There is limited understanding of how both trends and determinants of neonatal mortality vary from post-neonatal mortality, and more specifically how health care variables are associated with deaths in the first month of life. In particular the association between care at delivery and neonatal mortality is difficult to determine: in developing countries many women only seek skilled care once complications arise, making poor outcomes more probable. It is therefore inappropriate to directly compare outcomes from those who did and did not receive care at delivery due to this heterogeneity between the groups. This three-paper PHD thesis attempts to address some of these issues. Chapter 1 provides an overview of what is known about the determinants of neonatal and child mortality, before developing a conceptual framework for the analysis of neonatal and post-neonatal deaths. Chapter 2 (paper 1) provides a comprehensive analysis of the quality of Demographic & Household Surveys (DHS) data, before describing how trends in neonatal mortality differ from post-neonatal mortality over the short- and medium- term. It then examines how the associations between gross domestic product and neonatal, post-neonatal and early childhood mortality at national level differ using both cross-sectional and longitudinal data. Chapter 3 (paper 2) uses DHS data from Bangladesh to carry out bivariate and multivariate analysis to determine how the determinants of neonatal mortality vary from those of postneonatal mortality. It also tries to identify groups of women who are at ‘high’ or ‘low’ risk from institutional deliveries and compares rates of neonatal mortality. The risk categories are based on socio-economic, maternal health and health care utilisation factors that influence whether or not they are likely to have planned their delivery care or sought hospital care only in the event of complications. Chapter 4 (paper 3) furthers this work using Indian DHS data by examining how the association between health care determinants and neonatal mortality differ by asset quintile, mother’s education and state-level access to professional attendant at delivery. In this chapter I also use instrumental variable methodology to overcome the problem of endogeneity between delivery care variables and neonatal mortality. This technique enables me to examine the association between professional assistance at delivery while adjusting for the heterogeneity between women who do and do not seek such care. Chapter 5 concludes with a summary of key findings, as well as outlining areas for further research in this area.

This thesis examines health inequalities by area-level socioeconomic deprivation, and health in later life in New Zealand. It identifies whether expansion or compression of morbidity is occurring at the end of life. It asks if overall morbidity at a population level is likely to increase or decrease in future as life expectancy increases, and if the same trend is seen for more and less deprived areas. The focus of this research is the identification and dissemination of mortality and morbidity patterns present in two large datasets, using powerful but relatively simple techniques. Large administrative datasets on morbidity and public hospital discharges in New Zealand between 1974 and 2006 are used in the analyses. The thesis consists of three papers. Each paper uses the same datasets, but addresses separate research questions using different methods. The first paper is an exploratory analysis of age-specific and age-standardised mortality and hospital bed day rates, which are used as a proxy for morbidity. The second paper explores lifetime morbidity by using period-prevalence life table functions including Hospital Utilisation Expectancies: a variation of health expectancies. The third paper uses individual record linkage between the mortality and hospital datasets to examine hospital use in the last few months of life. Hospital bed day and mortality rates declined over the time period, and convergence was seen between more and less deprived areas. Individuals at the oldest ages (80 years and over) saw little variation in hospital or mortality rates by area deprivation. Strong evidence for compression of morbidity was observed, particularly at older ages. This was in the absence of evidence for rectangularisation of the survival curve, considered by some to be a prerequisite for compression of morbidity. Rectangularisation of the survival curve would be denoted by life expectancy increases slowing, indicating the nearing of a limit to life expectancy. Instead, compression of morbidity was achieved through a decline in the severity of morbidity in the months prior to death. No evidence of a change in the point at onset of morbidity prior to death was observed. There was however some evidence that the decline in hospital utilisation prior to death (particularly for deaths at older ages) may be partly artefactual. Further research using a different measure of morbidity is required to either support or disprove this theory.

