Gotowe bibliografie tematyczne / Legionnaires' Disease Mathematical models

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  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji

Gotowa bibliografia na temat „Legionnaires' Disease Mathematical models”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 1 lutego 2022

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Artykuły w czasopismach na temat "Legionnaires' Disease Mathematical models"

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Cassell, Kelsie, Paul Gacek, Therese Rabatsky-Ehr, Susan Petit, Matthew Cartter, and Daniel M. Weinberger. "Estimating the True Burden of Legionnaires’ Disease." American Journal of Epidemiology 188, no. 9 (June 21, 2019): 1686–94. http://dx.doi.org/10.1093/aje/kwz142.

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Abstract Over the past decade, the reported incidence of Legionnaires’ disease (LD) in the northeastern United States has increased, reaching 1–3 cases per 100,000 population. There is reason to suspect that this is an underestimate of the true burden, since LD cases may be underdiagnosed. In this analysis of pneumonia and influenza (P&I) hospitalizations, we estimated the percentages of cases due to Legionella, influenza, and respiratory syncytial virus (RSV) by age group. We fitted mixed-effects models to estimate attributable percents using weekly time series data on P&I hospitaliza
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Dobson, A. "Mathematical models for emerging disease." Science 346, no. 6215 (December 11, 2014): 1294–95. http://dx.doi.org/10.1126/science.aaa3441.

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Bakshi, Suruchi, Vijayalakshmi Chelliah, Chao Chen, and Piet H. van der Graaf. "Mathematical Biology Models of Parkinson's Disease." CPT: Pharmacometrics & Systems Pharmacology 8, no. 2 (November 2, 2018): 77–86. http://dx.doi.org/10.1002/psp4.12362.

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Grassly, Nicholas C., and Christophe Fraser. "Mathematical models of infectious disease transmission." Nature Reviews Microbiology 6, no. 6 (May 13, 2008): 477–87. http://dx.doi.org/10.1038/nrmicro1845.

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KLEIN, EILI, RAMANAN LAXMINARAYAN, DAVID L. SMITH, and CHRISTOPHER A. GILLIGAN. "Economic incentives and mathematical models of disease." Environment and Development Economics 12, no. 5 (October 2007): 707–32. http://dx.doi.org/10.1017/s1355770x0700383x.

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The fields of epidemiological disease modeling and economics have tended to work independently of each other despite their common reliance on the language of mathematics and exploration of similar questions related to human behavior and infectious disease. This paper explores the benefits of incorporating simple economic principles of individual behavior and resource optimization into epidemiological models, reviews related research, and indicates how future cross-discipline collaborations can generate more accurate models of disease and its control to guide policy makers.
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Meltzer, M. I., and R. A. I. Norval. "Mathematical models of tick-borne disease transmission." Parasitology Today 9, no. 8 (August 1993): 277–78. http://dx.doi.org/10.1016/0169-4758(93)90116-w.

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Donovan, Graham M. "Multiscale mathematical models of airway constriction and disease." Pulmonary Pharmacology & Therapeutics 24, no. 5 (October 2011): 533–39. http://dx.doi.org/10.1016/j.pupt.2011.01.003.

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Medley, Graham F. "Mathematical models of tick-borne disease transmission: Reply." Parasitology Today 9, no. 8 (August 1993): 292. http://dx.doi.org/10.1016/0169-4758(93)90123-w.

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DUNN, C. E., B. ROWLINGSON, R. S. BHOPAL, and P. DIGGLE. "Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling." Epidemiology and Infection 141, no. 4 (June 12, 2012): 687–96. http://dx.doi.org/10.1017/s095026881200101x.

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SUMMARYThis study investigated the relationships between Legionnaires' disease (LD) incidence and weather in Glasgow, UK, by using advanced statistical methods. Using daily meteorological data and 78 LD cases with known exact date of onset, we fitted a series of Poisson log-linear regression models with explanatory variables for air temperature, relative humidity, wind speed and year, and sine-cosine terms for within-year seasonal variation. Our initial model showed an association between LD incidence and 2-day lagged humidity (positive, P = 0·0236) and wind speed (negative, P = 0·033). Howeve
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De Gaetano, Andrea, Thomas Hardy, Benoit Beck, Eyas Abu-Raddad, Pasquale Palumbo, Juliana Bue-Valleskey, and Niels Pørksen. "Mathematical models of diabetes progression." American Journal of Physiology-Endocrinology and Metabolism 295, no. 6 (December 2008): E1462—E1479. http://dx.doi.org/10.1152/ajpendo.90444.2008.

