Frontiers journals are at the top of citation and impact metrics

Review ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Vet. Sci. | doi: 10.3389/fvets.2018.00263

Detecting and predicting emerging disease in poultry with the implementation of new technologies and big data

Jake Astill1, Rozita Dara1, Evan Fraser1 and  Shayan Shayan1*
  • 1University of Guelph, Canada

Future demands for food will place agricultural systems under pressure to increase production. Poultry is accepted as a good source of protein and the poultry industry will be forced to intensify production in many countries, leading to greater numbers of farms that house birds at elevated densities. Increasing farmed poultry can facilitate enhanced transmission of infectious pathogens among birds, such as avian influenza virus among others, which have the potential to induce widespread mortality in poultry and cause considerable economic losses. Additionally, the capability of some emerging poultry pathogens to cause zoonotic human infection will be increased as greater numbers of poultry operations could increase human contact with poultry pathogens. In order to combat the increased risk of spread of infectious disease in poultry due to intensified systems of production, rapid detection and diagnosis is paramount. In this review, multiple technologies that can facilitate accurate and rapid detection and diagnosis of poultry diseases are highlighted from the literature, with a focus on technologies developed specifically for avian influenza virus diagnosis. Rapid detection and diagnostic technologies allow for responses to be made sooner when disease is detected, decreasing further bird transmission and associated costs. Additionally, systems of rapid disease detection produce data that can be utilized in decision support systems that can predict when and where disease is likely to emerge in poultry. Other sources of data can be included in predictive models, and in this review two highly relevant sources, internet based-data and environmental data, are discussed. Additionally, big data and big data analytics, which will be required in order to integrate voluminous and variable data into predictive models that function in near real-time are also highlighted. Implementing new technologies in the commercial setting will be faced with many challenges, as will designing and operating predictive models for poultry disease emergence. The associated challenges are summarized in this review. Intensified systems of poultry production will require new technologies for detection and diagnosis of infectious disease. This review sets out to summarize them, while providing advantages and limitations of different types of technologies being researched.

Keywords: Influena virus, Poultry, rapid diagnosis, big data, biosensor, Infectious Disease

Received: 25 Jun 2018; Accepted: 02 Oct 2018.

Edited by:

Paul Wigley, University of Liverpool, United Kingdom

Reviewed by:

Christi Swaggerty, United States Department of Agriculture, United States
Silke Rautenschlein, University of Veterinary Medicine Hannover, Germany
Kuldeep Dhama, Indian Veterinary Research Institute (IVRI), India  

Copyright: © 2018 Astill, Dara, Fraser and Shayan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Shayan Shayan, University of Guelph, Guelph, N1G 2W1, Ontario, Canada, shayan@uoguelph.ca