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DeMars, Kathleen R., and Nathaniel A. MD Justice. "Pneumonia masking the presentation of incomplete Kawasaki disease." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/asrf/2019/schedule/76.
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Presentation: A 3 month-old male is referred for admission with a 2-day history of fever, having been diagnosed with pneumonia and prescribed a cephalosporin on the previous day. A blood culture obtained at that time is positive for coagulase negative Staphyloccocus.
On exam, he is ill-appearing. He has bilateral conjunctivitis that spares the limbus, non-exudative pharyngitis, and a polymorphic truncal rash. There is no appreciable cervical lymphadenopathy or extremity involvement. A chest x-ray demonstrates a round infiltrate of the left upper lobe, and initial labs reveal a white blood count of 17.5, a C-reactive protein (CRP) of 23.9 mg/dL, and a normal comprehensive metabolic panel. His positive blood culture is deemed a contaminant, and antibiotic coverage for community-acquired pneumonia is given with ampicillin.
Diagnostic evaluation: On day 5 of illness, his fevers persist despite broadened antibiotic coverage. Further work-up has ruled out viral respiratory pathogens and Epstein-Barr virus as a cause of persistent fevers. Incomplete Kawasaki disease is suspected due to continued fevers, the presence of three clinical criteria, and further increase in his CRP. He lacks other supplemental laboratory criteria, so an echocardiogram is obtained that shows mild dilation of the left anterior descending artery (LAD) of indeterminate significance. A repeat echocardiogram 2 days later reveals progressive dilation of left main coronary artery (LMCA), LAD, and right coronary artery (RCA).
Diagnosis: Dilation of the LAD and RCA confirm a diagnosis of incomplete Kawasaki disease. Within 48 hours of treatment with IVIG and high-dose aspirin, the patient is afebrile with resolving symptoms and a declining CRP. He is discharged on the 9th day of illness on low dose aspirin and a cephalosporin to complete an antibiotic course for concurrent pneumonia.
Conclusion & Discussion: This case illustrates the importance of maintaining a high index of suspicion for an incomplete presentation of Kawasaki disease, particularly among infants. The American Heart Association’s guidelines were updated in 2017 to improve recognition of incomplete Kawasaki disease, particularly among infants who are more likely to have an incomplete presentation, abnormalities of the coronary arteries, and a delayed diagnosis. The key to this patient’s diagnosis was the presence of a bilateral conjunctivitis that spared the limbus. A bilateral, non-exudative conjunctivitis that spares the limbus has been recognized as a feature suggestive of Kawasaki disease for the better part of four decades; our review of the literature suggests this feature is highly specific to the diagnosis of Kawasaki disease.
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陳奇志 and Qizhi Chen. "Analysis of infectious disease data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31239985.
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Chen, Qizhi. "Analysis of infectious disease data /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21841627.
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Ashraf, Shamaila. "Studies on infectious bursal disease virus." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1124124381.
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Thesis (Ph. D.)--Ohio State University, 2005.<br>Title from first page of PDF file. Document formatted into pages; contains xvi, 216 p.; also includes graphics (some col.). Includes bibliographical references (p. 180-216). Available online via OhioLINK's ETD Center
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Pressley, Meagan E. "Infectious Disease Models for the Zebrafish." Fogler Library, University of Maine, 2004. http://www.library.umaine.edu/theses/pdf/PressleyME2004.pdf.
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Baillie, John Kenneth. "Statistical genetics in infectious disease susceptibility." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/17620.
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Death from infectious disease is common heritable, and in many cases a consequence of the host response, rather than direct effects of the pathogen. Since the host response in sepsis is orchestrated by the transmission of a variety of signals, both intra-cellular and inter-cellular, with which we have at least some capacity to intervene, it follows that it should be possible to prevent death through pharmaceutical modulation of inflammatory cascades. So far, it is not. The best candidate therapy for sepsis, activated protein C, failed to live up to initial promise and was ultimately withdrawn from the market in dismal failure. The premise of the work presented here is that a different approach – to develop an understanding of the host response at a genomic level – may yield more tractable insights, specifically into the problem of host susceptibility to influenza, a heritable cause of death in otherwise healthy people and a significant global threat. Since the sequencing of the human genome, it has become possible to identify genomic loci underlying host susceptibility to disease using genome-wide association studies (GWAS), best exemplified by the Wellcome Trust Case Control Consortium. This new technology creates substantial new challenges. The genetic markers associated with a phenotype are rarely causative, frequently in poorly-understood intergenic regions, and tend to have small effect sizes, such that tens or even hundreds of thousands of subjects must be recruited to have sufficient power to detect them. It is therefore not straightforward to translate these genotype-phenotype associations into useful understanding of the role of genes and gene products in disease pathogenesis. Attempts to overcome these challenges in order to discover genomic loci underlying individual susceptibility to infection form the core of this thesis. Ultimately these efforts converge with the development of a new computational method to detect phenotype-associated loci from genome-wide association studies (GWAS) using co-expression at regulatory regions of the genome.
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Ahmad, Iqra. "Infectious Disease: An agent-based simulation." Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/honors/91.
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One of the primary reasons for studying infectious diseases is to improve control and ultimately eradicate the infection from the population (Keeling 2008). An agent base model was designed to observe the spread of disease and the effect of vaccination using the program known as StarLogo- TNG. Experiments were designed, not having a particular disease in mind, and simulations were run to determine the effects of different variables on the vaccination process of a certain population. Goals included observation of how infections spread and how vaccination plays a role in various situations such as, root of the infection, population size, number of providers for vaccination, and the longevity of vaccination.
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Mekaru, Sumiko Rachel. "Environmental risk factors in infectious diseases: studies in waterborne disease outbreaks, Ebola, and Lyme disease." Thesis, Boston University, 2013. https://hdl.handle.net/2144/11144.