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Few attempts have been made to model mathematically the progression of type 2 diabetes. A realistic representation of the long-term physiological adaptation to developing insulin resistance is necessary for effectively designing clinical trials and evaluating diabetes prevention or disease modification therapies. Writing a good model for diabetes progression is difficult because the long time span of the disease makes experimental verification of modeling hypotheses extremely awkward. In this context, it is of primary importance that the assumptions underlying the model equations properly refl
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Rozprawy doktorskie na temat "Legionnaires' Disease Mathematical models"

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Wilmot, Peter Nicholas. "Modelling cooling tower risk for Legionnaires' Disease using Bayesian Networks and Geographic Information Systems." Title page, contents and conclusion only, 1999. http://web4.library.adelaide.edu.au/theses/09SIS.M/09sismw744.pdf.

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Includes bibliographical references (leaves 115-120) Establishes a Bayesian Belief Network (BBN) to model uncertainty of aerosols released from cooling towers and Geographic Information Systems (GIS) to create a wind dispersal model and identify potential cooling towers as the source of infection. Demonstrates the use of GIS and BBN in environmental epidemiology and the power of spatial information in the area of health.
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Roberts, Paul Allen. "Mathematical models of the retina in health and disease." Thesis, University of Oxford, 2015. http://ora.ox.ac.uk/objects/uuid:385f61c4-4ff1-45d3-bdb2-41338c174025.

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The retina is the ocular tissue responsible for the detection of light. Its extensive demand for oxygen, coupled with a concomitant elevated supply, renders this tissue prone to both hypoxia and hyperoxia. In this thesis, we construct mathematical models of the retina, formulated as systems of reaction-diffusion equations, investigating its oxygen-related dynamics in healthy and diseased states. In the healthy state, we model the oxygen distribution across the human retina, examining the efficacy of the protein neuroglobin in the prevention of hypoxia. It has been suggested that neuroglobin co
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Oduro, Bismark. "Mathematical Models of Triatomine (Re)infestation." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1458563770.

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Zhang, Xu-Sheng. "Mathematical models of plant disease epidemics that involve virus interactions." Thesis, University of Greenwich, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327341.

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Bell, Sally Sue. "Mathematical models assessing the importance of disease on ecological invasions." Thesis, Heriot-Watt University, 2010. http://hdl.handle.net/10399/2316.

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A general understanding of the role that both shared disease and competition may play in ecological invasions is lacking. We develop a theoretical framework to determine the role of disease, in addition to competition, in invasions. We first investigate the e ect of disease characteristics on the replacement time of a native species by an invader. The outcome is critically dependent on the relative e ects that the disease has on the two species and less dependent on the basic epidemiological characteristics of the interaction. This framework is extended to investigate the e ect of disease on t
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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.
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Ning, Yao, and 宁耀. "The use of stochastic models of infectious disease transmission for public health: schistosomiasis japonica." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B4553097X.

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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
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Kwong, Kim-hung, and 鄺劍雄. "Spatio-temporal transmission modelling of an infectious disease: a case study of the 2003 SARS outbreak in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45693900.

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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 t
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Książki na temat "Legionnaires' Disease Mathematical models"

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Center for Emerging Issues (U.S.). Overview of predictive infectious-disease modeling. Washington, D.C.]: United States Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Center for Emerging Issues, 2005.

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Courant Institute of Mathematical Sciences, ed. Mathematical methods for analysis of a complex disease. New York: Courant Institute of Mathematical Sciences, 2011.

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Karakawa, Masanori. A mathematical approach to cardiovascular disease: Mechanics of blood circulation. Tokyo: Kokuseido Pub. Co., 1998.

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Modelling Disease Ecology With Mathematics. Springfield, MO: American Institute of Mathematical Sciences, 2008.

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Roy, Priti Kumar. Mathematical Models for Therapeutic Approaches to Control HIV Disease Transmission. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-852-6.

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Zawołek, M. W. A physical theory of focus development in plant disease. Wageningen, Netherlands: Agricultural University, 1989.

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Kremer, Michael. Integrating behavioral choice into epidemiological models of AIDS. Cambridge, MA: National Bureau of Economic Research, 1996.

