Coral colonies, from a reef near Abu Dhabi, United Arab Emirates (UAE), were counted and assessed for condition using photo-transects. An epidemic model, used to track how a communicable disease moves through a population, was constructed to help predict the future condition of this coral reef. In situ data from a disease outbreak that occurred in September 2011 provided a baseline for the model. Coral Populations of Porites, Platygyra, Acropora and Dipsastrea were modelled using condition categories that included Healthy, Black Band Disease Infected, Cyanobacteria Infected, Recovered, Recruits or Dead. Results from the modelling indicate that populations of Platygyra and Dipsastrea are healthy and growing, even with continued presence of diseases, due to the high rates of recovery (chance for host colony to overcome infection; high recovery rate = high chance of colony recovering from the infection) and low mortality rates (chance of dying from an infection; low mortality rate = low chance of a infected colony dying from the infection) in the genus. Porites showed no signs of population growth, but stabilized near its initial population size, despite having a high infection rate because population growth (recruitment) and recovery rate were canceled by a high mortality rate. Acropora showed a loss in population numbers over time, losing 25% of its population before the disease was eliminated. Diseases may have been eliminated from the Acropora population because population density was low and coral died quickly after becoming infected with a disease, due to the high mortality rate of this genus, before infecting other colonies. Acropora was the only genus to display what seems to be a density dependent infection rate, since chance of infection was reduced and then eliminated by the rapid mortality of infected colonies, if the population was higher disease spread may have been higher. In addition to results obtained using in situ data, higher modified infection rates were used to assess how they might impact these coral populations. Results suggest that all four genera seem to be resilient, shown by in situ modeling and parameters extracted from the phototransects, and able to withstand acute (rapid increase of infection rate which was then again quickly brought back to normal infection rate, an infection “spike”) increases of disease infection, which is shown by either a high recovery rate (Dipsastrea and Platygyra), a high recruitment/low mortality rate (Porites), or a high mortality rate (Acropora) that may not allow for the diseases to spread. However, all four genera would be slowly driven to extinction by a sustained (chronic) increase of disease infection rate brought on by growing stressors such as an increase in average water temperature or pollutants within the Gulf. These results demonstrate fragility of Gulf coral genera when exposed to chronic episodes of disease, which over time causes total collapse of the coral populations.

