Network epidemiology of cattle and cattle farms in Great Britain

Infectious diseases of livestock can cause substantial production losses and have detrimental impacts upon human health, and animal health and welfare. To limit the impact of diseases, understanding more about the dynamics of transmission can assist in the control and prevention of infectious disease. In particular, understanding infection transmission on networks, ‘network epidemiology’, offers a flexible approach, incorporating between-host heterogeneity in potentially infectious contacts drawn from empirical study of interactions among individual animals, or among farms. Trading animals and optimising productivity are vital to the commercial viability of farms, however they necessarily involve compromises in biosecurity, animal health, and welfare. Better understanding of the relationships among these multiple factors might facilitate the development of sustainable livestock industries that are more resilient to disease outbreaks. In this thesis I examine cattle interactions at two spatial scales, first at a national-level by studying the trading connections among farms, and then at a finer scale by analysing the social interactions among cattle. First, I introduce the concept of superspreaders, hosts that generate many more secondary infections than the rest of the population, and evaluate evidence for the notion that some farms might act as superspreaders of infection. I utilise the example of bovine tuberculosis (bTB) to illustrate this concept and find that farms might act as superspreaders in three main ways; first, via exceptional trading between farms, second, by factors that facilitate high within-herd transmission and trading of high-risk animals, and third, by harbouring undetected infection for long periods. I find mechanisms that align with all three processes in the cattle industry in Great Britain that might allow superspreader farms to contribute to the current bTB epidemic. At a national level, I describe cattle movements among farms over time, finding that some farms consistently act as ‘hubs’ in trading networks, functioning in a similar way to markets, in that they are highly connected to other farms by many direct trades. Utilising the temporal network measure of ‘contact chains’, I quantify the farms that represent potential sources of infection (ingoing contact chains) and the potential farms that a farm might infect over 1 year periods. Farms divide into two groups: those with very few connections (less than 10 farms) that are relatively isolated from the network, and those with very many connections (more than 1000 farms) that are highly connected within the network. I find that a substantial number of farms have over 10,000 farms in both their ingoing and outgoing contact chains, such that, if infected, they might potentially act as superspreaders by being more at risk of both acquiring and spreading infection. Building on my previous analysis, I then characterise the ‘source farms’ in the ingoing contact chains, in terms of their location and bTB history. I find that after controlling for previously-established risk factors for bTB, having more source farms in areas of higher bTB risk in the ingoing contact chain increases the odds of a bTB incident on the root farm, whilst having more source farms in lower risk areas is associated with lower odds of a bTB incident on the root farm. At a finer scale of contacts among animals, I explore interactions among dairy cattle in multiple herds using automated proximity sensors and GPS devices. When aggregated over long periods, cattle interactions appear dense and unstructured, however finer time spatial and temporal perspectives revealed structure and variation in contacts. Herds in our study had variable grazing and housing access, allowing us to determine that cattle interact with more other cows, for longer time periods when they are in buildings compared to contacts at pasture. Cattle exhibited heterogeneity in their number and duration of contacts, and although the majority of cattle interacted more equally with other cows, a small proportion of cows in each group showed evidence of stronger social ties. Next, I consider associations between social interactions, production, and health. I review the existing literature on social parameters such as dominance rank and re-grouping of cattle, and find inconclusive outcomes regarding their impact on milk yield and somatic cell count, an indicator of udder health. I perform my own analysis to examine the relationship between the time cows spend with other cows, milk yield and somatic cell count, and do not find a statistically significant relationship. In considering social preference, cows that had experienced the same number of lactations were more likely to interact, but cows spending more time with cows in the same lactation did not appreciably affect their milk yield or somatic cell count. Finally, I draw together the findings of this thesis and reflect on how the identification of higher-risk farms might be useful in the control of livestock infections, and specifically bTB in Great Britain. I conclude that network analysis is a valuable tool to study the interactions of cattle and cattle farms, identifying unique opportunities for targeted approaches to disease control.Animal Health Veterinary Laboratories Agency BBSRC - BB/M015874/

Spatio-temporal Pattern Recognition Using Hidden Markov Models

A new spatio-temporal method for identifying 3D objects found in 2D image sequences is presented. The Hidden Markov Model technique is used as a spatio-temporal classification algorithm to identify 3D objects by the temporal changes in observed shape features. A new information theoretic argument is developed that proves identifying objects based on image sequences can lead to higher classification accuracies than single look methods. A new distance measure is proposed that analyzes the performance of Hidden Markov Models in a multi-class pattern recognition problem. A three class problem identifying moving light display objects provides experimental verification of the sequence processing argument. Individual frames of a MLD image sequence contain very little spatial information. The single look classification rate for the moving light display imagery was observed to be near 50%. In contrast, the Hidden Markov Model classification rate was above 93 %. The alternate nearest neighbor multiple frame technique classification rate was 20% below the Hidden Markov Models. A one sided t-test revealed a highly statistically significant difference between the Hidden Markov Model and multiple frame technique at a 0. 01 level of significance. A five class problem consisting of tactical military ground vehicles is considered to provide verification using imagery with both spatial and temporal information. Results confirmed the new spatio-temporal pattern recognition method produces superior results by accessing the temporal information in the image sequences. A prototype automatic target recognition system is demonstrated

Why Do African Banks Lend so Little?

We put forward a plausible explanation of African financial under-development in the form of a bad credit market equilibrium. Utilising an appropriately modified IO model of banking, we show that the root of the problem could be unchecked moral hazard (strategic loan defaults) or adverse selection (a lack of good projects). Applying a dynamic panel estimator to a large sample of African banks, we show that loan defaults are a major factor inhibiting bank lending when the quality of regulation is poor. We also find that once a threshold level of regulatory quality has been reached, improvements in the default rate or regulatory quality do not matter, providing support for our theoretical predictions.Dynamic panel data; African financial under-development; African credit markets

Letter from John H. Fielding to James B. Finley

Fielding informs Finley that the semi-annual meeting of the Board of Trustees of Augusta College is scheduled for Feb. 5, 1834. He indicates that Brother (Joseph S.) Tomlinson has resigned the presidency and Dr. (Nathan) Bangs, whom the Board appointed to take his place, has declined acceptance. They are therefore without a head. Due to Tomlinson\u27s poor health, the faculty was weak before his resignation. The added duties made life very difficult for them. Fielding says that they need Finley\u27s advice and would like him to come a week before the Board meets. Fielding invites Finley to be a guest at his house. Abstract Number - 633https://digitalcommons.owu.edu/finley-letters/1729/thumbnail.jp

Political Violence and Excess Liquidity in Egypt

In this article we estimate a time-series model of excess liquidity in the Egyptian banking sector. While financial liberalisation and financial stability are found to have reduced excess liquidity, these effects have been offset by an increase in the number of violent political incidents arising from conflict between radical Islamic groups and the Egyptian state. The link between political events and financial outcomes provides a rationale for economic policy interventions by the international community in response to increases in political instability

Letter from John H. Fielding to James B. Finley

Fielding writes to Finley saying that he will not be able to attend the Ohio Conference because of his duties at St. Charles College in St. Louis, Missouri. He is in the process of forming a Board of Trustees, raising an endowment, creating a charter, etc. He is hopeful that he will be transferred from the Ohio Conference to the Missouri Conference without a problem. However, he seems concerned about rumors concerning his work at Augusta College. Abstract Number - 1209https://digitalcommons.owu.edu/finley-letters/2189/thumbnail.jp

State criminal justice telecommunications (STACOM). Volume 3: Requirements analysis and design of Texas criminal Justice Telecommunications Network

For abstract, see N78-16218