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Gumel, Abba B. Modeling paradigms and analysis of disease transmission models. Providence, R.I: American Mathematical Society, 2010.

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Stanecki, De Lay Karen, ed. The demographic impact of an AIDS epidemic on an African country: Application of the iwgAIDS model. Washington, D.C: Center for International Research, U.S. Bureau of the Census, 1991.

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International Association for the Study of Insurance Economics. General Assembly. AIDS and insurance: Documents and texts from the panel of the 15th General Assembly of the Geneva Association. Genève: "Association", 1988.

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Części książek na temat "Legionnaires' Disease Mathematical models"

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Brown, Andrew S., Ian R. van Driel, and Elizabeth L. Hartland. "Mouse Models of Legionnaires’ Disease." In Current Topics in Microbiology and Immunology, 271–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/82_2013_349.

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Kretzschmar, Mirjam, and Jacco Wallinga. "Mathematical Models in Infectious Disease Epidemiology." In Modern Infectious Disease Epidemiology, 209–21. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-93835-6_12.

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Dietz, K., and D. Schenzle. "Mathematical Models for Infectious Disease Statistics." In A Celebration of Statistics, 167–204. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4613-8560-8_8.

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Kühl, Michael, Barbara Kracher, Alexander Groß, and Hans A. Kestler. "Mathematical Models of Wnt Signaling Pathways." In Wnt Signaling in Development and Disease, 153–60. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118444122.ch11.

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Roy, Priti Kumar. "Mathematical Models in Stochastic Approach." In Mathematical Models for Therapeutic Approaches to Control HIV Disease Transmission, 183–213. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-852-6_8.

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Nanni, P. G., G. Castellani, P. Pettazzoni, G. Pallotti, and C. Pallotti. "Limits of mathematical models in biology and medicine." In Atherosclerosis and Cardiovascular Disease, 232–36. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0731-7_31.

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Mohapatra, R. N., Donald Porchia, and Zhisheng Shuai. "Compartmental Disease Models with Heterogeneous Populations: A Survey." In Mathematical Analysis and its Applications, 619–31. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2485-3_51.

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Qi, Zhen, Gary W. Miller, and Eberhard O. Voit. "Mathematical Models of Dopamine Metabolism in Parkinson’s Disease." In Systems Biology of Parkinson's Disease, 151–71. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3411-5_8.

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Boutayeb, Abdesslam, Mohamed E. N. Lamlili, and Wiam Boutayeb. "A Review of Compartmental Mathematical Models Used in Diabetology." In Disease Prevention and Health Promotion in Developing Countries, 217–50. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34702-4_14.

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Dioguardi, N., P. Mussio, M. Zuin, and A. Lovati. "Mathematical Models for the Study of Hepatic Metabolism: A New Strategy." In Assessment and Management of Hepatobiliary Disease, 9–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-72631-6_2.

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Streszczenia konferencji na temat "Legionnaires' Disease Mathematical models"

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COLLINO, SIMONA, EZIO VENTURINO, LUCA FERRERI, LUIGI BERTOLOTTI, SERGIO ROSATI, and MARIO GIACOBINI. "MODELS FOR TWO STRAINS OF THE CAPRINE ARTHRITIS ENCEPHALITIS VIRUS DISEASE." In 15th International Symposium on Mathematical and Computational Biology. WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813141919_0019.

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Chang, Albert Ling Sheng, Chong Khim Phin, and Ho Chong Mun. "Comparing nonlinear models in describing disease progress curve of cocoa black pod." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041682.

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Nielsen, B. F., M. Lysaker, C. Tarrou, M. C. MacLachlan, A. Abildgaard, and A. Tveito. "On the use of st-segment shifts and mathematical models for identifying ischemic heart disease." In Computers in Cardiology, 2005. IEEE, 2005. http://dx.doi.org/10.1109/cic.2005.1588280.

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Elliott, Novak S. J. "Cerebrospinal Fluid-Structure Interactions: The Development of Mathematical Models Accessible to Clinicians." In ASME 2014 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/pvp2014-29096.

