Includes abstract. / Includes bibliographical references. / Finding and treating cases [of tuberculosis] in the community before they present to health facilities, a strategy known as active-case-finding is gaining momentum as a way to decrease the infectious pool. This can be achieved through door-to-door community surveys using a TB symptom-screening questionnaire, and is an economical and practical tool to employ in poor, high burden areas. However, unlike for the high risk group of people infected with HIV, there is a lack of evidence supporting the adaptation of a symptom screening tool in the other high risk groups. In 2010, a TB prevalence survey was conduceted in 24 high TB and HIV burden communities in Zambia and the Western Cape, South Africa. This prevalence survey served as the endpoint for the Zambia and South Africa TB and AIDS Reduction study (ZAMSTAR). This survey made use of a questionnaire the collected, among other information, data regarding individual TB symptom reporting, HIV status, diabetes mellitus status and cigarette smoking.

The British cattle population hosts a diverse community of endemic pathogens that impact the sustainability of beef and dairy production. As such, there has been a tremendous amount of ongoing research to develop more cost-effective strategies for controlling disease at the industry level. Cattle movements have come under particular scrutiny over the past decade both because of their role in spreading many economically important diseases and because the movements of individual cattle in Great Britain have been explicitly recorded in a centralized electronic database since 1998. Numerous studies have shown that these cattle movements organize into complex networks with key structural and temporal features that influence transmission dynamics. Building on previous work, this thesis used a variety of epidemiological and statistical models to highlight limitations in the current approaches to controlling disease as well as opportunities for reducing endemic disease prevalence through targeted interventions. Empirical disease data from the national bovine tuberculosis (bTB) control programme and from two seroprevalence studies of bovine viral diarrhoea virus (BVDV) in Scottish cattle herds were used in conjunction with movement data from the Cattle Tracing System (CTS) database. Endemic diseases are often challenging to control due to lack of affordable and accurate diagnostic tests as well as the presence of subclinically infected carriers that can easily escape detection. There was evidence that combined issues with the sensitivity and specificity of routine surveillance methods for bTB were contributing to a low level of disease transmission within and between Scottish cattle herds from 2002 to 2009. For BVDV, herds that purchased pregnant beef dams, beef dams with a calf at foot, and open dairy heifers were significantly more likely to be seropositive even though these movements were responsible for only a small number of network contacts. In both cases, targeting the subset of high risk movements with disease specific biosecurity measures may be a more cost-effective use of limited national disease control resources. Other researchers have suggested that control strategies should target multiple diseases simultaneously to reduce trade-offs in resource allocation. Using key indicators of herd reproductive performance derived from the CTS database, it was shown that improving the reproductive management of herds operating below industry standards could reduce endemic disease prevalence by reducing the movements of replacement breeding cattle. A series of network generation algorithms were also developed to study the effects of restricting contact formation based on key demographic and network characteristics of actively trading cattle farms. Strategies that increased network fragmentation either by forcing highly connected farms to form contacts with other highly connected farms or preventing the formation of movements with a high predicted betweenness centrality were found to be particularly effective in limiting disease transmission. For these models to be useful in guiding future policy decisions, it is important to incorporate financial and behavioural drivers of dynamic network change. Following the introduction of pre- and post-movement testing requirements for cattle imported into Scotland from endemic bTB regions, there was a significant decline in cross-border movements, which has likely contributed to the decreasing risk of bTB outbreaks as much as testing itself. Many endemic cattle diseases such as BVDV also spread through local transmission mechanisms, which may undermine the success of disease control programmes that exclusively target cattle movements. There was also evidence that in the absence of national animal legislation, few farmers were likely to adopt biosecurity measures against BVDV. This may be related to the perceived inefficacy of recommendations as well as general unawareness of farm disease status due to the non-specific clinical signs of BVDV outbreaks. Although the CTS database was originally intended for use in slaughter traceback investigations, results from this thesis show how the basic records of births, deaths, and movements can be used to generate valuable insights into the epidemiology of endemic cattle diseases. The findings also emphasize that the management decisions of individual herds can have a substantial impact on industry level transmission dynamics, which offers unique opportunities to develop novel and more cost-effective disease control programmes.

