
129. Lupo, C, et al. Space-time clustering of mortality notifications in Pacific oysters of Charente sluices, France, 2008–2010. Epidémiologie et Santé Animale 2011; 59–60: 166168.
130. Liu, C-H, et al. Temperature drops and the onset of severe avian influenza A H5N1 virus outbreaks. PLoS ONE 2007; 2: 48.
131. Anyamba, A, et al. Rift Valley fever potential, Arabian Peninsula. Emerging Infectious Diseases 2006; 12: 518–20.
132. Hendrikx, P, et al. OASIS: an assessment tool of epidemiological surveillance systems in animal health and food safety. Epidemiology and Infection 2011; 139: 14861496.
133. Peyre, M, et al. Evaluation of surveillance systems in animal health: the need to adapt the tools to the contexts of developing countries, results from a regional workshop in South East Asia. Epidémiologie et Santé Animale 2011; 59–60: 415417.
134. Martínez, M, et al. Risk assessment applied to Spain's prevention strategy against highly pathogenic avian influenza virus H5N1. Avian Diseases 2007; 51: 507511.
135. European Food Safety Authority (EFSA). Scientific opinion on epizootic hemorrhagic disease. EFSA Journal 2009; 7: 1418.
136. Mur, L, et al. Quantitative risk assessment for the introduction of African swine fever virus into the European Union by legal import of live pigs. Transboundary and Emerging Diseases 2012; 59: 134144.
137. Cowen, P, et al. Evaluation of ProMED-mail as an electronic early warning system for emerging animal diseases: 1996 to 2004. Journal of the American Veterinary Medical Association 2006; 229: 10901099.
138. Thrush, MA, Dunn, PL, Peeler, EJ. Monitoring emerging diseases of fish and shellfish using electronic sources. Transboundary and Emerging Diseases 2012; 59: 385394.
139. Scotch, M, Odofin, L, Rabinowitz, P. Linkages between animal and human health sentinel data. BMC Veterinary Research 2009; 9: 19.
140. Warns-Petit, E, et al. Unsupervised clustering of wildlife necropsy data for syndromic surveillance. BMC Veterinary Research 2010; 6: 56.
141. Ortiz-Pelaez, A, Pfeiffer, DU. Use of data mining techniques to investigate disease risk classification as a proxy for compromised biosecurity of cattle herds in Wales. BMC Veterinary Research 2008; 4: 24.
142. Gubernot, DM, Boyer, BL, Moses, MS. Animals as early detectors of bioevents: veterinary tools and a framework for animal-human integrated zoonotic disease surveillance. Public Health Reports 2008; 123: 300315.
143. Donahue, BC, et al. Analysis of clinical samples for early detection of classical swine fever during infection with low, moderate, and highly virulent strains in relation to the onset of clinical signs. Journal of Virological Methods 2012; 179: 108115.
144. European Commission. Commission Regulation on implementing rules for Council Directive 2000/75/EC as regards the control, monitoring, surveillance and restrictions on movements of certain animals of susceptible species in relation to bluetongue.
145. Perez, AM, et al. A web-based system for near real-time surveillance and space-time cluster analysis of foot-and-mouth disease and other animal diseases. Preventive Veterinary Medicine 2009; 91: 3945.
146. Perry, AG, et al. Modeling and syndromic surveillance for estimating weather-induced heat.related illness. Journal of Environmental Public Health 2011. doi:10.1155/2011/750236.
147. Schrell, S, et al. Local implementation of a syndromic influenza surveillance system using emergency department data in Santander, Spain. Journal of Public Health 2013; 35: 397403.
148. Josseran, L, et al. Assessment of a syndromic surveillance system based on morbidity data: results from the Oscour (R) network during a heat wave. PLoS ONE. Published online: 9 August 2010 . doi:10.1371/journal.pone.0011984.
149. Centers for Disease Control and Prevention. Surveillance in hurricane evacuation centers – Louisiana, September-October 2005. Morbidity and Mortality Weekly Report 2006; 55: 3235.
