Global animal disease surveillance

Abstract Development and implementation of global animal disease surveillance has been limited by the lack of information systems that enable near real-time data capturing, sharing, analysis, and related decision- and policy-making. The objective of this paper is to describe requirements for global animal disease surveillance, including design and functionality of tools and methods for visualization and analysis of animal disease data. The paper also explores the potential application of techniques for spatial and spatio-temporal analysis on global animal disease surveillance, including for example, landscape genetics, social network analysis, and Bayesian modeling. Finally, highly pathogenic avian influenza data from Denmark and Sweden are used to illustrate the potential application of a novel system (Disease BioPortal) for data sharing, visualization, and analysis for regional and global surveillance efforts.

[1]  C R Webb,et al.  Investigating the potential spread of infectious diseases of sheep via agricultural shows in Great Britain , 2005, Epidemiology and Infection.

[2]  Michael J. Ryan,et al.  Rumors of disease in the global village: outbreak verification. , 2000, Emerging infectious diseases.

[3]  J Woodall,et al.  Official versus unofficial outbreak reporting through the Internet. , 1997, International journal of medical informatics.

[4]  M. Everett,et al.  Recent network evolution increases the potential for large epidemics in the British cattle population , 2007, Journal of The Royal Society Interface.

[5]  A. Perez,et al.  Temporospatial clustering of foot-and-mouth disease outbreaks in Israel and Palestine, 2006-2007. , 2009, Transboundary and emerging diseases.

[6]  Po-Huang Chiang,et al.  Probabilistic Daily ILI Syndromic Surveillance with a Spatio-Temporal Bayesian Hierarchical Model , 2010, PloS one.

[7]  Wesley O. Johnson,et al.  Exploration of associations between governance and economics and country level foot‐and‐mouth disease status by using Bayesian model averaging , 2008 .

[8]  Mark C Thurmond,et al.  Conceptual Foundations for Infectious Disease Surveillance , 2003, Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc.

[9]  Enrico Coiera,et al.  Biosurveillance of emerging biothreats using scalable genotype clustering , 2009, J. Biomed. Informatics.

[10]  Dirk U. Pfeiffer,et al.  Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning , 2008, The Veterinary Journal.

[11]  Andres M. Perez,et al.  Spatial and phylogenetic analysis of vesicular stomatitis virus over-wintering in the United States. , 2010, Preventive veterinary medicine.

[12]  John S Brownstein,et al.  The New International Health Regulations: Considerations for Global Public Health Surveillance , 2007, Disaster Medicine and Public Health Preparedness.

[13]  Michael P Ward,et al.  Rural cases of equine West Nile virus encephalomyelitis and the normalized difference vegetation index. , 2005, Vector borne and zoonotic diseases.

[14]  Kun Chen,et al.  [Bayesian statistics in spatial epidemiology]. , 2008, Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences.

[15]  Aruna Srivastava,et al.  Application of spatial technology in malaria research & control: some new insights. , 2009, The Indian journal of medical research.

[16]  Daniel Zeng,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. , 2009, Preventive veterinary medicine.

[17]  B. Martínez-López,et al.  Social network analysis. Review of general concepts and use in preventive veterinary medicine. , 2009, Transboundary and emerging diseases.

[18]  D. Catelan,et al.  Disease mapping in veterinary epidemiology: a Bayesian geostatistical approach , 2006, Statistical methods in medical research.

[19]  M. Gilbert,et al.  The Cold European Winter of 2005–2006 Assisted the Spread and Persistence of H5N1 Influenza Virus in Wild Birds , 2010, EcoHealth.

[20]  A. Fomsgaard,et al.  First introduction of highly pathogenic H5N1 avian influenza A viruses in wild and domestic birds in Denmark, Northern Europe , 2007, Virology Journal.

[21]  I. Kiss,et al.  The network of sheep movements within Great Britain: network properties and their implications for infectious disease spread , 2006, Journal of The Royal Society Interface.

[22]  Chunju Tseng,et al.  Global Foot-and-Mouth Disease Surveillance Using BioPortal , 2007, BioSurveillance.

[23]  György Czifra,et al.  Molecular characterization of highly pathogenic H5N1 avian influenza viruses isolated in Sweden in 2006 , 2008, Virology Journal.

[24]  Michael P Ward,et al.  Spatio-temporal analysis of infectious disease outbreaks in veterinary medicine: clusters, hotspots and foci. , 2007, Veterinaria italiana.

[25]  W O Johnson,et al.  Bayesian spatiotemporal analysis of foot-and-mouth disease data from the Republic of Turkey , 2007, Epidemiology and Infection.

[26]  James T Case Are we really communicating? Standard terminology versus terminology standards in veterinary clinical pathology. , 2005, Veterinary clinical pathology.

[27]  G. Roberts,et al.  Predicting undetected infections during the 2007 foot-and-mouth disease outbreak , 2009, Journal of The Royal Society Interface.

[28]  Alexei J. Drummond,et al.  Bayesian Phylogeography Finds Its Roots , 2009, PLoS Comput. Biol..