Medical cartography can provide valuable insights into the epidemiology and ecology of infectious diseases, providing a quantitative representation of the distribution of these pathogens. Such methods therefore provide a key step in informing public health policy decisions ranging from prioritising sites for further investigation to identifying targets for interventions. By increasing the resolution at which risk is defined, policymakers are provided with an increasingly informed approach for considering next steps as well as evaluating past progress. In spite of their benefits however, global maps of infectious disease are lacking in both quality and comprehensiveness. This thesis sets out to investigate the next steps for medical cartography and details the use of species distribution models in evaluating global distributions of a variety of zoonotic diseases of public health importance. Chapter 2 defines a methodology by which global targets for infectious disease mapping can be quantitatively assessed by comparing the global burden of each disease with the demand from national policymakers, non-governmental organisations and academic communities for global assessments of disease distribution. Chapter 3 introduces the use of boosted regression trees for mapping the distribution of a group of vector-borne diseases identified as being a high priority target, the leishmaniases. Chapter 4 adapts these approaches to consider Ebola virus disease. This technique shows that the West African outbreak was ecologically consistent with past infections and suggests a much wider area of risk than previously considered. Chapter 5 investigates Marburg virus disease and considers the variety of different factors relating to all aspects of the transmission cycle that must be considered in these analyses. Chapters 6 and 7 complete the mapping of the suite of viral haemorrhagic fevers by assessing the distribution of Crimean-Congo haemorrhagic fever and Lassa fever. Finally, Chapter 8 considers the risk that these viral haemorrhagic fevers present to the wider African continent, quantifying potential risk of spillover infections, local outbreaks and more widespread infection. This thesis addresses important information gaps in global knowledge of a number of pathogens of public health importance. In doing so, this work provides a template for considering the global distribution of a number of other zoonotic diseases.

Meningococcal disease, caused by the bacterium Neisseria meningitidis, is an important cause of morbidity and mortality in young children and adolescents worldwide. There are 12 serogroups with most disease due to meningococci expressing one of five capsular polysaccharide antigens corresponding to serogroups A, B, C, Y and W135. In Europe, the majority of disease-causing strains are of serogroups B and C. No comprehensive vaccine is available against the bacterium due to the difficulty in producing serogroup B vaccines. A number of countries, e.g. UK and the Republic of Ireland have implemented routine meningococcal conjugate C (MCC) vaccine strategies. Due to the high proportion of disease accounted for by serogroup B in Europe and other developed countries, much research is currently being carried out to unearth vaccine candidates that would be protective and give as wide coverage as possible. Such candidates include the antigens PorA, FetA and factor H-binding protein. Potential drawbacks with antigens such as these which are under immune selection are high degrees of variability and lack of cross-immunity. Determination of the distribution, both geographically and temporally, of antigens and their association with clonal complex can aid in the formulation of novel vaccines and assess their potential coverage across Europe. Serological typing schemes involving characterisation of the polysaccharide capsule (serogroup) and outer membrane proteins such as PorA (serosubtype) and PorB (serotype) have been used for a number of years with some success. However, drawbacks associated with these methods include insufficient discrimination, limitations in panels of monoclonal antibodies used in the typing procedures and difficulty in comparison of results among labs. Consequently, in recent years genotypic methods such as multi-locus enzyme electrophoresis (MLEE) and subsequently multi-locus sequence typing (MLST) have been developed. These methods measure the variation in slowly evolving housekeeping genes whereas serological methods measure variation in antigens which are under immune pressure and are therefore more diverse. Combination of phenotypic and genotypic typing methods can offer high levels of discrimination. Molecular studies into meningococcal diversity have offered many important insights into its population biology, which have implications for prevention and control of meningococcal disease. These have included the identification of hyperinvasive lineages and the correlation of genetic type with antigenic type and disease epidemiology. The EU-MenNet programme was established as a pan-European infrastructure for the research and surveillance of European meningococcal disease. Its aim was to coordinate and disseminate the latest molecular isolate characterisation techniques (MLST) and electronic data transfer via the Internet to exploit epidemiological and population genetic studies. Within the EU-MenNet, the European Meningococcal MLST Centre (EMMC) was set up to carry out molecular typing — MLST, PorA and FetA — of European disease isolates from 18 countries over three years 2000, 2001 and 2002. The output of this project will be the largest representative molecular epidemiological study of meningococcal disease in Europe. Assessment of the data produced will give insights into the geographic and temporal distribution and structuring of disease-associated clonal complexes and antigens and their associations. This will give an indication of the meningococcal disease population in Europe and will be invaluable for the current, and ongoing, development and introduction of new meningococcal vaccines.