Cholera made an unforeseen appearance on the eastern coast of South Africa in the province of KwaZulu-Natal (KZN) in August 2000. Having started from the more urban centres of the coastal region of the province, cholera proceeded unabated to the interior of the province where no community was spared from the scourge. Despite prompt medical intervention, health education and media awareness campaigns, cholera continued to spread throughout KZN. By March 2004, the official statistics of cholera cases in KZN as per the Cholera Database records, stood at 158 895 cases (Dept-KZN Health, 2000). The death toll as reported in the Cholera Database was 575 persons that translated to a percentage case fatality rate of 0.36%; the lowest when compared to the previous epidemics recorded in South African (Kustner et al., 1981; Küstner and du Plessis, G. 1991). An interesting feature of the epidemic was that 99% of the cases recorded by the central and provincial Departments of Health during the height of the epidemic were all from KZN. The question then was, what factors played a role in the cholera epidemic of KZN? This study sought to understand the outbreak and the factors that possibly contributed to the spread of the 2000-2004 cholera epidemic in KZN. The drivers of disease associated with the communities affected by cholera were also explored by analysing the complex and dynamic interaction of their biological, socio economic, and environmental nature over time and space. The nature of the study was such that it called for a multi faceted design to involve not just understanding the societal aspect of the disease but its demographic, ecological and spatial characteristics as well. Thus GIS was used as a research tool to facilitate the comparison of the disease trends and risk factors on a spatial level in order to determine the possible role(s) played by the different environmental and socio-economic drivers. The objective of the study was to investigate the possible role of the natural environment i.e. temperature, rainfall and humidity as the primary factors that influence cholera outbreaks in KZN; on the basis of its uniqueness in climatic conditions as compared to other areas of the Republic of South Africa (RSA). The other socio-economical and demographic factors were considered as factors that enhance the spread of the disease. As such, the exploration of the Cholera Database by use of spreadsheet, statistical correlations and spatial mapping using GIS technology mutually investigated the relationships between the different variables that came up as important factors in the spread of cholera. Results indicated that 52% of the total cholera cases in KZN were reported from DC28 (Uthungulu), making it the focal point of the epidemic. In general, all the age groups were represented in the cholera database though the age groups 15-19 years and 0-4 years featured more prominently in the overall epidemic picture. On average the male to female case ratio was 1:1.5 respectively. The major cholera peak was experienced in 2001 and a minor peak in 2002. Both the peaks appeared during the summer months, which are also characterised by heavy rains. The issues that were statistically proven to be associated with the spread of the disease were related to issues highlighting the inefficiencies in the provision of water and sanitation, which go hand in hand with poverty. Thus poverty was indirectly reflected in the data as an issue that compounded the cholera epidemic. There was no statistical correlation between the incidence of cholera and the climatic variables of rainfall, humidity and temperature. Notwithstanding, there was an overall seasonality revealed by the data, as seen with the cases peaking and waning between the summers and the winters respectively. Furthermore, GIS mapping revealed a concurrence between the incidence of cholera and the climatic variables of rainfall, humidity and maximum temperature. At the spatial level, the characteristics of the epidemic as revealed by the GIS maps and spatial modelling highlighted possible relationships between the incidence of cholera and the various socio-economic and climatic variables (Chapter 6: 6.2.3; 6.2.3). The spatial disease picture displayed a link between climatic seasons and the incidence of cholera. Spatial modelling offered more insight that the statistically supported climatic and socio-economic aspects were indeed important factors in guiding cholera outbreak predictions in the future. The cholera model illustrated this as it selected for areas considered to be at high risk for cholera (Map 34). The results give an altogether holistic portrayal of the cholera epidemic from all perspectives and also supported to the hypothesis that cholera is a function of social and environmental factors. The results from this study further confirm the negative health effects of inadequacies in basic services delivery. The study made use of data resources to understand the relationships between the incidence of cholera and the different demographic, socio-economic and climatic variables implicated in the spread of cholera epidemics (Chapter 3: 3.3.3). It also emphasizes the importance of using reliable data as a management tool to model various scenarios in order to obtain information that could be used in the prediction and management of diseases like cholera at the community level in the future. / Thesis (PhD (Water Resource Management))--University of Pretoria, 2006. / Microbiology and Plant Pathology / unrestricted

The Argus Commission identified three major federal priorities related to health care, including the precision medicine initiative, the Cancer Moonshot and the opioid abuse epidemic. Current activities at the federal level were summarized and an analysis of activities within the profession, and academic pharmacy specifically, was prepared. The implications for pharmacy education, research and practice are compelling in all three areas. Recommendations, suggestions and two policy statements aim to optimize the attention to these priorities by the academy. Further, aligning the AACP Strategic Engagement agenda with the opportunities and threats acknowledged in the analysis is essential.

This paper analyzes the impact of the 2012 legalization of recreational marijuana in Washington State on opioid abuse. Using synthetic control methodology, this paper finds that the legislation prevented 638 overdose deaths and lead to over 3,600 individuals seeking treatment for opioid abuse disorders. Due to the large health, social, and economic impacts of the opioid epidemic, further research should be conducted into ways to reduce the number of opioid prescriptions, the number of opioid overdoses, and opioid abuse generally.

US Foster Care is already known to be an under researched and complex topic, and the literature that is done tends to focus on the need for more investigation to improve this ineffective system. Foster care has even been described as “one huge experiment that has been conducted on children”, at a “cost of untold billions of dollars” (Courtney, 2000). This comment doesn’t seem too far off—there is a consensus that more work needs to be done in the realm of child welfare services, and some studies have even questioned whether removals and placements by foster care are beneficial at all (Doyle, 2006). In order to improve foster care and decisions in treatment (as these decisions have significant impact on children’s safety and well-being), we need to be more effective in using our resources and understanding the needs of the population, and the trends that might be influencing foster care. On that note, research by the US Department of Health and Human Services has shown a clear relationship between parental substance abuse and child abuse, and a study reported by Economic Inquiry (Cunningham, 2013), investigates this in terms of foster care. Cunningham’s study investigates the impact of methamphetamine abuse on admissions in foster care, and reports a significant causal relationship. This interesting report motivated me to investigate this further, and in terms of the recent opioid epidemic in the US. In this study, I adapt Cunningham’s strategies to investigate the effect of the opioid epidemic on US Foster Care, at a more recent time period. Surprisingly, I find different results for the opioid epidemic than the meth shocks, despite many variations of the model to proxy opioid use. My results show a negative relationship from opioid use on foster care admissions, while also confirming Cunningham’s study with a positive relationship with methamphetamine use and foster care at a more recent time period. This study will explain the methods that attain these results, as well as the reasons driving the results in the discussion. While contributing to Cunningham’s study, this study also contributes new research to a topic (the opioid epidemic) frequently mentioned in recent news. This study also considers the impact of this epidemic on individuals it might impact most, and addresses the gap in literature that exists regarding US Foster Care.