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Thesis (Ph.D.)--Boston University<br>The resurgence of infectious diseases and global climate change's potential impact on them has refocused public health's attention on the environment's role in infectious disease. The studies in this dissertation utilize the increased availability of satellite image-derived data sets with fine temporal and geographic granularity and the expansion of epidemiologic methods to explore the relationship between the environment and infectious disease in three settings.
The first study employed a novel study design and analytic methods to investigate the hypothesis that heavy rainfall is an independent risk factor for waterborne disease outbreaks (WBDOs). We found that a location experiencing a heavy rainfall event had about half the odds of a WBDO two or four weeks later than did a location without a heavy rainfall event. The location-based case-crossover study design utilized in this study may help to expand the research methods available to epidemiologists working in this developing field.
The second study employed a location-based case-crossover study design to evaluate standardized differences from historic average of weekly rainfall in locations with a recorded introduction of Ebola into a human. For each 1.0 unit z-score decrease in total rainfall, the odds of an Ebola introduction three weeks later increased by 75%. Given the severity of Ebola outbreaks and the dearth of knowledge about indicators of increased risk, this finding is an important step in advancing our understanding of Ebola ecology.
The third study used GIS methods on remote sensing data to estimate the association between peridomestic forest/non-forest interface within 100, 150, 250 meters and Lyme-associated peripheral facial palsy (LAPFP) among pediatric facial palsy patients. After adjustment for sex, age, and socio-economic status, children with the highest level of forest edge in the three radii of analysis had 2.74 (95% CI 1.15, 6.53), 4.58 (1.84, 11.41), and 5.88 (2.11, 16.4) times the odds of LAPFP compared to children with zero forest edge in those radii. This study is the first to examine environmental risk factors for LAPFP.
Each of these studies advances the techniques used to investigate environmental risk factors for infectious disease through study design, case definition, data used, or exposure definitions.
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Rudd, Matthew Francis, and mikewood@deakin edu au. "Virulence determinants of infectious bursal disease virus." Deakin University. School of Biological and Chemical Sciences, 2003. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20050825.103742.
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The very virulent (vv) pathotype of infectious bursal disease virus (IBDV) has spread rapidly throughout Europe, Asia, and the Middle East. Although Australia is currently unaffected, there remains the potential for incursion of an exotic isolate. The aim of this study was to identify putative virulence determinants of IBDV to facilitate the development of improved diagnostic assays for detection and characterisation of vvIBDV isolates.
Sequencing of Indonesian vvIBDV Tasik94 revealed a unique substitution
[ A¨S222] in the hypervariable region (HVR) of viral protein (VP) VP2, which did not appear to impinge on virulence or antigenicity. Phylogenetic analyses indicated that Tasik94 was closely related to Asian and European vvIBDV strains. Extensive alignment of deduced protein sequences across the HVR of VP2 identified residuesI242 I256 and I294 as putative markers of the vv phcnotype.
Comparison of the pathology induced by mildly-virulent Australian IBDV 002/73 and Indonesian vvIBDV Tasik94, revealed that histological lesions in the spleen, thymus and bone marrow were restricted to Tasik94-infected birds, suggesting the enhanced pathogenicity of vvIBDV might be attributed to replication in non-bursal lymphoid organs.
The biological significance of the VP2 HVR in virulence was assessed using recombinant viruses generated by reverse genetics. Both genomic segments of Australian IBDV 002/73, and recombinant segment A constructs in which the HVR of 002/73 was replaced with the corresponding region of either tissue culture-adapted virus or vvIBDV (Tasik94), were cloned behind T7 RNA polymerase promoter sequences. In vitro transcription/translation of each construct resulted in expression of viral proteins. Co-transfection of synthetic RNA transcripts initiated replication of both tissue culture-adapted parental and recombinant viruses, however attempts to rescue non-adapted viruses in specific-pathogen-free (SPF) chickens were unsuccessful.
Nucleotide sequence variation in the HVR of VP2 was exploited for the development of a new diagnostic assay to rapidly detect exotic IBDV isolates, including vvIBDV, using reverse transcription polymerase chain reaction (RT-PCR) amplification and Bmrl restriction enzyme digestion. The assay was capable of differentiating between endemic and exotic IBDV in 96% of 105 isolates sequenced to date.
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Hofmann, Mathias. "Statistical Models for Infectious Disease Surveillance Counts." Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-66012.
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Beadell, Jon Sumner. "Emerging infectious disease host and parasite perspectives /." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/6744.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.<br>Thesis research directed by: Biology. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Hon, Chung-chau. "Molecular evolution of infectious bursal disease virus." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B38821898.
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Hon, Chung-chau, and 韓鍾疇. "Molecular evolution of infectious bursal disease virus." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B38821898.
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Moody, Adrian John. "Mapping genetic resistance to infectious bursal disease." Thesis, University of Reading, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326754.
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Majumder, Maimuna S. (Maimuna Shahnaz). "Modeling transmission heterogeneity for infectious disease outbreaks." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120885.