abstract: In the field of infectious disease epidemiology, the assessment of model robustness outcomes plays a significant role in the identification, reformulation, and evaluation of preparedness strategies aimed at limiting the impact of catastrophic events (pandemics or the deliberate release of biological agents) or used in the management of disease prevention strategies, or employed in the identification and evaluation of control or mitigation measures. The research work in this dissertation focuses on: The comparison and assessment of the role of exponentially distributed waiting times versus the use of generalized non-exponential parametric distributed waiting times of infectious periods on the quantitative and qualitative outcomes generated by Susceptible-Infectious-Removed (SIR) models. Specifically, Gamma distributed infectious periods are considered in the three research projects developed following the applications found in (Bailey 1964, Anderson 1980, Wearing 2005, Feng 2007, Feng 2007, Yan 2008, lloyd 2009, Vergu 2010). i) The first project focuses on the influence of input model parameters, such as the transmission rate, mean and variance of Gamma distributed infectious periods, on disease prevalence, the peak epidemic size and its timing, final epidemic size, epidemic duration and basic reproduction number. Global uncertainty and sensitivity analyses are carried out using a deterministic Susceptible-Infectious-Recovered (SIR) model. The quantitative effect and qualitative relation between input model parameters and outcome variables are established using Latin Hypercube Sampling (LHS) and Partial rank correlation coefficient (PRCC) and Spearman rank correlation coefficient (RCC) sensitivity indices. We learnt that: For relatively low (R0 close to one) to high (mean of R0 equals 15) transmissibility, the variance of the Gamma distribution for the infectious period, input parameter of the deterministic age-of-infection SIR model, is key (statistically significant) on the predictability of the epidemiological variables such as the epidemic duration and the peak size and timing of the prevalence of infectious individuals and therefore, for the predictability these variables, it is preferable to utilize a nonlinear system of Volterra integral equations, rather than a nonlinear system of ordinary differential equations. The predictability of epidemiological variables such as the final epidemic size and the basic reproduction number are unaffected by (or independent of) the variance of the Gamma distribution for the infectious period and therefore for the choice on which type of nonlinear system for the description of the SIR model (VIE's or ODE's) is irrelevant. Although, for practical proposes, with the aim of lowering the complexity and number operations in the numerical methods, a nonlinear system of ordinary differential equations is preferred. The main contribution lies in the development of a model based decision-tool that helps determine when SIR models given in terms of Volterra integral equations are equivalent or better suited than SIR models that only consider exponentially distributed infectious periods. ii) The second project addresses the question of whether or not there is sufficient evidence to conclude that two empirical distributions for a single epidemiological outcome, one generated using a stochastic SIR model under exponentially distributed infectious periods and the other under the non-exponentially distributed infectious period, are statistically dissimilar. The stochastic formulations are modeled via a continuous time Markov chain model. The statistical hypothesis test is conducted using the non-parametric Kolmogorov-Smirnov test. We found evidence that shows that for low to moderate transmissibility, all empirical distribution pairs (generated from exponential and non-exponential distributions) for each of the epidemiological quantities considered are statistically dissimilar. The research in this project helps determine whether the weakening exponential distribution assumption must be considered in the estimation of probability of events defined from the empirical distribution of specific random variables. iii) The third project involves the assessment of the effect of exponentially distributed infectious periods on estimates of input parameter and the associated outcome variable predictions. Quantities unaffected by the use of exponentially distributed infectious period within low transmissibility scenarios include, the prevalence peak time, final epidemic size, epidemic duration and basic reproduction number and for high transmissibility scenarios only the prevalence peak time and final epidemic size. An application designed to determine from incidence data whether there is sufficient statistical evidence to conclude that the infectious period distribution should not be modeled by an exponential distribution is developed. A method for estimating explicitly specified non-exponential parametric probability density functions for the infectious period from epidemiological data is developed. The methodologies presented in this dissertation may be applicable to models where waiting times are used to model transitions between stages, a process that is common in the study of life-history dynamics of many ecological systems. / Dissertation/Thesis / Ph.D. Applied Mathematics for the Life and Social Sciences 2014

The Innovative Medicines Initiative Accelerated Development of VAccine beNefit-risk Collaboration in Europe (IMI ADVANCE) project aims to develop a framework for best practice methods on integrated rapid benefit/risk monitoring of vaccines in the European Union (EU). Burden of disease is one of the measures considered when estimating vaccine benefits. This study explores the use of notifiable infectious disease surveillance data for this purpose by estimating burden of invasive meningococcal disease in the EU/European Economic Area (EEA). We use the Burden of Communicable Diseases in Europe toolkit for computing disability-adjusted life years from incidence-based data retrieved from the European Surveillance System (TESSy) held at the European Centre for Disease Prevention and Control. Invasive meningococcal is a common cause of meningitis and septicaemia, with high case-fatality (~10%) and sequelae. We found that the median annual burden of invasive meningococcal disease in the EU/EEA, 2011-2015, was 3.87 DALYs per 100 000 total population (95% UI: 3.79-3.95). Children below one year of age and children below five years of age were at greatest risk of invasive meningococcal disease serogroup B with 89.15 DALYs per 100 000 stratum specific population (95% UI: 83.11-95.02) and 22.57 DALYs per 100 000 stratum specific population (95% UI: 21.03-24.12), respectively. We found that the distribution of burden of invasive meningococcal disease serogroup B differs widely between countries in the EU/EEA and consequently confirm that national assessment of the new infant meningococcal B vaccine is highly relevant.