150. Elliot, AJ, et al. Syndromic surveillance to assess the potential public health impact of the Icelandic volcanic ash plume across the United Kingdom, April 2010. Eurosurveillance 2010; 15: 69.
151. Koopmans, M. Surveillance strategy for early detection of unusual infectious disease events. Current Opinion in Virology 2013; 3: 185191.
152. Racloz, V, Griot, C, Stark, KD. Sentinel surveillance systems with special focus on vector-borne diseases. Animal Health Research Reviews 2006; 7: 7179.
153. Pfeffer, M, Dobler, G. Emergence of zoonotic arboviruses by animal trade and migration. Parasites & Vectors. Published online: 8 April 2010 . doi:10.1186/1756-3305-3-35.
154. Giovannini, A. National monitoring and surveillance. Veterinaria Italiana 2006; 42: 407429.
155. Pérez de Diego, AC, Sánchez-Cordón, PJ, Sánchez-Vizcaíno, JM. Bluetongue in Spain: from the first outbreak to 2012. Transboundary and Emerging Diseases. Published online: 11 March 2013 . doi:10.1111/tbed.12068.
156. Goffredo, M, et al. Schmallenberg virus in Italy: a retrospective survey in Culicoides stored during the bluetongue Italian surveillance program. Preventive Veterinary Medicine 2013; 111: 230236.
157. Morner, T, et al. Surveillance and monitoring of wildlife diseases. Revue Scientifique et Technique de l'Office International des Epizooties 2002; 21: 6776.
158. Kuiken, T, et al. Establishing a European network for wildlife health surveillance. Revue Scientifique et Technique de l'Office International des Epizooties 2011; 30: 755761.
159. Siembieda, JL, et al. The role of wildlife in transboundary animal diseases. Animal Health Research Reviews 2011; 12: 95111.
160. Doceul, V, et al. Epidemiology, molecular virology and diagnostics of Schmallenberg virus, an emerging orthobunyavirus in Europe. Veterinary Research 2013; 44: 31.
161. Elbers, ARW, et al. The classical swine fever epidemic 1997–1998 in the Netherlands: descriptive epidemiology. Preventive Veterinary Medicine 1999; 42: 157184.
162. Mintiens, K, et al. Descriptive epidemiology of a Classical Swine Fever outbreak in the Limburg Province of Belgium in 1997. Journal of Veterinary Medicine, Series B 2001; 48: 143149.
163. Iglesias, I, et al. Identifying areas for infectious animal disease surveillance in the absence of population data: highly pathogenic avian influenza in wild bird populations of Europe. Preventive Veterinary Medicine 2010; 96: 18.
164. Martinez-Lopez, B, et al. A novel spatial and stochastic model to evaluate the within- and between-farm transmission of classical swine fever virus. I. General concepts and description of the model. Veterinary Microbiology 2011; 147: 300309.
165. Martinez-Lopez, B, et al. A novel spatial and stochastic model to evaluate the within and between farm transmission of classical swine fever virus: II Validation of the model. Veterinary Microbiology 2012; 155: 2132.
166. Martinez-Lopez, B, Perez, AM, Sanchez-Vizcaino, JM. Combined application of social network and cluster detection analyses for temporal-spatial characterization of animal movements in Salamanca, Spain. Preventive Veterinary Medicine 2009; 91: 2938.
167. Martinez-Lopez, B, Perez, AM, Sanchez-Vizcaino, JM. Identifying equine premises at high risk of introduction of vector-borne diseases using geo-statistical and space-time analyses. Preventive Veterinary Medicine 2011; 100: 100108.
168. Leung, Z, Middleton, D, Morrison, K. One Health and EcoHealth in Ontario: a qualitative study exploring how holistic and integrative approaches are shaping public health practice in Ontario. BMC Public Health 2012. Published online: 16 May 2012 . doi:10.1186/1471-2458-12-358.
169. Zinsstag, J. Convergence of EcoHealth and One Health. Ecohealth 2012; 9: 371373.

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