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Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references.<br>The transmissibility of a given infectious disease is often described by its basic reproduction number (Ro) - namely, the average number of secondary infections caused by an index case in a fully susceptible population. Typical approaches to modeling transmission dynamics associated with infectious disease outbreaks frequently use Ro to produce deterministic case count projections, in effect treating the affected population as homogeneous (i.e. as if every individual in the population interest has an equal likelihood of passing on the infection of interest). As a result, such approaches often fail to effectively capture transmission dynamics during real-world outbreaks in heterogeneous populations. Here, we use analytical and simulation methods to show that the treatment of Ro as the mean of a random variable (thus permitting the estimation of non-deterministic case count projections) allows us to better assess outbreak trajectory and likelihood of disease propagation in non-homogeneous populations (Chapter 2). We then empirically investigate predictors of in-population transmission heterogeneity (i.e. the fact that some individuals in a given population are more likely than others to pass on the infection of interest) within the context of Middle East Respiratory Syndrome in South Korea using a combination of statistical- and review-driven approaches (Chapter 3). Then, in Chapter 4, we explore how in-population transmission heterogeneity can be used to our advantage through the deployment of risk-informed interventions (i.e. in which individuals who are more likely to pass on the infection of interest are exclusively targeted to receive the intervention) during infectious disease outbreaks. More specifically, we use the analytical and simulation methods first introduced in Chapter 2 - paired with inpopulation transmission heterogeneity data from Chapter 3 - to compare the utility of a variance-informed deployment scheme against a traditional, uniform deployment scheme (i.e. in which every individual has an equal likelihood of receiving the intervention). Finally, building off of our findings in Chapters 2, 3, and 4, we recommend four interrelated policies in Chapter 5 that aim to (1) normalize the treatment and reporting of Ro as the mean of a random variable and (2) improve access to the data required to sufficiently capture population heterogeneity when modeling disease propagation.<br>by Maimuna Shahnaz Majumder.<br>Ph. D. in Engineering Systems
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Ghosh, Saurav. "News Analytics for Global Infectious Disease Surveillance." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/80574.
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Traditional disease surveillance can be augmented with a wide variety of open sources, such
as online news media, twitter, blogs, and web search records. Rapidly increasing volumes of
these open sources are proving to be extremely valuable resources in helping analyze, detect,
and forecast outbreaks of infectious diseases, especially new diseases or diseases spreading
to new regions. However, these sources are in general unstructured (noisy) and construction
of surveillance tools ranging from real-time disease outbreak monitoring to construction of
epidemiological line lists involves considerable human supervision. Intelligent modeling of
such sources using text mining methods such as, topic models, deep learning and dependency
parsing can lead to automated generation of the mentioned surveillance tools. Moreover, realtime
global availability of these open sources from web-based bio-surveillance systems, such
as HealthMap and WHO Disease Outbreak News (DONs) can aid in development of generic
tools which will be applicable to a wide range of diseases (rare, endemic and emerging) across
different regions of the world.
In this dissertation, we explore various methods of using internet news reports to develop
generic surveillance tools which can supplement traditional surveillance systems and aid in
early detection of outbreaks. We primarily investigate three major problems related to infectious
disease surveillance as follows. (i) Can trends in online news reporting monitor and
possibly estimate infectious disease outbreaks? We introduce approaches that use temporal
topic models over HealthMap corpus for detecting rare and endemic disease topics as well as
capturing temporal trends (seasonality, abrupt peaks) for each disease topic. The discovery
of temporal topic trends is followed by time-series regression techniques to estimate future
disease incidence. (ii) In the second problem, we seek to automate the creation of epidemiological
line lists for emerging diseases from WHO DONs in a near real-time setting. For
this purpose, we formulate Guided Epidemiological Line List (GELL), an approach that
combines neural word embeddings with information extracted from dependency parse-trees
at the sentence level to extract line list features. (iii) Finally, for the third problem, we
aim to characterize diseases automatically from HealthMap corpus using a disease-specific
word embedding model which were subsequently evaluated against human curated ones for
accuracies.<br>Ph. D.
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Rivers, Caitlin. "Modeling Emerging Infectious Diseases for Public Health Decision Support." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/52023.
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Emerging infectious diseases (EID) pose a serious threat to global public health. Computational epidemiology is a nascent subfield of public health that can provide insight into an outbreak in advance of traditional methodologies. Research in this dissertation will use fuse nontraditional, publicly available data sources with more traditional epidemiological data to build and parameterize models of emerging infectious diseases. These methods will be applied to avian influenza A (H7N9), Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV), and Ebola virus disease (EVD) outbreaks. This effort will provide quantitative, evidenced-based guidance for policymakers and public health responders to augment public health operations.<br>Ph. D.
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Appiah, Simon K. "Space-time statistical analysis of malaria morbidity incidence cases in Ghana: A geostatistical modelling approach." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2014. https://ro.ecu.edu.au/theses/1398.
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Malaria is one of the most prevalent and devastating health problems worldwide. It is a highly endemic disease in Ghana, which poses a major challenge to both the public health and socio-economic development of the country. Major factors accounting for this situation include variability in environmental conditions and lack of prevention services coupled with host of other socio-economic factors. Ghana’s National Malaria Control Programme (NMCP) risk assessment measures have been largely based on household surveys which provided inadequate data for accurate prediction of new incidence cases coupled with frequent incomplete monthly case reports. These raise concerns about annual estimates on the disease burden and also pose serious threats to efficient public health planning including the country’s quest of reducing malaria morbidity and mortality cases by 75% by 2015.
In this thesis, both geostatistical space-time models and time series seasonal autoregressive integrated moving average (SARIMA) predictive models have been studied and applied to the monthly malaria morbidity cases from both district and regional health facilities in Ghana. The study sought to explore the spatio-temporal distributions of the malaria morbidity incidence and to account for the potential influence of climate variability, with particular focus on producing monthly spatial maps, delimiting areas with high risk of morbidity. This was achieved by modelling the morbidity cases as incidence rates, being the number of new reported cases per 100,000 residents, which together with the climatic covariates were considered as realisations of random processes occurring in space and/or time.