HIV prevalence in China is currently less than one percent, but due to the large population this translates into a large number of people. The number of people living with HIV is growing and moving beyond high-risk groups to the general population. Ensuring adequate HIV awareness and knowledge is important for the successful prevention of HIV. This thesis investigates the evolution of HIV awareness and knowledge in China between 1997 and 2005. It also compares two methodological approaches to measuring HIV knowledge: a simple score approach and a latent variable approach. Three papers are presented and each addresses the main substantive issue using different methodologies. Various data sources and techniques used in the thesis provide each paper with its own perspective on the main substantive research question and unique insights into the main substantive and methodological issues. The first paper examines the evolution of HIV awareness among women in China between 1997 and 2005. The aim of this paper is to compare the levels of HIV awareness at various points in time. A regression decomposition analysis technique is used in this paper in order to disentangle the two main components driving a change in HIV awareness: the change in a population structure and the change in effect sizes due to external factors such as political environment, interventions and programmes. The results show that HIV awareness increased over time in China. With time, lower awareness groups are catching up and gaps between groups with initially different awareness levels are narrowing. The results suggest that the main driver of the observed change in HIV awareness over time in China is the change in the environment such as in political commitment, interventions and campaigns. The second and third paper both focus on the evolution of HIV knowledge among women in China between 1997 and 2005. The main aim of these papers is to assess whether China has succeeded in improving women’s HIV knowledge over time, and if China is a relative success story in improving women’s HIV knowledge when compared with other countries in the world with generalised (Kenya and Malawi) as well as with non-generalised (India and the Ukraine) HIV epidemics. The second paper uses a simple score approach to measuring HIV knowledge, whereas the third paper uses a latent variable approach. Partial proportional odds and multinomial logistic regression modelling techniques are employed for the analysis of patterns of HIV knowledge in China over time and in other countries included in the analyses. The main findings indicate that China has succeeded in improving women’s HIV knowledge. HIV knowledge in China is comparable to HIV knowledge in other countries with non-generalised epidemics. The HIV knowledge in China has become more homogeneous over time across different groups. However, the gap between the groups still exists and, therefore, more efforts should be directed towards improvement of HIV knowledge among women in China as well as in other cultural and epidemiological contexts. The main methodological findings show that both simple score and latent variable approaches to measuring HIV knowledge are useful and provide unique insights into the topic of the evolution of HIV knowledge in China

This thesis investigates differentials in the levels of fertility, nuptiality and contraceptive use in Liberia and Ghana, using data from the recent Demographic and Health Surveys in these countries. Of particular interest is the effect of the community in which a woman lives on her current and past fertility, her marital status and her use of contraception. This interest stems from the fact that, although the community in which a woman lives is integral to anthropological explanations of fertility, statistical models of fertility have rarely included an assessment of community effects. The method of analysis used is multilevel modelling. This involves fitting variables measured at the woman level, variables measured at the community level and also includes the use of random effects to assess the extent to which community effects have not been captured by the fixed explanatory variables. Multilevel log-linear models are used in the analyses of fertility and multilevel logistic models are used in the analyses of nuptiality and contraceptive use. This thesis demonstrates not only that there is significant variation between communities in both Liberia and Ghana for number of births 0-4 years before survey, children ever born, marital status and use of contraception but also that in each case significant community effects are found even after controlling for woman's age, education, religion and ethnicity.

This thesis, structured into four separate but related papers, uses survey birth history data to examine marital and fertility change in post-Soviet Central Asia, with a particular focus on Tajikistan. The first paper, ‘Through civil war, food scarcity and drought: fertility and nuptiality during periods of crisis in post-Soviet Tajikistan’, presents recent trends in marriage and fertility rates in Tajikistan since 1989. The fluctuating pattern of change illustrates the importance of three specific crises: the period of peak fighting in the civil war in 1992, which led to a decrease in birth registration but may also have contributed to a real decline in fertility in the worst affected areas in 1993; a food crisis in 1995, leading to immediate and significant declines in marriage and fertility; and a drought in 2000-01, which also led to marriage and fertility declines. Given the significant changes in nuptiality in Tajikistan, the next stage of the thesis places these changes within a wider Central Asian context. The second paper, ‘Marrying more and earlier: age-period interaction in trends of first union formation in transitional Central Asia’, documents the significant increase in rates of first union formation in Kazakhstan, Kyrgyzstan, Uzbekistan and Tajikistan in the late 1980s and early 1990s, showing that this increase was most marked at younger ages. The third paper, ‘Tajikistan shows the biggest collapse of all: comparing declines in union formation in post-Soviet Central Asia’, examines rates of first union formation in these countries in the post-Soviet period. It finds a significant decline in union formation across the region, but also clear differences between the republics in terms of the extent of the decline. Tajikistan, which experienced the most severe post- Soviet declines in food security, had the highest rate of union formation in the late- Soviet period but the lowest rate by the turn of the millennium. The fourth paper, ‘Spousal separation, selectivity and contextual effects: exploring the relationship between international labour migration and fertility in post-Soviet Tajikistan’ contributes to the sparse literature on the impact of temporary migration on fertility in origin areas. Fertility and migration models are solved simultaneously to account for cross-process correlation. There is clear evidence for a short-term disruptive effect of spousal separation, but it is too early to assess the implications for completed fertility.

