Spatial and network aspects of the spread of infectious diseases in livestock populations

Churakov, Mikhail (2014) Spatial and network aspects of the spread of infectious diseases in livestock populations. PhD thesis, University of Glasgow.

Abstract

In this thesis, I focus on methodological concepts of studying infectious disease transmission between agricultural premises. I used different disease systems as exemplars for spatial and network methods to investigate transmission patterns.

Infectious diseases cause tangible economic threat to the farming industry worldwide by damaging livestock populations, reducing farm productivity and causing trade restriction. This implies the importance of veterinary epidemiological studies in control and eradication of pathogens.
Recent increase in availability of data and computational power allowed for more opportunities to study mechanisms of pathogenic transmission. Nowadays, the bottleneck is primarily associated with efficient methods that can analyse vast amounts of high-resolution data.

Here I address two livestock pathogens that differ in their epidemiology: bacteria Streptococcus agalactiae and foot-and-mouth disease (FMD) virus.

Streptococcus agalactiae is a contagious pathogen that causes mastitis in cattle, and thus possesses a substantial economic burden to the dairy industry. Known transmission routes between cattle are restricted to those via milking machines, milkers’ hands and fomites during milking process. Additionally, recent studies suggested potential introductions from other host species: primarily, humans. However, strain typing data showed discrepancies in strain compositions of bacteria isolated from humans and bovines. In this thesis, strain-specific features of between-herd transmission of Streptococcus agalactiae within dairy cattle population in Denmark are investigated.

Foot-and-mouth disease (FMD) is a viral infection that affects cloven-hoofed animals and is of big importance mainly because of the trade restrictions against infected regions and countries. Control programmes against FMD usually include vaccination and culling of animals. However, the debate on the optimal control for FMD is still ongoing. In this thesis, I address questions on identification of the routes of infection and on requirements for movement recording systems to be used for efficient contact tracing during an FMD outbreak.

This thesis reveals several interesting findings. Firstly, the increased understanding of strain-specific transmission characteristics of Streptococcus agalactiae. One of the observed strains (ST103) showed significant and consistent spatial clustering of its cases among Danish dairy cattle herds in 2009–2011.

Secondly, the network analysis of cattle movements and affiliations with veterinary practices showed that veterinary practices were exclusively associated with transmission of ST103 of Streptococcus agalactiae. Contrastingly, movement networks appeared to be important for all the three predominant bacterial strains (ST1, ST23 and ST103).

Fourthly, the new extended approach that allows estimation of the whole transmission tree at once was proposed and tested for the Darlington cluster within the 2001 FMD UK epidemic.
Finally, in chapter 6, it was shown that mathematical modelling did not suggest any advantages of ensuring smaller delays in the post-silent control of FMD-like pathogens.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: Epidemiology, clustering, network analysis, transmission trees, FMD, Streptococcus agalactiae.
• Subjects: Q Science > QA Mathematics; Q Science > QH Natural history > QH301 Biology; Q Science > QR Microbiology; S Agriculture > SF Animal culture > SF600 Veterinary Medicine
• Colleges/Schools: College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
• Supervisor's Name: Kao, Prof Rowland, Zadoks, Prof Ruth and Rogers, Dr Simon
• Date of Award: 2014
• Depositing User: Mr Mikhail Churakov
• Unique ID: glathesis:2014-6417
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 18 Jun 2015 09:43
• Last Modified: 02 May 2018 12:37
• URI: https://theses.gla.ac.uk/id/eprint/6417