The SARIMA models indicated an upward trend of morbidity incidence in the regions with strong seasonal variation which can be explained primarily by the effects of rainfall, temperature and relative humidity in the month preceding incidence of the disease as well as the morbidity incidence in the previous months. The various spacetime ordinary kriging (STOK) models showed varied spatial and temporal distributions of the morbidity incidence rates, which have increased and expanded across the country over the years. The space-time semivariogram models characterising the spatio-temporal continuity of the incidence rates indicated that the occurrence of the malaria morbidity was spatially and temporally correlated within spatial and temporal ranges varying between 30 and 250 km and 6 and 100 months, respectively. The predicted incidence rates were found to be heterogeneous with highly elevated risk at locations near the borders with neighbouring countries in the north and west as well as the central parts towards the east. The spatial maps showed transition of high risk areas from the north-west to the north-east parts with climatic variables contributing to the variations in the number of morbidity cases across the country. The morbidity incidence estimates were found to be higher during the wet season when temperatures were relatively low whilst low incidence rates were observed in the warm weather period during the dry seasons.
In conclusion, the study quantified the malaria morbidity burden in Ghana to produce evidence-based monthly morbidity maps, illustrating the risk patterns of the morbidity of the disease. Increased morbidity risk, delimiting the highest risk areas was also established. This statistical-based modelling approach is important as it allows shortterm prediction of the malaria morbidity incidence in specific regions and districts and also helps support efficient public health planning in the country.
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Alsan, Marcella Mousavi. "Infectious Diseases and Economic Development." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10321.
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This dissertation contains three essays analyzing how disease (particularly communicable disease) and development interact. The first chapter explores how TseTse-transmitted Trypanosomiasis influenced African development. The second essay seeks to understand why the HIV epidemic declined in Uganda. The third study investigates the effect of population health on foreign direct investment. In the first essay, I examine the effect of the TseTse fly on African historical development. African ethnicities in TseTse suitable areas are found to be more reliant on indigenous slavery, shifting agriculture and are less urbanized as of the 19th century. TseTse suitability does not predict such correlations outside of Africa, where the fly does not exist. Africa would have been more similar to Eurasia in the absence of the fly. Current economic performance appears to be affected by the fly through its effect on historical institutions. In the second essay, David Cutler and I study how and why the HIV epidemic declined in Uganda. We identify reduced pre-marital sexual activity among young women as the most important factor leading to the decline in HIV. We next explore why young women would have changed their behavior. Using two-stage least-squares and difference-in-difference estimators, we find increases in girls’ secondary school enrollment, brought about by a targeted education policy, explains half the reduction in HIV in this cohort and approximately one-third of the overall decline. In the last essay, David Bloom, David Canning and I investigate the role of population health on foreign direct investment (FDI). We conduct a panel data analysis of 74 industrialized and developing countries over 1980-2000. Our main finding is that gross inflows of FDI are positively and significantly influenced by low population health in low- and middle-income countries. Our estimates suggest that raising life expectancy by one year increases gross FDI inflows by 9%, after controlling for other relevant variables. These findings are consistent with the view that health is an integral component of human capital for developing countries.<br>Economics
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Korobeinikov, Andrei. "Stability and bifurcation of deterministic infectious disease models." Thesis, University of Auckland, 2001. http://wwwlib.umi.com/dissertations/fullcit/3015611.
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Autonomous deterministic epidemiological models are known to be asymptotically stable. Asymptotic stability of these models contradicts observations. In this thesis we consider some factors which were suggested as able to destabilise the system. We consider discrete-time and continuous-time autonomous epidemiological models. We try to keep our models as simple as possible and investigate the impact of different factors on the system behaviour. Global methods of dynamical systems theory, especially the theory of bifurcations and the direct Lyapunov method are the main tools of our analysis. Lyapunov functions for a range of classical epidemiological models are introduced. The direct Lyapunov method allows us to establish their boundedness and asymptotic stability. It also helps investigate the impact of such factors as susceptibles' mortality, horizontal and vertical transmission and immunity failure on the global behaviour of the system. The Lyapunov functions appear to be useful for more complicated epidemiological models as well. The impact of mass vaccination on the system is also considered. The discrete-time model introduced here enables us to solve a practical problem-to estimate the rate of immunity failure for pertussis in New Zealand. It has been suggested by a number of authors that a non-linear dependence of disease transmission on the numbers of infectives and susceptibles can reverse the stability of the system. However it is shown in this thesis that under biologically plausible constraints the non-linear transmission is unable to destabilise the system. The main constraint is a condition that disease transmission must be a concave function with respect to the number of infectives. This result is valid for both the discrete-time and the continuous-time models. We also consider the impact of mortality associated with a disease. This factor has never before been considered systematically. We indicate mechanisms through which the disease-induced mortality can affect the system and show that the disease-induced mortality is a destabilising factor and is able to reverse the system stability. However the critical level of mortality which is necessary to reverse the system stability exceeds the mortality expectation for the majority of human infections. Nevertheless the disease-induced mortality is an important factor for understanding animal diseases. It appears that in the case of autonomous systems there is no single factor able to cause the recurrent outbreaks of epidemics of such magnitudes as have been observed. It is most likely that in reality they are caused by a combination of factors.<br>Subscription resource available via Digital Dissertations
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Davenport, Miles Philip. "Molecular analysis of HLA associations with infectious disease." Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297073.
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羅文新 and Man-sun Law. "DNA vaccine against chicken infectious bursal disease virus." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31221221.
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Szeszko, Jeffrey Scott. "The genetics of immune-mediated and infectious disease." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611902.
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Rojek, Amanda. "Improving patient centred research during infectious disease outbreaks." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:8a53052f-9585-4709-a06e-15586826efce.
