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<div>Using sensor measurements to estimate the states and parameters of a system is a fundamental task in understanding the behavior of the system. Moreover, as modern systems grow rapidly in scale and complexity, it is not always possible to deploy sensors to measure all of the states and parameters of the system, due to cost and physical constraints. Therefore, selecting an optimal subset of all the candidate sensors to deploy and gather measurements of the system is an important and challenging problem. In addition, the systems may be targeted by external attackers who attempt to remove or destroy the deployed sensors. This further motivates the formulation of resilient sensor selection strategies. In this thesis, we address the sensor selection problem under different settings as follows. </div><div><br></div><div>First, we consider the optimal sensor selection problem for linear dynamical systems with stochastic inputs, where the Kalman filter is applied based on the sensor measurements to give an estimate of the system states. The goal is to select a subset of sensors under certain budget constraints such that the trace of the steady-state error covariance of the Kalman filter with the selected sensors is minimized. We characterize the complexity of this problem by showing that the Kalman filtering sensor selection problem is NP-hard and cannot be approximated within any constant factor in polynomial time for general systems. We then consider the optimal sensor attack problem for Kalman filtering. The Kalman filtering sensor attack problem is to attack a subset of selected sensors under certain budget constraints in order to maximize the trace of the steady-state error covariance of the Kalman filter with sensors after the attack. We show that the same results as the Kalman filtering sensor selection problem also hold for the Kalman filtering sensor attack problem. Having shown that the general sensor selection and sensor attack problems for Kalman filtering are hard to solve, our next step is to consider special classes of the general problems. Specifically, we consider the underlying directed network corresponding to a linear dynamical system and investigate the case when there is a single node of the network that is affected by a stochastic input. In this setting, we show that the corresponding sensor selection and sensor attack problems for Kalman filtering can be solved in polynomial time. We further study the resilient sensor selection problem for Kalman filtering, where the problem is to find a sensor selection strategy under sensor selection budget constraints such that the trace of the steady-state error covariance of the Kalman filter is minimized after an adversary removes some of the deployed sensors. We show that the resilient sensor selection problem for Kalman filtering is NP-hard, and provide a pseudo-polynomial-time algorithm to solve it optimally.</div><div> </div><div> Next, we consider the sensor selection problem for binary hypothesis testing. The problem is to select a subset of sensors under certain budget constraints such that a certain metric of the Neyman-Pearson (resp., Bayesian) detector corresponding to the selected sensors is optimized. We show that this problem is NP-hard if the objective is to minimize the miss probability (resp., error probability) of the Neyman-Pearson (resp., Bayesian) detector. We then consider three optimization objectives based on the Kullback-Leibler distance, J-Divergence and Bhattacharyya distance, respectively, in the hypothesis testing sensor selection problem, and provide performance bounds on greedy algorithms when applied to the sensor selection problem associated with these optimization objectives.</div><div> </div><div> Moving beyond the binary hypothesis setting, we also consider the setting where the true state of the world comes from a set that can have cardinality greater than two. A Bayesian approach is then used to learn the true state of the world based on the data streams provided by the data sources. We formulate the Bayesian learning data source selection problem under this setting, where the goal is to minimize the cost spent on the data sources such that the learning error is within a certain range. We show that the Bayesian learning data source selection is also NP-hard, and provide greedy algorithms with performance guarantees.</div><div> </div><div> Finally, in light of the COVID-19 pandemic, we study the parameter estimation measurement selection problem for epidemics spreading in networks. Here, the measurements (with certain costs) are collected by conducting virus and antibody tests on the individuals in the epidemic spread network. The goal of the problem is then to optimally estimate the parameters (i.e., the infection rate and the recovery rate of the virus) in the epidemic spread network, while satisfying the budget constraint on collecting the measurements. Again, we show that the measurement selection problem is NP-hard, and provide approximation algorithms with performance guarantees.</div>

Outbreaks of novel influenza viruses are continually occurring on many places on our planet, with the ultimate and most extreme consequence being a full-scale pandemic. Modern communication technology is widely used for risk communication regarding recommended change in behavior patterns and other precautions in order to mitigate the transmission. However, the assumption and bias that modern communication technology constitutes the norm causes vulnerable groups to be at possible risk of systematic exclusion to correct and updated information. Through conducting a literature- and case analysis, the aim of this study is to identify insufficient or inadequate risk communication efforts in South Korea and Vietnam during influenza outbreaks, especially with concern of vulnerable groups. Further, to analyze how national influenza preparedness plans observe or ignore these insufficiencies. Results show that vulnerable groups are explicitly recognized in the preparedness plan of Vietnam. However, the South Korean preparedness plan show a more homogenous approach. Both South Korea and Vietnam showed a broad variety of channels used in their risk communication strategies which could be positive in terms of a broad outreach to a heterogenous population, including vulnerable groups. Four key factors that moderate the outcomes of risk communication were identified: Channels, Messages, Transparency and Trust.