[29]  T E Carpenter,et al.  Methods to investigate spatial and temporal clustering in veterinary epidemiology. , 2001, Preventive veterinary medicine.

[30]  G. Roberts,et al.  A novel approach to real-time risk prediction for emerging infectious diseases: a case study in Avian Influenza H5N1. , 2009, Preventive veterinary medicine.

[31]  Andrew B. Lawson,et al.  Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology , 2008 .

[32]  M. Kulldorff,et al.  Multivariate scan statistics for disease surveillance , 2007, Statistics in medicine.

[33]  B. Olsen,et al.  Avian Influenza Virus (H5N1) Mortality Surveillance , 2008, Emerging infectious diseases.

[34]  L. R. Beck,et al.  Perspectives Perspectives Perspectives Perspectives Perspectives Remote Sensing and Human Health: New Sensors and New Opportunities , 2022 .

[35]  A R Cameron,et al.  Demonstrating freedom from disease using multiple complex data sources 2: case study--classical swine fever in Denmark. , 2007, Preventive veterinary medicine.

[36]  Eli Stahl,et al.  Unifying the spatial population dynamics and molecular evolution of epidemic rabies virus. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[37]  A. Breed,et al.  Surveillance for Avian Influenza in Wild Birds in the European Union in 2007 , 2010, Avian diseases.

[38]  T E Carpenter,et al.  Techniques for analysis of disease clustering in space and in time in veterinary epidemiology. , 2000, Preventive veterinary medicine.

[39]  György Czifra,et al.  Genetic characterization of the NS gene indicates co-circulation of two sub-lineages of highly pathogenic avian influenza virus of H5N1 subtype in Northern Europe in 2006 , 2008, Virus Genes.

[40]  Andrew P. Dobson,et al.  Spatial and Temporal Association of Outbreaks of H5N1 Influenza Virus Infection in Wild Birds with the 0°C Isotherm , 2010, PLoS pathogens.

[41]  Ying C MacNab,et al.  On Gaussian Markov random fields and Bayesian disease mapping , 2011, Statistical methods in medical research.

[42]  C. Webb,et al.  Farm animal networks: unraveling the contact structure of the British sheep population. , 2005, Preventive veterinary medicine.

[43]  D. Freedman,et al.  Internet and computer-based resources for travel medicine practitioners. , 2001, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[44]  L. Audigé,et al.  Monitoring and surveillance for rare health-related events: a review from the veterinary perspective. , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[45]  Andrew B. Lawson,et al.  Space-time Bayesian small area disease risk models: development and evaluation with a focus on cluster detection , 2010, Environmental and Ecological Statistics.

[46]  Y. Guan,et al.  Establishment of multiple sublineages of H5N1 influenza virus in Asia: implications for pandemic control. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[47]  L Matthews,et al.  Epidemiological implications of the contact network structure for cattle farms and the 20–80 rule , 2005, Biology Letters.

[48]  Michael P Ward Geographic information system-based avian influenza surveillance systems for village poultry in Romania. , 2007, Veterinaria italiana.

[49]  Vincent Martin,et al.  EARLY WARNING, DATABASE, AND INFORMATION SYSTEMS FOR AVIAN INFLUENZA SURVEILLANCE 1 , 2007 .

[50]  D. Suarez,et al.  Highly Pathogenic Avian Influenza , 2015, Radiology of Infectious Diseases: Volume 1.

[51]  Sheng Gao,et al.  Online GIS services for mapping and sharing disease information , 2008, International journal of health geographics.

[52]  Lis Alban,et al.  Towards a risk-based surveillance for Trichinella spp. in Danish pig production. , 2008, Preventive veterinary medicine.

[53]  European Commission Health & Consumer Protection Directorate-general Directorate C -scientific Opinions C2 -management of Scientific Committees; Scientific Co-operation and Networks Opinion of the Scientific Committee on Veterinary Measures Relating to Public Health on Honey and Microbiological Haza , 2022 .

[54]  Andrew B Lawson,et al.  Disease cluster detection: a critique and a Bayesian proposal , 2006, Statistics in medicine.

[55]  Tim Carpenter,et al.  Visualization and Analysis of the Danish 2006 Highly Pathogenic Avian Influenza Virus H5N1 Wild Bird Surveillance Data by a Prototype Avian Influenza BioPortal , 2010, Avian diseases.

[56]  Annibale Biggeri,et al.  New insights into the application of geographical information systems and remote sensing in veterinary parasitology. , 2006, Geospatial health.

[57]  P A J Martin,et al.  Demonstrating freedom from disease using multiple complex data sources 1: a new methodology based on scenario trees. , 2007, Preventive veterinary medicine.

[58]  K Mølbak,et al.  Avian influenza in Denmark, March-June 2006: public health aspects. , 2006, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[59]  R. Christley,et al.  Exploring the role of auction markets in cattle movements within Great Britain. , 2007, Preventive veterinary medicine.

[60]  R S Morris,et al.  Decision support systems for monitoring and maintaining health in food animal populations , 2007, New Zealand veterinary journal.

[61]  R. Christley,et al.  Infection in social networks: using network analysis to identify high-risk individuals. , 2005, American journal of epidemiology.