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Emerging infectious diseases (EIDs) constitute an important global health security problem. During EID outbreaks, patient centred research can play a significant role in informing evidence-based care for patients, in calibrating public health responses, and in directing effective policy and research. However, to date, this type of research has been limited in impact. This thesis sets out to improve the value of patient centred research in combating EID outbreaks. It provides a structured analysis of what has previously constrained efforts to rapidly accumulate high-quality evidence. It provides primary data from research conducted during an outbreak, and conducted in an outbreak vulnerable setting. And it provides recommendations that aim to facilitate high-quality data collection in future events. This thesis contains four results chapters. Chapter 2 systematically reviews elements of the research response to two EID outbreaks of public health importance. Chapter 3 provides findings of a phase II clinical trial of an investigational therapy for Ebola virus disease (EVD), contextualises the utility of this and comparable work in improving patient care, and discusses the operational feasibility of such work during an epidemic. Chapter 4 focuses specifically on improving one element - disease characterisation - during EID outbreaks. It achieves this through presenting a systematic analysis of bias in the characterisation of EVD and recommends how to prioritise data gathering for high-risk pathogens. Chapter 5 exemplifies how clinical data collection practices can progress between outbreaks. It is the first stage of work undertaken to improve the clinical characterisation of communicable diseases in the vulnerable environment of refugee camps. This thesis demonstrates progress towards having higher quality clinical research conducted during the time frame of an epidemic. Future work can focus on the most important barriers to accelerating research, now that these have been more clearly defined.
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Nsubuga, Rebecca Namugabwe. "Statistical inference for infectious disease data of animals." Thesis, University of Edinburgh, 2004. http://hdl.handle.net/1842/30591.
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This thesis primarily explores parameter methods as applied to data generated from an experimental infection with foot and mouth disease (FMD) virus in sheep. Data were generated from two experiments involving four groups of sheep, housed under restricted mixing, where sheep in the initial group were inoculated with type O FMD virus. The aim of the analysis is to investigate the presence of any trend in the infection rate with increased generation. The infection process of FMD virus in sheep can be modelled using chain binomial models and generalized linear models. However, application of these methods requires that the epidemic chain of infection pathways be known. The set of true pathways is an unobservable quantity and, in general, infectious disease data will be incomplete because the infection process is only partially observed. One proposed strategy is subjectively to assign an epidemic chain to the data and to analyse it on this basis. This approach is evaluated. An alternative to modelling the FMD infection process for individual sheep is to consider the transmission among groups of sheep, thus avoiding the need to make inference about individual infection pathways. Martingale methods and maximum likelihood estimation methods are used to estimate the typical infection rate β applying to groups of sheen where the aim is to investigate whether the infection rate changes across groups. The expected total infection exposure for each group is estimated. This entails knowledge of the time of infection, the latent period and the infectious period for each infected sheep. Parameters for the latent period and infectious period distributions are estimated from the data. A joint distribution of time to infection and latent period is formulated from which expected values for time to infection and the latent period for each infected sheep are estimated.
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Natour, Mohammad Qasem. "Vaccination of chicks against infectious bursal disease virus /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487940665436333.
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Knoblich, Heidi Vivian. "Pathogenicity and immunogenicity of infectious bursal disease virus /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488193665236897.
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Cathcart, Laura A. "Novice and expert comprehensive reasoning about infectious disease." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8590.
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Thesis (M.A.) -- University of Maryland, College Park, 2008.<br>Thesis research directed by: Dept. of Curriculum and Instruction. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Law, Man-sun. "DNA vaccine against chicken infectious bursal disease virus /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20128393.
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Wombwell, Emma Louise. "Emerging infectious disease and the trade in amphibians." Thesis, University of Kent, 2014. https://kar.kent.ac.uk/48014/.
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Amphibians are the most threatened class of vertebrate, and rates of species decline and extinction far exceed those seen historically. Habitat loss, climate change, over-exploitation and emerging infectious disease have all been identified as threatening processes. The trade in amphibians has been implicated in over-exploitation through the harvesting of wild animals, and as an important pathway for the global spread of the fungal pathogen, Batrachochytrium dendrobatidis (Bd). However, there are no analyses of how Bd may spread through the trade chain. This thesis addresses this issue by (1) determining the prevalence of Bd at different stages of the trade chain; (2) examining knowledge, husbandry protocols and biosecurity among retailers and (3) assessing the risk of Bd dissemination into the wild in the UK. Approximately 20,000 amphibians from at least 11 countries enter the UK annually via Heathrow Animal Reception Centre. Overall Bd prevalence was 3.6%, but was confined to six of the 43 genera encountered, and only detected in shipments from the USA and Tanzania. Amphibians were sold by 30% of the estimated 3500 livestock retailers in the UK, but made a low contribution to overall income. Disease awareness and knowledge in retailers was found to be lacking, although husbandry standards were deemed to be appropriate. Mortality appeared to be influenced by restocking methods and number of species held, but mass die-offs as a result of disease were generally uncommon. Screening of over 2000 amphibians from 148 retailers for Bd revealed a prevalence of 5.8%, but the geographic distribution of infection in the UK was patchy, and was more prominent in aquatic species. A risk assessment conducted according to the framework set out by the World Organisation of Animal Health, identified regions and sections of the trade that pose the greatest threats in terms of introducing Bd, and assessed various mitigation measures. The consequences of novel strains of Bd and a second, recently discovered Batrachochytrium species were found to pose a risk to both native UK and captive amphibians. As trade bans are unlikely to be feasible or effective, alternative measures to mitigate the impact of disease are evaluated.
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Ye, X., J. N. Van, F. M. Munoz, et al. "Noroviruses as a Cause of Diarrhea in Immunocompromised Pediatric Hematopoietic Stem Cell and Solid Organ Transplant Recipients." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etsu-works/1490.