Valid measurement of voter turnout is crucial to electoral studies. One major problem in obtaining valid turnout measurements is over-reporting, i.e. survey respondents who did not vote report having voted. Aiming to identify effective solutions to turnout over-reporting, this doctoral thesis consists of four separate but interrelated papers , plus introductory and concluding chapters. The introductory chapter reviews the causes and consequences of turnout over-reporting, providing the basis for an in-depth research into solutions. Each of the papers then addresses a question about solutions. Paper 1 critically re-examines an influential study of turnout over-reporting. The examination results highlight the need for better solutions to over-reporting. Addressing the question of "What is out there?", Paper 2 conducts a meta-analysis of studies that have experimented on innovative solutions to turnout over-reporting. Addressing the question of "What works?", Paper 3 experimentally compares two promising solutions – item-count and pipeline techniques – and finds that the former is, overall, better than the latter for preventing turnout over-reporting. Addressing the question of "Can we do better?", Paper 4 improves the design and analysis of the item-count technique, making it an even better solution to turnout over-reporting. From the results of these research papers, the concluding chapter considers the implications for developing effective solutions to turnout over-reporting, and laying the foundations for future advances in the measurement of turnout. Furthermore, the concluding chapter also discusses how the results of this doctoral research can contribute beyond election studies, towards scientific studies on a wide range of topics on which people often misreport.

In this thesis, we are interested in the asymptotic analysis of extremes and risks. The heavy-tailed distribution function is used to model the extreme risks, which is widely applied in insurance and is gradually penetrating in finance as well. We also use various tools such as copula, to model dependence structures, and extreme value theorem, to model rare events. We focus on modelling and analysing of extreme risks as well as demonstrate how the derived results that can be used in practice. We start from a discrete-time risk model. More concretely, consider a discrete-time annuity-immediate risk model in which the insurer is allowed to invest its wealth into a risk-free or a risky portfolio under a certain regulation. Then the insurer is said to be exposed to a stochastic economic environment that contains two kinds of risk, the insurance risk and financial risk. The former is traditional liability risk caused by insurance loss while the latter is the asset risk resulting from investment. Within each period, the insurance risk is denoted by a real-valued random variable X, and the financial risk Y as a positive random variable fulfils some constraints. We are interested in the ruin probability and the tail behaviour of maximum of the stochastic present values of aggregate net loss with Sarmanov or Farlie-Gumbel-Morgenstern (FGM) dependent insurance and financial risks. We derive asymptotic formulas for the finite-ruin probability with lighted-tailed or moderately heavy-tailed insurance risk for both risk-free investment and risky investment. As an extension, we improve the result for extreme risks arising from a rare event, combining simulation with asymptotics, to compute the ruin probability more efficiently. Next, we consider a similar risk model but a special case that insurance and financial risks following the least risky FGM dependence structure with heavy-tailed distribution. We follow the study of Chen (2011) that the finite-time ruin probability in a discrete-time risk model in which insurance and financial risks form a sequence of independent and identically distributed random pairs following a common bivariate FGM distribution function with parameter -1 ≤ θ ≤ 1 governing the strength of dependence. For the subexponential case, when -1 < θ ≤ 1, a general asymptotic formula for the finite-time ruin probability was derived. However, the derivation there is not valid for θ = -1. In this thesis, we complete the study by extending Chen's work to θ = -1 that the insurance risk and financial risk are negatively dependent. We refer this situation as the least risky FGM dependent insurance risk and financial risk. The new formulas for θ = −1 look very different from, but are intrinsically consistent with, the existing one for -1 < θ ≤ 1, and they offer a quantitative understanding on how significantly the asymptotic ruin probability decreases when θ switches from its normal range to its negative extremum. Finally, we study a continuous-time risk model. Specifically, we consider a renewal risk model with a constant premium and a constant force of interest rate, where the claim sizes and inter-arrival times follow certain dependence structures via some restriction on their copula function. The infinite-time absolute ruin probabilities are studied instead of the traditional infinite-time ruin probability with light-tailed or moderately heavy-tailed claim-size. Under the assumption that the distribution of the claim-size belongs to the intersection of the convolution-equivalent class and the rapid-varying tailed class, or a larger intersection class of O-subexponential distribution, the generalized exponential class and the rapid-varying tailed class, the infinite-time absolute ruin probabilities are derived.