Background. Developing countries are undergoing a process of epidemiological transition from infectious to non-communicable diseases, described by the United Nations Secretary General Ban Ki-Moon as “a public health emergency in slow motion”. One of the most prevalent of these diseases, in sub-Saharan Africa, is hypertension, which is a complex chronic condition often referred to as the “silent killer” and a key contributor to the development of cardiovascular and cerebrovascular diseases. Hypertensive patients in this setting are estimated to increase from 74.7 million in 2008 to 125.5 million in 2025, a 68% increase. There is however an important gap between emerging high-level policies and recommendations, and the near-absence of practical guidance and experience delivering long-term medical care for non-communicable diseases within resources-limited health systems. To address this gap, our study consisted of field investigations to determine the minimum health systems requirements necessary to ensure successful delivery of anti-hypertensive medications when scaling-up interventions. Methods/Design. A cross-sectional analytic study was conducted in the Western Cape Province of South Africa using a mixed method approach with two sets of semi-structured interviews and simulation modeling. One set of interviews was conducted with health professionals involved in the care of hypertensive patients within nine community health centers (five urban and four rural) to understand the challenges associated with their care. The other set was used to map and assess the current supply chain management system of antihypertensive medications and involved key informants at different levels of the process. Finally, modeling and simulation tools with ARENA Software were used to estimate minimum numbers of health workers required to ensure successful delivery of medications when scaling up interventions. Results. The study found numerous challenges affecting the care of hypertensive patients in primary health care facilities and categorized these into five interconnected dimensions: Management of the visits within the PHC facility, Adequacy of human resources, Standardization of patients’ care, Infrastructure limitations, and Patients’ responsibilities. Potential solutions to overcome these challenges were explored in order to improve the care of the hypertensive patients in the PHC facilities. Mapping of the drug supply chain management system highlighted the complexity of the system. In fact many of the issues reported fell outside of the control of the provincial health department. The need for a more single comprehensive computer system to handle most of the functions of the drug supply management system was heavily emphasized. The modeling and simulation tool with ARENA Software estimated the type and number of health care professionals needed to provide appropriate services to a certain patient population based on the set targets. The sample data used showed how one can test the impact of various changes in the processes and staffing levels to minimize waiting times while increasing the daily patients’ intake at the facility. We found that with few additional nursing staff, that are more affordable and quicker to train than medical doctors and pharmacists, one can considerably improve the performance of the facilities in the care of hypertensive patients. Discussion. This investigation has highlighted the detailed processes in place for the care of hypertensive patients in primary health care facilities, identifying the challenges in providing such care. The potential solutions suggested by the study results, if implemented, should help improve services offered and ensure that the system remains sustainable when patients’ intake increases exponentially as a result of scaled up interventions. The weaknesses of the drug supply chain management system demand immediate action. The modeling and simulation tools used in this study, if used on an ongoing basis, could create more effective planning of needed resources, although their proper utilization will require extra training for managers. Whether there is sufficient political support to ensure the resources necessary to reach the provincial health department’s hypertension target remains to be seen, and would benefit with further economic studies to estimate the cost associated with tackling the hypertension epidemic.