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Complex networks have been used to represent the fundamental structure of a multitude of complex systems from various fields. In the network representation, the system is reduced to a set of nodes and links that denote the elements of the system and the connections between them respectively. Complex networks are commonly adaptive such that the structure of the network and the states of nodes evolve dynamically in a coupled fashion. Adaptive networks lead to peculiar complex dynamics and network topologies, which can be investigated by moment-closure approximations, a coarse-graining approach that enables the use of the dynamical systems theory. In this thesis, I study several contact processes in adaptive networks that are defined by the transmission of node states. Employing moment-closure approximations, I establish analytical insights into complex phenomena emerging in these systems. I provide a detailed analysis of existing alternative moment-closure approximation schemes and extend them in several directions. Most importantly, I consider developing analytical approaches for models with complex update rules and networks with complex topologies. I discuss four different contact processes in adaptive networks. First, I explore the effect of cyclic dominance in opinion formation. For this, I propose an adaptive network model: the adaptive rock-paper-scissors game. The model displays four different dynamical phases (stationary, oscillatory, consensus, and fragmented) with distinct topological and dynamical properties. I use a simple moment-closure approximation to explain the transitions between these phases. Second, I use the adaptive voter model of opinion formation as a benchmark model to test and compare the performances of major moment-closure approximation schemes in the literature. I provide an in-depth analysis that leads to a heightened understanding of the capabilities of alternative approaches. I demonstrate that, even for the simple adaptive voter model, highly sophisticated approximations can fail due to special dynamic correlations. As a general strategy for targeting such problematic cases, I identify and illustrate the design of new approximation schemes specific to the complex phenomena under investigation. Third, I study the collective motion in mobile animal groups, using the conceptual framework of adaptive networks of opinion formation. I focus on the role of information in consensus decision-making in populations consisting of individuals that have conflicting interests. Employing a moment-closure approximation, I predict that uninformed individuals promote democratic consensus in the population, i.e. the collective decision is made according to plurality. This prediction is confirmed in a fish school experiment, constituting the first example of direct verification for the predictions of adaptive network models. Fourth, I consider a challenging problem for moment-closure approximations: growing adaptive networks with strongly heterogeneous degree distributions. In order to capture the dynamics of such networks, I develop a new approximation scheme, from which analytical results can be obtained by a special coarse-graining procedure. I apply this analytical approach to an epidemics problem, the spreading of a fatal disease on a growing population. I show that, although the degree distribution has a finite variance at any finite infectiousness, the model lacks an epidemic threshold, which is a genuine adaptive network effect. Diseases with very low infectiousness can thus persist and prevail in growing populations.:1. Introduction .................................................................................. 1 2. Moment-closure approximations of complex networks ................. 5 3. Cyclic dominance in adaptive network models of opinion formation .......... 25 4. Performance of moment-closure approximations of adaptive networks .... 35 5. Information and consensus in a fish school ................................. 65 6. Epidemic spreading on growing heterogeneous adaptive networks ......... 83 7. Conclusions ................................................................................. 101 Appendix A: Moment expansion for node update rules ................... 107

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This exploratory study investigated the psychosocial impact on rural grandmothers of Gutu, Zimbabwe, caring for their grandchildren orphaned by HIV/AIDS. The participants included 12 paternal and maternal grandmother-caregivers from four districts of Gutu, whose ages ranged from 56 to 76 years with orphans in their care ranging from infants to 18 years. The present study made use of Erikson's psychosocial theory of development on late adulthood. Data were gathered using semi-structured open-ended interviews in the participants' homes. Interpretive analysis was used to analyse the audio-taped data. Findings reveal that most grandmothers are experiencing a personal toll in dealing with the late adult crisis of integrity versus despair, including finding it difficult to resolve the grief of losing children while engaging in full time grandparenting in a stigmatising society. Participants reported a need for support and interventions tailored to their unique needs. Counselling, social support, financial assistance, and skills and knowledge about HIV/AIDS are therefore recommended. / Psychology / M.Sc. (Psychology)

Obesity and obesity-related diseases – such as type 2 diabetes – have become the most crucial indicators of population health in the 21st century. Formerly understood as ‘diseases of affluence’, obesity is now prevalent in the Global South posing serious risk to socioeconomic development. This is particularly true for rapidly developing countries where nutrition transitions are most apparent. There are many factors which impact on risk of obesity (e.g. gender, culture, environment, socioeconomic status, biological determinants). The problem is further aggravated within small island developing states where food security is exacerbated by factors associated with globalization and development. The thesis examines the surge of obesity and type 2 diabetes within Caribbean populations, using Barbados as a case study. A holistic approach was applied using an ecological health model. Moving away from the lifestyle model, the theoretical framework underpinning included sub-theories (e.g. social constructivism, feminism, post-colonial theory, concepts of memory and trauma).

This thesis sets out to explore the lives of homosexuals in the AIDS epidemic in Sweden in Jonas Gardell´s trilogy Torka aldrig tårar utan handskar (Don´t Ever Dry Tears Without Gloves). How is queer space able to unfold in connection to concrete places? The thesis utilizes the perspective of queer theory, where the useful terms of queer space and heteronormativity are found.   The analysis is divided into two parts based on the important themes of life and death found in the trilogy. The metal ring at the central station called Bögringen (The Gay Ring) and other public places such as parks and streets make up the first part. It becomes evident that these spaces are vital to the very existence of the homosexual lives of the men in the book-series. In these places, they are able to create their own (queer) space, which exists in parallel to the heteronormative surroundings. The concrete spaces that become these queer spaces are nevertheless often challenged by their surroundings, both verbally and physically.   Funerals make up the second half of the analysis. Here, two opposite funerals are being looked closer at. These are the funerals of two of the most important men in the trilogy: Rasmus and Paul. In Rasmus´funeral, there is no room for anything (or anyone) that might be associated with homosexuality and AIDS – a queer lifestyle ­– at all, and the boyfriend and all the other friends of the deceased Rasmus are not welcome. Everything queer is banished. The other funeral, Paul´s funeral, celebrates everything that is different, and here, it is the heteronormative, conservative views and thoughts that are being pushed aside. This funeral brings hope (and power) to the queers.