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Case reports describe significant norovirus gastroenteritis morbidity in immunocompromised patients. We evaluated norovirus pathogenesis in prospectively enrolled solid organ (SOT) and hematopoietic stem cell transplant (HSCT) patients with diarrhea who presented to Texas Children's Hospital and submitted stool for enteric testing. Noroviruses were detected by real-time reverse transcription polymerase chain reaction. Clinical outcomes of norovirus diarrhea and non-norovirus diarrhea patients, matched by transplanted organ type, were compared. Norovirus infection was identified in 25 (22%) of 116 patients, more frequently than other enteropathogens. Fifty percent of norovirus patients experienced diarrhea lasting ≥14 days, with median duration of 12.5 days (range 1–324 days); 29% developed diarrhea recurrence. Fifty-five percent of norovirus patients were hospitalized for diarrhea, with 27% requiring intensive care unit (ICU) admission. One HSCT recipient developed pneumatosis intestinalis. Three HSCT patients expired ≤6 months of norovirus diarrhea onset. Compared to non-norovirus diarrhea patients, norovirus patients experienced significantly more frequent ICU admission (27% vs. 0%, p = 0.02), greater serum creatinine rise (median 0.3 vs. 0.2 mg/dL, p = 0.01), and more weight loss (median 1.6 vs. 0.6 kg, p < 0.01). Noroviruses are an important cause of diarrhea in pediatric transplant patients and are associated with significant clinical complications.
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Elender, Frances. "The resurgence of tuberculosis in England and Wales." Thesis, University of East Anglia, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323353.
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Tabrizi, Shervin. "Leveraging Genomic Signatures to Understand Human Disease: Applications in Infectious Disease and Cancer." Thesis, Harvard University, 2017. http://nrs.harvard.edu/urn-3:HUL.InstRepos:32676125.
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Genomics has been transformative to the study of human evolution and disease. With the dropping cost and increased availability of genome sequencing, it is now possible to probe the genetic mediators of human disease at an unprecedented level. My own research grew out of earlier work on the genomic signatures of natural selection in humans. As an undergraduate, I investigated the evidence for recent positive selection in large-scale genomic data, identifying pathways that appear to be targeted by evolution and prioritizing promising candidate variants for functional follow-up. In medical school, I turned my attention to applying tools in genomics and evolution to the study of human disease. In this thesis, I present the results of that work applied to two major contributors to human morbidity and mortality: infectious disease and malignancy.
Motivated by results from earlier work on genomic signals of recent adaptation in a West African population, I investigate genetic resistance to Lassa fever, a viral hemorrhagic disease endemic to West Africa. Focusing on a gene that is critical to Lassa infection and carries a signature of positive selection in the Yoruba population in Nigeria, I demonstrate that the same putative selected haplotype is present in other West African populations, but at different frequencies. Furthermore, I show evidence that the observed differences in frequency show correlation with the geographic distribution of Lassa virus and historical spread of the virus based on viral sequencing data. I test this haplotype for association with Lassa fever and demonstrate evidence of a protective effect. In a genome-wide association study for resistance to Lassa fever, I also identify preliminary genome-wide significant associations and promising variants for replication and follow-up.
In the second part of this thesis, I focus on genomic study of human malignancy. I collaborate with a team to investigate the signatures of mutational forces in the cancer genome. We develop a novel computational framework to extract signatures from large-scale tumor sequencing data. Through this approach, we provide unbiased new estimates for the number and characteristics of the mutational processes that shape the cancer genome. We also investigate these signatures at an unprecedented level of resolution and show how they have the potential to reveal new mechanistic insights into the process of DNA damage repair and mutagenesis in cancer. Finally, we show how these signatures can reveal important clinical insights and identify subsets of tumors within the same tumor type that are dominated by different mutational processes. Our results are in stark contrast to the currently accepted model of mutational signatures in cancer, and have broad implications on our fundamental understanding of cancer biology and the future direction of the field.
Although the diseases investigated here are diverse, the common theme underpinning my approach is to leverage tools in evolution and genomics to shed new light on the most devastating human diseases. Through this approach, I hope to extend our understanding of the biology of these disease processes, with implications on new therapeutic and public health interventions.
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Anroman, Gilda Marie. "Infectious disease in Philadelphia, 1690-1807 an ecological perspective /." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3700.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.<br>Thesis research directed by: American Studies. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Donnelly, Ruairi. "Eco-evolutionary modelling of infectious disease and host resistance." Thesis, Heriot-Watt University, 2015. http://hdl.handle.net/10399/2914.
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In this work we take an evolutionary invasion analysis approach to modelling evolution and use it to describe the selection pressures underlying epidemiological traits in natural host populations harboring endemic infections. Throughout this work a logistic form for host-birth rate allows for disease dependent population dynamics so that the detrimental e ects of infection can be modelled and we also consider the more neglected detrimental e ect whereby infection is linked to infertility. To begin with we give a theoretical introduction to the framework of adaptive dynamics and illustrate it through the established example of the evolution of parasite virulence. We then extend the results to account for condition dependent virulence which is an interaction between host condition (i.e. host stress) and virulence, that has recently generated much attention from empiricists. Many natural systems are seasonal, potentially leading to seasonal stress, and we show how to conduct a study for seasonal host populations and analyse its role in the evolution of density dependent virulence. We then turn our attention to the evolution of resistance beginning with a perspective on the relationship between investment in acquired immunity and the lifespan of hosts and parasites. In our penultimate chapter we derive explicit expressions for optimal investment in the various modes of resistance for a range of epidemiological scenarios. These expressions are then key to understanding our nal chapter where we elaborate further on the established theory by allowing for parasite diversity. The nal chapter highlights the central role played by speci city in the evolution of host defence. Since our approach throughout has been to build complexity onto a baseline model we conclude our discussion with a short section interpreting established results on the coevolution of virulence and resistance from the perspective of our results on the evolution of virulence and resistance.
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Marmara, Vincent Anthony. "Prediction of Infectious Disease outbreaks based on limited information." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/24624.