Orientador: Élcio Lebensztayn / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-27T01:18:53Z (GMT). No. of bitstreams: 1 EstradaLopez_MarioAndres_M.pdf: 691310 bytes, checksum: c03e392b197051a7368585d6c09a7835 (MD5) Previous issue date: 2015 / Resumo: Este trabalho tem como objetivo estudar o modelo SIR (suscetível-infectado-removido) de epidemia nas versões determinística e estocástica. Nosso objetivo é encontrar limitantes para a probabilidade de que o tamanho da epidemia não sobrepasse certa proporção do número inicial de suscetíveis. Iniciamos apresentando as definições e a dinâmica do processo de epidemia determinístico. Obtemos um valor limiar para o número inicial de suscetíveis para que a epidemia exploda ou não. Consideramos o modelo de epidemia estocástico SIR assumindo que não há período latente, isto é, que um infectado pode transmitir a infecção ao instante de ser contagiado. O modelo é considerado com uma configuração inicial de suscetíveis e infectados e é feita especial ênfases no estudo da variável aleatória ''tamanho da epidemia'', que é definida como a diferença entre o número de suscetíveis ao começar e ao terminar a propagação da doença. Como na parte determinística, obtemos teoremas limiares para o modelo de epidemia estocástico. Os métodos usados para encontrar os limitantes são os de análise da cadeia de Markov imersa e de comparação estocástica / Abstract: This work has as objective to study the SIR (susceptible-infected-removed) epidemic model in the deterministic and stochastic version. Our objective is to find bounds for the probability that the size of the epidemic does not exceed certain proportion of the initial number of susceptible individuals. We begin presenting the definitions and the dynamics for the deterministic model for a general epidemic. We obtain a threshold value for the initial number of susceptible individuals for the epidemic to build up or not. As fundamental part of this work, we consider a stochastic epidemic SIR model assuming there is no latent period, that is, one infected can transmit the infection at the moment of being infected. The model is considered with an initial configuration of susceptible and infected individuals and the study is focused on the random variable ''size of the epidemic'', which is defined as the difference between the number of susceptible individuals at the start and at the end of the propagation of the epidemic. As in the deterministic part, we obtain a threshold theorem for the stochastic epidemic. The methods used to prove the theorem are analysis of the embedded chain and the stochastic comparison / Mestrado / Estatistica / Mestre em Estatística

Nos travaux ont démontré les performances des systèmes d’intelligence épidémiologique en matière de détection précoce des évènements infectieux au niveau mondial, la valeur ajoutée spécifique de chaque système, la plus grande sensibilité intrinsèque des systèmes modérés et la variabilité du type de source d’information utilisé. La création d’un système virtuel combiné intégrant le meilleur résultat des sept systèmes a démontré les gains en termes de sensibilité et de réactivité, qui résulterait de l’intégration de ces systèmes individuels dans un supra-système. Ils ont illustrés les limites de ces outils et en particulier la faible valeur prédictive positive des signaux bruts détectés, la variabilité les capacités de détection pour une même pathologie, mais également l’influence significative jouée par le type de pathologie, la langue et la région de survenue sur les capacités de détection des évènements infectieux. Ils ont établis la grande diversité des stratégies d’intelligence épidémiologique mises en œuvre par les institutions de santé publique pour répondre à leurs besoins spécifiques et l’impact de ces stratégies sur la nature, l’origine géographique et le nombre des évènements rapportés. Ils ont également montré que dans des conditions proches de la routine, l’intelligence épidémiologique permettait la détection d’évènements infectieux en moyenne une à deux semaines avant leur notification officielle, permettant ainsi d’alerter les autorités sanitaires et d’anticiper la mise en œuvre d’éventuelles mesures de contrôle. Nos travaux ouvrent de nouveaux champs d’investigations dont les applications pourraient être importantes pour les utilisateurs comme pour les systèmes. / Our work demonstrated the performance of the epidemic intelligence systems used for the early detection of infectious diseases in the world, the specific added value of each system, the greater intrinsic sensitivity of moderated systems and the variability of the type information source’s used. The creation of a combined virtual system incorporating the best result of the seven systems showed gains in terms of sensitivity and timeliness that would result from the integration of these individual systems into a supra-system. They have shown the limits of these tools and in particular: the low positive predictive value of the raw signals detected, the variability of the detection capacities for the same disease, but also the significant influence played by the type of pathology, the language and the region of occurrence on the detection of infectious events. They established the wide variety of epidemic intelligence strategies used by public health institutions to meet their specific needs and the impact of these strategies on the nature, the geographic origin and the number of events reported. As well, they illustrated that under conditions close to the routine, epidemic intelligence permitted the detection of infectious events on average one to two weeks before their official notification, hence allowing to alert health authorities and therefore the anticipating the implementation of eventual control measures. Our work opens new fields of investigation which applications could be important for both users systems.