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Physical scientists work with clinicians on biomechanical problems, yet the predictive capabilities of mathematical models often remain elusive to clinical collaborators. This is due to both conceptual differences in the research methodologies of each discipline, and the perceived complexity of even simple models. This limits expert medical input, affecting the applicability of the results. Moreover, a lack of understanding undermines the medical practitioner’s confidence in modeling predictions, hampering its clinical application. In this paper we consider the disease syringomyelia, which inv
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Takada, M., M. Sugimoto, N. Masuda, H. Iwata, K. Kuroi, H. Yamashiro, S. Ohno, H. Ishiguro, T. Inamoto, and M. Toi. "Abstract P4-21-24: Development of mathematical prediction models to identify disease-free survival events for HER2-positive primary breast cancer patients treated by neoadjuvant chemotherapy and trastuzumab." In Abstracts: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.sabcs16-p4-21-24.

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Lundberg, Hannah J., Kharma C. Foucher, Thomas P. Andriacchi, and Markus A. Wimmer. "Comparison of Numerically Modeled Knee Joint Contact Forces to Instrumented Total Knee Prosthesis Forces." In ASME 2009 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2009. http://dx.doi.org/10.1115/sbc2009-206791.

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Total knee replacement (TKR) surgery decreases pain and increases functional mobility for patients with joint disease. As primary TKRs are implanted in patients who are younger, heavier, and more active (1), increases in wear and TKR revision rates are expected. Preclinical analysis of TKRs with mathematical models and experimental tests require accurate in vivo kinetic and kinematic input data. Kinematics can be obtained with gait analysis, but in vivo force data are just beginning to become available from instrumented TKRs from only a few patients (2). Patient gait is highly variable both wi
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Rugonyi, Sandra, and Kent Thornburg. "Modeling the Effect of Hemodynamics on Cardiac Growth During Embryonic Development." In ASME 2010 First Global Congress on NanoEngineering for Medicine and Biology. ASMEDC, 2010. http://dx.doi.org/10.1115/nemb2010-13171.

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Congenital heart disease (CHD) affects about 1% of newborn babies in the US, and is the leading cause of non-infectious death in children. Abnormal blood flow dynamics during early development can lead to CHD. Although the effect of hemodynamic conditions on cardiac development — even under normal conditions — has been widely accepted, the mechanisms by which blood flow influences cardiac cell responses are only starting to emerge. Mathematical models of cardiac growth could then help elucidate key aspects of cardiac development.
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Bazilo, Constantine, Alvydas Zagorskis, Oleg Petrishchev, Yulia Bondarenko, Vasyl Zaika, and Yulia Petrushko. "Modelling of Piezoelectric Transducers for Environmental Monitoring." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.008.

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World Health Organization (WHO) defined health as being “a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity”. Physical factors (noise, vibration, electromagnetic fields, ionized radiation, etc.) may have a negative influence on both the environment and the health of population. Piezoelectric sensors have been employed in different fields such as medical analysis, environmental monitoring, etc. The object of the research is piezoelectric sensors for environmental monitoring and their simulation. Currently, there are no reliable and val
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Chagdes, James R., Joshua J. Liddy, Jessica E. Huber, Howard N. Zelaznik, Shirley Rietdyk, Arvind Raman, and Jeffrey M. Haddad. "Dynamic Instabilities Induced Through Altered Visual Cues and Their Relationship to Postural Response Latencies." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60248.

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Mathematical models predict limit cycle oscillations (LCOs) in postural sway when the combination of neuromuscular time-delay and feedback gains are excessively large. LCOs have been observed in the standing posture of various populations known to have longer time-delays including concussed young adults and adults with neuromuscular impairment such as multiple sclerosis (MS) and Parkinsons disease (PD) but not healthy controls. However, the relationship between feedback gain and time-delay that leads to these LCOs has yet to be explored experimentally. In this study, we examine the relationshi
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Hossain, Md Shahadat, Bhavin Dalal, Ian S. Fischer, Pushpendra Singh, and Nadine Aubry. "Modeling of Blood Flow in the Human Brain." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30554.

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The non-Newtonian properties of blood, i.e., shear thinning and viscoelasticity, can have a significant influence on the distribution of Cerebral Blood Flow (CBF) in the human brain. The aim of this work is to quantify the role played by the non-Newtonian nature of blood. Under normal conditions, CBF is autoregulated to maintain baseline levels of flow and oxygen to the brain. However, in patients suffering from heart failure (HF), Stroke, or Arteriovenous malformation (AVM), the pressure in afferent vessels varies from the normal range within which the regulatory mechanisms can ensure a const
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