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The last two decades have seen several large-scale epidemics of international impact, including human, animal and plant epidemics. Policy makers face health challenges that require epidemic predictions based on limited information. There is therefore a pressing need to construct models that allow us to frame all available information to predict an emerging outbreak and to control it in a timely manner. The aim of this thesis is to develop an early-warning modelling approach that can predict emerging disease outbreaks. Based on Bayesian techniques ideally suited to combine information from different sources into a single modelling and estimation framework, I developed a suite of approaches to epidemiological data that can deal with data from different sources and of varying quality. The SEIR model, particle filter algorithm and a number of influenza-related datasets were utilised to examine various models and methodologies to predict influenza outbreaks. The data included a combination of consultations and diagnosed influenza-like illness (ILI) cases for five influenza seasons. I showed that for the pandemic season, different proxies lead to similar behaviour of the effective reproduction number. For influenza datasets, there exists a strong relationship between consultations and diagnosed datasets, especially when considering time-dependent models. Individual parameters for different influenza seasons provided similar values, thereby offering an opportunity to utilise such information in future outbreaks. Moreover, my findings showed that when the temperature drops below 14°C, this triggers the first substantial rise in the number of ILI cases, highlighting that temperature data is an important signal to trigger the start of the influenza epidemic. Further probing was carried out among Maltese citizens and estimates on the under-reporting rate of the seasonal influenza were established. Based on these findings, a new epidemiological model and framework were developed, providing accurate real-time forecasts with a clear early warning signal to the influenza outbreak. This research utilised a combination of novel data sources to predict influenza outbreaks. Such information is beneficial for health authorities to plan health strategies and control epidemics.
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Licata, Matthew J. "The efficacy of combined infectious bronchitis/Newcastle disease vaccines." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 112 p, 2007. http://proquest.umi.com/pqdlink?did=1253510101&Fmt=7&clientId=79356&RQT=309&VName=PQD.
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Howard, Sally Claire. "Statistical estimation of epidemiological parameters relating to infectious disease." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365804.
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Xue, Chunyi, and 薛春宜. "Molecular characterization of infectious bursal disease virus (IBDV) receptor." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31246187.
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Wark, Kim Louise. "Expression and processing of infectious bursal disease virus proteins." Thesis, University of Hertfordshire, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323651.
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Gog, Julia Rose. "The dynamics of multiple strains of an infectious disease." Thesis, University of Cambridge, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.619522.
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Hansen, Victoria Lee. "Recent Infectious Disease Mortality Trends in the United States." Thesis, The University of Arizona, 2015. http://hdl.handle.net/10150/594558.
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Importance: Infectious diseases present an ever-changing threat to public health. Analysis of pathogen-linked mortality trends is elucidatory to infectious disease burden. Objective: To describe major shifts in United States infectious disease mortality trends from 1900-2013 with emphasis on recent changes for1980-2013. Design: Ecological study of infectious disease mortality in the United States. Setting: Infectious disease deaths were summed from Vital Statistic Reports from 1900-1967. Infectious disease deaths from 1968-2013 were extracted from the Centers for Disease Control and Prevention Wonder database and tallied. Participants: Deaths among United States residents from 1900-2013. Main Outcome Measures: Crude and age-adjusted mortality rates for key infectious diseases including emerging infections, specifically human immunodeficiency virus and certain vector-borne diseases, re-emerging diseases, specifically, vaccine-preventable diseases and pathogens with drug-resistant strains, and newly defined infectious diseases such as cervical cancer due to human papilloma virus. Results: While human immunodeficiency virus mortality has been declining since 1995 (average annual percent change = 10.6%, 95% Confidence Interval (CI) [-13.1, -7.9]), recent years have seen an increase in infectious disease mortality related to vector-borne diseases. Specifically, with the emergence of West Nile virus in the United States, vector-borne disease mortality increased from 34.5 deaths per year (1980-2001) to 141.7 deaths per year (2002-2013). Vaccine preventable disease mortality continues to decrease with an average annual percent change of 2.4%, 95% CI [-2.8, -2.0] from 1980-2013. Mortality due to drug-resistant strains of infectious diseases is increasing at an average annual percent change of 0.8%, 95% CI [0.1, 1.6] from 1980-2013. Finally, mortality due to a disease previously not classified as infectious, cervical cancer, has been decreasing at an average annual percent change of 1.4%, 95% CI [-1.7, -1.1] since 1980. Conclusions: Despite the overall downward trends in infectious disease mortality, they still account for 43 per 100,000 deaths annually in the United States. Specific diseases and disease groups evaluated in this study show inconsistent, but concerning, trends across emerging, re-emerging, and newly defined infectious diseases, indicating that infectious diseases remain a public health concern.
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Bingham, Adrienna N. "Controlling Infectious Disease: Prevention and Intervention Through Multiscale Models." W&M ScholarWorks, 2019. https://scholarworks.wm.edu/etd/1582642581.
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Controlling infectious disease spread and preventing disease onset are ongoing challenges, especially in the presence of newly emerging diseases. While vaccines have successfully eradicated smallpox and reduced occurrence of many diseases, there still exists challenges such as fear of vaccination, the cost and difficulty of transporting vaccines, and the ability of attenuated viruses to evolve, leading to instances such as vaccine derived poliovirus. Antibiotic resistance due to mistreatment of antibiotics and quickly evolving bacteria contributes to the difficulty of eradicating diseases such as tuberculosis. Additionally, bacteria and fungi are able to produce an extracellular matrix in biofilms that protects them from antibiotics/antifungals. Mathematical models are an effective way of measuring the success of various control measures, allowing for cost savings and efficient implementation of those measures. While many models exist to investigate the dynamics on a human population scale, it is also beneficial to use models on a microbial scale to further capture the biology behind infectious diseases. In this dissertation, we develop mathematical models at several spatial scales to help improve disease control. At the scale of human populations, we develop differential equation models with quarantine control. We investigate how the distribution of exposed and infectious periods affects the control efficacy and suggest when it is important for models to include realistically narrow distributions. At the microbial scale, we use an agent-based stochastic spatial simulation to model the social interactions between two yeast strains in a biofilm. While cheater strains have been proposed as a control strategy to disrupt the harmful cooperative biofilm, some yeast strains cooperate only with other cooperators via kin recognition. We study under what circumstances kin recognition confers the greatest fitness benefit to a cooperative strain. Finally, we look at a multiscale, two-patch model for the dynamics between wild-type (WT) poliovirus and defective interfering particles (DIPs) as they travel between organs. DIPs are non-viable variants of the WT that lack essential elements needed for reproduction, causing them to steal these elements from the WT. We investigate when DIPs can lower the WT population in the host.
