Building an ecologically founded disease risk prioritization framework for migratory wildlife species based on contact with livestock

Munib Khanyari*, Sarah Robinson, Eric R. Morgan, Tony Brown, Navinder J. Singh, Albert Salemgareyev, Steffen Zuther, Richard Kock, E.J. Milner-Gulland

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
27 Downloads (Pure)


Shared use of rangelands by livestock and wildlife can lead to disease transmission. To align agricultural livelihoods with wildlife conservation, a multipronged and interdisciplinary approach for disease management is needed, particularly in data‐limited situations with migratory hosts. Migratory wildlife and livestock can range over vast areas, and opportunities for disease control interventions are limited. Predictive frameworks are needed which can allow for identification of potential sites and timings of interventions. We developed an iterative three‐step framework to assess cross‐species disease transmission risk between migrating wildlife and livestock in data‐limited circumstances and across social‐ecological scales. The framework first assesses risk of transmission for potentially important diseases for hosts in a multi‐use landscape. Following this, it uses an epidemiological risk function to represent transmission‐relevant contact patterns, using density and distribution of the host to map locations and periods of disease risk. Finally, it takes fine‐scale data on livestock management and observed wildlife–livestock interactions to provide locally relevant insights on disease risk. We applied the framework to characterize disease transmission between livestock and saiga antelopes Saiga tatarica in Central Kazakhstan. At step 1, we identified peste‐des‐petits‐ruminants as posing a high risk of transmission from livestock to saigas, foot‐and‐mouth disease as low risk, lumpy skin disease as unknown and pasteurellosis as uncertain risk. At step 2, we identified regions of high disease transmission risk at different times of year, indicating where disease management should be focussed. At step 3, we synthesized field surveys, government data and literature review to assess the role of livestock in the 2015 saiga mass mortality event from pasteurellosis, concluding that it was minimal. Synthesis and applications. Our iterative framework has wide applicability in assessing and predicting disease spill‐over at management‐relevant temporal and spatial scales in areas where livestock share space with migratory species. Our case study demonstrated the value of combining ecological and social information to inform management of targeted interventions to reduce disease risk, which can be used to plan disease surveillance and vaccination programmes.
Original languageEnglish
JournalJournal of Applied Ecology
Early online date22 Jun 2021
Publication statusEarly online date - 22 Jun 2021

Bibliographical note

Funding Information:
We would like to thank UK Research and Innovation (NERC grant NE/N007646/1), People's Trust for Endangered Species, Saiga Conservation Alliance and the Zutshi‐Smith fellowship for supporting this work. We also thank staff of the Association for the Conservation of Biodiversity of Kazakhstan for enabling the on‐the‐ground surveys. N.J.S. was supported by the research program ‘Beyond Moose – Ecology and management of multispecies ungulate systems’ of the Swedish Environmental Protection Agency (Naturvårdsverket, NV‐01337‐15/NV‐03047‐16/NV‐08503‐18).

Publisher Copyright:
© 2021 The Authors. Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society

Copyright 2021 Elsevier B.V., All rights reserved.


  • Conservation ecology
  • Disease ecology
  • Movement ecology
  • Socioecology
  • disease transmission
  • framework
  • livestock
  • management
  • migration
  • multi‐use landscapes
  • overlap
  • saiga

ASJC Scopus subject areas

  • Ecology


Dive into the research topics of 'Building an ecologically founded disease risk prioritization framework for migratory wildlife species based on contact with livestock'. Together they form a unique fingerprint.

Cite this