2 edition of Mathematical models for antigenically diverse viral pathogens found in the catalog.
Mathematical models for antigenically diverse viral pathogens
Lisa Jane White
Thesis (M.Sc.) - University of Warwick, 1996.
|Statement||Lisa Jane White.|
|The Physical Object|
|Number of Pages||178|
Selection by host immune responses to pathogens could explain important aspects of strain structure and dynamics. • Models are valuable tools in understanding these processes, but equally plausible assumptions can give divergent results. • There is a need to adapt models to specific pathogens. • Data are required to arbitrate between. A mathematical model helps in establishment of links between sets of epidemiological data through well-understood mathematical relationships. This is facilitated only through a thorough understanding of various factors associated with the disease like, incubation, transmission and mortality and also factors associated with the vector.
Collaborator [email protected] Villyen is a medical epidemiologist who works on infectious diseases, child health, and reproductive health. Following training as a medical doctor at the University of Yaoundé 1 in Cameroon, he worked for four years in the North West Region of Cameroon as a general practitioner before deciding to pursue a career in medical research. A variety of models have been applied to wildlife diseases, including mathematical and statistical models. We restrict this review to viral zoonoses and to mathematical models, that are either deterministic or stochastic. In Sections 3 and 4, models that have been developed at the population level and cellular level, respectively, are.
Characterization of the endemic equilibrium and response to mutant injection in a multi-strain disease model Tomás Aquinoa,b, Diogo Bolstera, Ana Nunesb,n a Department of Civil & Environmental Engineering and Earth Sciences, University of Notre Dame, IN, USA b Centro de Física da Matéria Condensada and Departamento de Física, Faculdade de Ciências da Universidade de . A new model of the within-host evolutionary arms race between viral pathogens and the adaptive immune responses intended to fight them suggests that vaccines based on genetically diverse sets of viral antigens may be more likely to stimulate the production of antibodies capable of neutralizing broad panels of virions, according to the results of a study published recently in PLoS Genetics 1.
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Pathogens have evolved diverse strategies to maximize their transmission fitness. Here we investigate these strategies for directly transmitted pathogens using mathematical models of disease pathogenesis and transmission, modeling fitness as a function of within- and between-host pathogen by: Viral pathogens RNA viruses are incapable of correcting the frequent mistakes that occur during viral replication.
The net result is the generation of an enormous amount of genetic diversity within a population of replicating RNA viruses.
We examine the dynamics of antigenically diverse infectious agents using a mathematical model describing the transmission dynamics of arbitrary numbers of pathogen strains, interacting via cross-immunity, and in the presence of mutations generating new strains and stochastic extinctions of existing by: Mathematical models can project how infectious diseases progress to show the likely outcome of an epidemic and help inform public health interventions.
Models use basic assumptions or collected statistics along with mathematics to find parameters for various infectious diseases and use those parameters to calculate the effects of different interventions, like mass vaccination programmes. Ferguson N., Andreasen V.
() The Influence of Different Forms of Cross-Protective Immunity on the Population Dynamics of Antigenically Diverse Pathogens.
In: Castillo-Chavez C., Blower S., van den Driessche P., Kirschner D., Yakubu AA. (eds) Mathematical Approaches for Emerging and Reemerging Infectious Diseases: Models, Methods, and by: On the determinants of population structure in antigenically diverse pathogens Article (PDF Available) in Proceedings of the Royal Society B: Biological Sciences () March In mathematical studies of the dynamics of multi-strain diseases caused by antigenically diverse pathogens, there is a substantial interest in analytical insights.
space models. If the viral. Bartlett ,who examined models and data to expose the fac-tors that determine disease persistence in large populations. Arguably, the ﬁrst landmark book on mathematical modeling of epidemiological systems was published by Bailey  which led in part to the recognition of the importance of modeling in public health decision making .
The ubiquity of this assembly code in RNA viruses, including major human pathogens, suggests that it confers selective advantages.
However, their impact on viral evolution cannot be assessed in current models of viral infection that lack molecular details of virus assembly. Enteric viral co-infections, infections involving more than one virus, have been reported for a diverse group of etiological agents, including rotavirus, norovirus, astrovirus, adenovirus, and enteroviruses.
These pathogens are causative agents for acute gastroenteritis and diarrheal disease in immunocompetent and immunocompromised individuals of all ages globally.
We examine the dynamics of antigenically diverse infectious agents using a mathematical model describing the transmission dynamics of arbitrary numbers of pathogen strains, interacting via cross–immunity, and in the presence of mutations generating. A mathematical framework is presented that models intra- and inter-host dynamics in a minimalistic but unified fashion covering a broad spectrum of viral pathogens, including those that cause flu.
The field of viral fitness was originally developed through studies of a relatively small number of bacteriophage, animal, and plant viruses. With increasing recognition of the importance of viral fitness, there is now a wide array of study systems as detailed in Table majority of viral fitness study systems are based on RNA viruses, and the highest numbers of publications in recent.
Role of mathematical models in immunology There are many viewpoints in regard to the purpose of developing mathematical models to describe immunological phenomena: from explaining existing observations and generating new hypotheses that can be tested empirically (Ankomah and Levin ), to understanding which assumptions in the model are useful and generate outcomes.
Ferguson N, Andreasen V () The influence of different forms of cross-protective immunity on the population dynamics of antigenically diverse pathogens.
Mathematical approaches for emerging and reemerging infectious diseases: models, methods, and theory p ; Ferguson N, Anderson R, Gupta S.
The preceding chapters describe essential aspects of viral pathogenesis, including virus–cell interactions; viral spread within a host; and intrinsic, innate, and adaptive immune responses. This chapter extends the theme and addresses diverse patterns of viral infections that are determined by both the virus and the host.
The influence of different forms of cross-protective immunity on the population dynamics of antigenically diverse pathogens Mathematical Approaches for Emerging and Reemerging Infectious Diseases: Models, Methods, and Theory, Springer (), pp.
PDF | The effects of selection by host immune responses on transmission dynamics was analyzed in a broad class of antigenically diverse pathogens. | Find, read and cite all the research you. RABV-G/A in liquid form was shown to be antigenically stable at 5 °C and 25 °C for one month, and a dedicated kinetic model predicted its stability up to 1 year at 5 °C.
To mitigate the RABV-G/A sensitivity to mechanical stress, a solid form of RABV-G/A and a freeze-drying process were considered, resulting in a 2-year thermally.
Mathematical models with multiple pathogens are just beginning to explore the role of the within-host immune response on the population dynamics [66, 67, 82, ]. Viral Quasispecies The viral genetic variation has been included in the basic TIV model into what is referred to as viral quasispecies models [ 36,].
Mathematical models of epidemics have a long history of contributing to the understanding of the impact of vaccination programmes. Simple, one-line models can predict target vaccination coverage.
2. Mathematical model. Our model is based on a conventional extension of the standard SIR framework to multiple co-circulating strains with immune cross-reaction [7,10–12,21–32].The global population is divided into three distinct regions (), each of population size regions are characterized by transmission and non-transmission seasons that each last six months and do not.
Despite being recognized and fought against over countless centuries, human viral pathogens continue to cause major public health problems worldwide-killing millions of people and costing billions of dollars in medical care and lost productivity each year. With contributions from specialists in their respective areas of viral pathogen research, Mol.