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Venkatachalam, Sangeeta. "Modeling Infectious Disease Spread Using Global Stochastic Field Simulation." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5335/.
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Susceptibles-infectives-removals (SIR) and its derivatives are the classic mathematical models for the study of infectious diseases in epidemiology. In order to model and simulate epidemics of an infectious disease, a global stochastic field simulation paradigm (GSFS) is proposed, which incorporates geographic and demographic based interactions. The interaction measure between regions is a function of population density and geographical distance, and has been extended to include demographic and migratory constraints. The progression of diseases using GSFS is analyzed, and similar behavior to the SIR model is exhibited by GSFS, using the geographic information systems (GIS) gravity model for interactions. The limitations of the SIR and similar models of homogeneous population with uniform mixing are addressed by the GSFS model. The GSFS model is oriented to heterogeneous population, and can incorporate interactions based on geography, demography, environment and migration patterns. The progression of diseases can be modeled at higher levels of fidelity using the GSFS model, and facilitates optimal deployment of public health resources for prevention, control and surveillance of infectious diseases.
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Vallet, Victor Jay. "Infection and Infectious Disease US Military Medicine in the Pacific Theater of Operations during WWII." Thesis, The University of Arizona, 2009. http://hdl.handle.net/10150/193017.
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Brierley, Liam. "The ecology of emerging diseases : virulence and transmissibility of human RNA viruses." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/22067.
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Emerging infectious diseases continue to represent serious threats to global human health. Novel zoonotic pathogens are continually being recognised, and some ultimately cause significant disease burdens and extensive epidemics. Research and public health initiatives often face emerging pathogens with limited knowledge and resources. Inferences from empirical modelling have begun to uncover the factors determining cross-species transmission and emergence in humans, and subsequently guide risk assessments. However, the dynamics of virulence and transmissibility during the process of emergence are not well understood. Here, I focus on RNA viruses, a priority pathogen type because of their potential for rapid evolution. I use comparative trait-based analyses to investigate how aspects of both host and virus ecology contribute to the risk of virulence and transmissibility within human RNA viruses. To explore these questions, data were collected via systematic literature search protocols. In the first half of this thesis, I focus on viral determinants of virulence and transmissibility. I ask whether virulence can be predicted by viral traits of tissue tropism, transmission route, transmissibility and taxonomic classification. Using a machine learning approach, the most prominent predictors of severe virulence were breadth of tissue tropism, and nonvector-borne transmission routes. When applied to newly reported viruses as test set, the final model predicted disease severity with 87% accuracy. Next, I assess support for hypothesised routes of adaptation during emergence using phylogenetic state-switching models. Propensity for adaptation in small ‘stepwise’ movements versus large ‘off-the-shelf’ jumps differed between virus taxa, though no single route dominated, suggesting multiple independent trajectories of adaptation to human hosts. In addition, phylogenetic regressions showed vector and respiratory-transmitted viruses to be more likely to progress through early stages of emergence. In the second half of this thesis, I focus on how dynamics of virulence and transmissibility differ with respect to nonhuman host diversity, identity, and ecology. Using a regression framework, I observe that viruses with a broader mammalian host range exhibited higher risk of severe virulence, but lower risk of transmissibility, which may reflect potential trade-offs of host specificity. Furthermore, viruses with artiodactyl hosts exhibited lower risk of severe virulence and viruses with bat or nonhuman primate hosts exhibited higher risk of transmissibility. Next, I test hypotheses that mammal species with faster-paced life history may be predisposed to host viruses with greater virulence and transmissibility. Mammal body mass was used as an established proxy for pace of life history. In regression analyses, mammals with faster-paced life history hosted more viruses with severe virulence, though evidence for a relationship with transmissibility was limited. The broad-scale associations presented in this thesis suggest the evolution of virulence and human-to-human transmissibility during zoonotic emergence is a multifactorial, highly dynamic process influenced by both virus and host ecology. Despite this, general characteristics of high-risk emerging viruses are evident. For example, severe virulence was associated with broad niche diversity of both tissue tropisms at the within-host scale, and host species at the macroecological scale. However, risk factors for virulence and human-to-human transmissibility often did not coincide, which may imply an overarching trade-off between these traits. These analyses can contribute to preparedness and direction within public health strategies by identifying likely candidates for high-impact emergence events among previously known and newly discovered human viruses. The inherent connectivity between RNA viruses, their nonhuman hosts and the resulting implications for human health emphasise the holistic nature of emerging diseases and supports the One Health perspective for infectious disease research.
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McInnis, Leah Russell. "Law and the control of infectious disease during extraordinary emergencies." Thesis, Lancaster University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404255.
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巫志偉 and Chi-wai Mo. "Prevention and therapy of infectious bursal disease by molecular approaches." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B30253329.
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Yeung, Wing-shing, and 楊永成。. "Development of a subunit vaccine against infectious bursal disease virus." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31222055.
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Prakash, Manyu. "Leukocytes in the cervical epithelium in health and infectious disease." Thesis, University of London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404575.
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