Les systèmes décentralisés sont par nature extensibles mais sont également difficiles à coordonner en raison de leur faible couplage. La réplication de données dans ces systèmes géo-répartis est donc un défi inhérent à leur structure. Les deux contributions de cette thèse exploitent l'hétérogénéité des besoins des utilisateurs et permettent une qualité de service personnalisable pour la réplication de données dans les systèmes décentralisés. Notre première contribution Gossip Primary-Secondary étend le critère de cohérence Update consistency Primary-Secondary afin d'offrir des garanties différenciées de cohérence et de latence de messages pour la réplication de données à grande échelle. Notre seconde contribution Dietcoin enrichit Bitcoin avec des nœuds diet qui peuvent (i) vérifier la validité de sous-chaînes de blocs en évitant le coût exorbitant de la vérification initiale et (ii) choisir leur propres garanties de sécurité et de consommation de ressources. / Decentralized systems are scalable by design but also difficult to coordinate due to their weak coupling. Replicating data in these geo-distributed systems is therefore a challenge inherent to their structure. The two contributions of this thesis exploit the heterogeneity of user requirements and enable personalizable quality of services for data replication in decentralized systems. Our first contribution Gossip Primary-Secondary enables the consistency criterion Update consistency Primary-Secondary to offer differentiated guarantees in terms of consistency and message delivery latency for large-scale data replication. Our second contribution Dietcoin enriches Bitcoin with diet nodes that can (i) verify the correctness of entire subchains of blocks while avoiding the exorbitant cost of bootstrap verification and (ii) personalize their own security and resource consumption guarantees.

Thesis advisor: Julie H. Mortimer / The unifying theme of this dissertation is the growing importance of pharmaceutical products in health care and in society more broadly. The first two chapters use structural and reduced-form models to study the effects of various policies on the choice and utilization of prescription drugs. The third chapter surveys the empirical literature on the competitive effects of a class of pricing arrangements used in the pharmaceutical and many other industries. Chapter 1. One of the criticisms leveled against direct-to-consumer advertising of prescription drugs is that it overemphasizes the use of pharmaceuticals at the expense of other forms of treatment. In “Choice of Depression Treatment: Advertising Spillovers in a Model with Complementarity,” I study how antidepressant TV ads affect demand for psychotherapy. Antidepressant advertising can increase demand for therapy if the products are complements or if advertising has spillover effects. To disentangle the different channels, I develop a discrete-choice demand model that allows for complementarity between products, advertising spillovers, and flexible unobserved preference heterogeneity. Individual-level panel data on treatment choices and price variation allow me to separately identify complementarity and correlated preferences, whereas the average price of TV advertising, used as an instrument, identifies the causal effect of antidepressant ads on demand for each product. The results indicate that even though antidepressants and psychotherapy are substitutes, drug advertising increases demand for therapy through a spillover effect. Allowing for time-invariant and time-varying unobservables that can be correlated across products critically affects the estimated degree of complementarity and advertising elasticities. Chapter 2. While prescription drugs have enabled the cost-effective treatment of a myriad of diseases, many pharmaceuticals come with potential for abuse. The growing use of opioid medications for chronic pain led to widespread misuse, addiction, and skyrocketing overdose death rates. In “Did Plain-Vanilla Prescription Drug Monitoring Programs Reduce Opioid Use? Evidence from Privately Insured Patients,” I explore whether prescription drug monitoring programs (PDMPs) with no registration or use mandates were effective in reducing the utilization of opioid prescription drugs. Exploiting the staggered introduction of such programs between 2008 and 2010, I use difference-in-differences to estimate their causal effect on the number of prescriptions, days supply, and dosage per capita. Based on data from privately insured adults, the estimation results reveal that PDMPs successfully reduced opioid utilization, especially of high-dosage prescriptions. A battery of robustness checks suggests that the estimated effects are caused by the PDMPs and not by confounding factors such as broader trends in health care, attrition, out-of-state purchases, or other anti-opioid policies. Chapter 3. The assumption that buyers pay the same price for each unit of the good they purchase underlies many economic analyses. However, linear pricing is one of many pricing arrangements used in practice. In “Empirical Evidence on Conditional Pricing Practices: A Review,” Julie Holland Mortimer and I review the existing empirical studies on the competitive impact of conditional pricing practices (CPPs), under which the price of a product may depend on a quantity, share, bundling, or other requirement. Examples of CPPs include all-units and loyalty discounts, full-line forcing contracts, and exclusivity arrangements. A common thread unifying the empirical literature is that CPPs often have both procompetitive and anticompetitive effects and that their net effect may depend on the details of the arrangements and the characteristics of the markets in which they are used. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.