Materials with appropriate combinations of multifunctional properties (strength, toughness, electrical conductivity and piezoelectricity) together with desired biocompatibility are promising candidates for biomedical applications. Apart from these material properties, recent studies have shown the efficacy of electric field in altering cell functionality in order to elicit various cell responses, like proliferation, differentiation, apoptosis (programmed cell death) on conducting substrates in vitro. In the above perspective, the current work demonstrates how CaTiO3 (CT) addition to Hydroxyapatite (HA) can be utilised to obtain an attractive combination of long crack fracture toughness (up to 1.7 MPa.m1/2 measured using single edge V-notch beam technique) and a flexural strength of 155 MPa in addition to moderate electrical conductivity. The enhancement of fracture toughness in HA-CT composites has been explained based on the extensive characterization of twinned microstructure in CT along with the use of theoretical models for predicting the enhancement of toughening through crack tip tilt and twist mechanisms. Subsequent in vitro studies on HA-CT composites with human Mesenchymal Stem cells (hMSCs) in the presence of electric field has shown enhanced differentiation towards bone like cells (osteogenic lineage) as evaluated by ALP activity, Collagen content and gene expression analyses through Polymerase Chain Reaction (PCR) at the end of two weeks. he extracellular matrix mineralization analysis at the end of 4 weeks of hMSC culture further substantiated the efficacy of electric field as a biochemical cue that can influence the stem cell fate processes on conducting substrates. The electric field stimulation strategy was also implemented in in vitro studies with C2C12 mouse myoblast (muscle) cells on elastically compliant poly(vinylidene difluoride) (PVDF)-multiwall carbon nanotube (MWNT) composite substrates. PVDF is a piezoelectric polymer and the addition of MWNTs makes the composite electrically conducting. Upon, electric field stimulation of C2C12 mouse myoblast cells on these composites, has been observed that in a narrow window of electric field parameters, the cell viability was enhanced along with excellent cell alignment and cell-cell contact indicating a potential application of PVDF-based materials in the muscle cell regeneration. In an effort to rationalise such experimental observations, a theoretical model is proposed to explain the development of bioelectric stress field induced cell shape stability and deformation. A single cell is modelled as a double layered membrane separating the culture medium and the cytoplasm with different dielectric properties. This system is linearized by invoking Debye-Huckel approximation of the Poisson-Boltzmann equation. With appropriate boundary conditions, the system is solved to obtain intracellular and extracellular Maxwell stress as a function of multiple parameters like cell size, intracellular and extracellular permittivity and electric field strength. Based on the stresses, we predict shape changes of cell membrane by approximating the deformation amplitude under the influence of electric field. Apart from this, the shear stress on the membrane has been used to determine the critical electric field required to induce membrane breakdown. The analysis is conducted for a cell in suspension/on a conducting substrate and on an insulating substrate to illustrate the effect of substrate properties on cell response under the influence of external electric field.

Critical infrastructures are based on complex systems that provide vital services to the nation. The complexities of the interconnected networks, each managed by individual organisations, if not properly secured, could offer vulnerabilities that threaten other organisations’ systems that depend on their services. This thesis argues that the awareness of interdependencies among critical sectors needs to be increased. Managing and securing critical infrastructure is not isolated responsibility of a government or an individual organisation. There is a need for a strong collaboration among critical service providers of public and private organisations in protecting critical information infrastructure. Cyber exercises have been incorporated in national cyber security strategies as part of critical information infrastructure protection. However, organising a cyber exercise involved multi sectors is challenging due to the diversity of participants’ background, working environments and incidents response policies. How well the lessons learned from the cyber exercise and how it can be transferred to the participating organisations is still a looming question. In order to understand the implications of cyber exercises on what participants have learnt and how it benefits participants’ organisation, a Cyber Exercise Post Assessment (CEPA) framework was proposed in this research. The CEPA framework consists of two parts. The first part aims to investigate the lessons learnt by participants from a cyber exercise using the four levels of the Kirkpatrick Training Model to identify their perceptions on reaction, learning, behaviour and results of the exercise. The second part investigates the Organisation Cyber Resilience (OCR) of participating sectors. The framework was used to study the impact of the cyber exercise called X Maya in Malaysia. Data collected through interviews with X Maya 5 participants were coded and categorised based on four levels according to the Kirkpatrick Training Model, while online surveys distributed to ten Critical National Information Infrastructure (CNII) sectors participated in the exercise. The survey used the C-Suite Executive Checklist developed by World Economic Forum in 2012. To ensure the suitability of the tool used to investigate the OCR, a reliability test conducted on the survey items showed high internal consistency results. Finally, individual OCR scores were used to develop the OCR Maturity Model to provide the organisation cyber resilience perspectives of the ten CNII sectors.

Since the Global Financial Crisis, the literature of financial networks analysis has been trying to investigate the changes in the financial networks structure, that led to the instability of the financial system. The Global Financial Crisis followed by the Great Recession costed taxpayers an unprecedented $14 trillion (Alessandri and Haldane, 2009), austerity and downturns in GDP. The dynamics of the financial networks transferred the collapse of a US housing market bubble into a large meltdown of the financial systems globally. The study of systemic risk and macro-prudential policy has come to the forefront to model and manage the negative externalities of monetary, fiscal and financial sector activities that can lead to system wide instabilities and failure. The dimensions of crisis propagation have been modelled as those that can spread cross-sectionally in domino like failures with global scope, or build up over time, as in asset bubbles. The cross sectional propagation of shocks that occur due to non-payment of debt or other financial obligations with the failure of a financial intermediary or a sovereign leading to the failure of other economic entities, is called financial contagion. Cross sectional analysis of financial contagion can be done using statistical methods or by network analysis. The latter gives a structural model of the interconnections in terms of financial obligations. This dissertation uses both approaches to model financial contagion. The applications include the study of systemic risk in Eurozone Sovereign crisis, the US CDS market and the global banking network. This is organized in three self-contained chapters Our contribution to the literature begins with the study of the dynamics of the market of the Credit Default Swap (CDS) contracts for selected Eurozone sovereigns and the UK. The EWMA correlation analysis and the Granger-causality test demonstrate that there was contagion effect since correlations and cross-county interdependencies increased after August 2007. Furthermore, the IRF analysis shows that among PIIGS, the CDS spreads of Spain and Ireland have the biggest impact on the European CDS spreads, whereas the UK is found not be a source of sovereign contagion to the Eurozone. Next we perform the empirical reconstruction of the US CDS network based on the real-world data obtained from the FDIC Call Reports, and study the propagation of contagion, assuming different network structures. The financial network shows a highly tiered core-periphery structure. We find that network topology matters for the stability of the financial system. The “too interconnected to fail” phenomenon is discussed and shown to be the result of highly tiered network with central core of so called super-spreaders. In this type of network the contagion is found to be short, without multiple waves, but with very high losses brought by the core of the network. Finally we study a global banking network (GBN) model based on the Markose (2012) eigen-pair approach and propose a systemic risk indices (SRI) which provide early warning signals for systemic instability and also the rank order of the systemic importance and vulnerability of the banking systems. The empirical model is based on BIS Consolidated Banking Statistics for the exposures of 19 national banking systems to the same number of debtor countries and the data obtained from Bankscope for the equity capital of these 19 national banking systems. The SRI is based on the ratio of the netted cross-border exposures of the national banking systems to their respective equity capital. The eigen-pair method stipulates that if the maximum eigenvalue of the network exceeds the capital threshold, there is cause for concern of a contagion. This is compared with the loss multiplier SRI proposed by Castrén and Rancan (2012). The latter is found to have no early warning capabilities and peaks well after the onset of the crisis in 2009 while the eigen-pair SRI gives ample warning by late 2006 that the cross border liabilities was unsustainable in respect of the equity capital of the national banking systems. We contribute to the literature by highlighting the efficacy of the network approach to systemic stability analysis of GBNs. In particular we develop an eigen-pair approach for GBNs and prove its usefulness in an early warning context.