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Topic: Mathematical modelling in epidemiology

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	Mathematical modelling in epidemiology - Wikipedia, the free encyclopedia (Site not responding. Last check: 2007-10-20)
		It is possible to model mathematically the progress of most infectious diseases to discover the likely outcome of an epidemic or to help manage them by vaccination.
		Whenever we are modelling anything mathematically, whether in epidemiology or otherwise, we would be wise to remember that a mathematical model is only as good as the assumptions on which it is based.
		Notice that this relation means that for a disease to be in the endemic steady state, the higher the basic reproduction number, the lower the proportion of the population susceptible must be, and vice versa; a mathematical basis for a result that might have been intuitively obvious.
	en.wikipedia.org /wiki/Mathematical_modelling_in_epidemiology (1374 words)

	Sergey Rudnev's Home Page
		Rudnev S.G. Mathematical modelling of defensive immunophysiological reaction in pneumonia.
		Romanyukha A.A., Rudnev S.G., Karkatch A.S., Sannikova T.E. Mathematical modelling of infection immunity.
		Mathematical modelling of epidemiology and pathogenesis of tuberculosis.
	immunol.inm.ras.ru /personal/rdnv.htm (956 words)

	Susceptible - Wikipedia, the free encyclopedia
		In epidemiology a susceptible individual (sometimes known simply as a susceptible) is a member of a population who is at risk of becoming infected by a disease, if they are exposed to the infectious agent.
		Susceptibles have been exposed to neither the wild strain of the disease nor a vaccination against it, and thus have not developed immunity.
		The parameter S is important in the mathematical modelling of epidemics.
	en.wikipedia.org /wiki/Susceptible (362 words)

	Workshop on Mathematical Epidemiology: Abstracts
		We use a deterministic compartmental mathematical model to study the influence of various heterogeneities in a population on the transmission of measles.
		The persistence threshold for the SIS model is obtained by analysing an appropriate deterministic model.
		I will use the models as predictive tools: (i) to predict (with a degree of uncertainty) future levels of antibiotic and antiviral resistance, and (ii) to identify which factors are the most important both in generating the initial emergence of drug resistant strains, and in driving the transmission dynamics of drug resistant strains.
	www.pims.math.ca /science/1999/bio99/epid.abstracts.html (4389 words)

	Epidemiology - Psychology Central
		Epidemiology is the scientific study of factors affecting the health and illness of individuals and populations, and serves as the foundation and logic of interventions made in the interest of public health and preventive medicine.
		Although epidemiology is sometimes viewed as a collection of statistical tools used to elucidate the associations of exposures to health outcomes, a deeper understanding of this science is that of discovering causal relationships.
		Strictly speaking, epidemiology can only go to prove that an agent could have caused but not that, in any particular case, it did cause: "Epidemiology is concerned with the incidence of disease in populations and does not address the question of the cause of an individual’s disease.
	psychcentral.com /psypsych/Epidemiology (1715 words)

	Applied Mathematical Modelling - School of Physical, Environmental and Mathematical Sciences (PEMS) - UNSW@ADFA (Site not responding. Last check: 2007-10-20)
		Mathematical modelling is used in the research project to study the spread of infectious diseases and the effects of control interventions such as vaccination and quarantine.
		The model can be extended to other infectious diseases, although the choice of transmission routes and the details of infectiousness as a function of infection age would in general be quite different.
		Our aim is to be able to model the performance of long-distance runners and, by being able to predict heart rate and glycogen levels as a function of work and time, to develop feeding and work-rate strategies to improve long-term performance.
	www.adfa.oz.au /pems/research/appl_math_mod.html (974 words)

	Epidemiology of Infectious Diseases (Site not responding. Last check: 2007-10-20)
		Mathematical modelling now plays a key role in policy making, including health-economic aspects; emergency planning and risk assessment; control-programme evaluation; and monitoring of surveillance data.
		Imperial College London's Department of Infectious Disease Epidemiology has been the world leader in mathematical modelling of the epidemiology and control of infectious diseases of humans and animals in both industrialised and developing countries for 20 years.
		Keynote lectures on a wide range of topics and case studies place the current use of mathematical modelling in context, illustrating how in a number of ways it contributes to epidemiological studies, policy-making and evaluation.
	www.imperial.ac.uk /cpd/epidemiology.htm (1299 words)

	BioSS Postgraduate-Current and Recent Projects (Site not responding. Last check: 2007-10-20)
		Alternative models will be compared in terms of the deterministic and stochastic models' prediction of the course of E. coli O157 infection within a herd and tested using longitudinal data as it becomes available from farm surveys.
		The output based on the deterministic models will be compared with output from stochastic models and also output from stochastic models which incorporate uncertainty [in a bayesian sense] into their estimates of parameter values.
		A stochastic model for the propagation and control of a infectious disease in a lattice-structured population is considered.
	www.bioss.sari.ac.uk /student/currentphd.html (3310 words)

	UT Feature Story -- Predicting the Path of Infectious Diseases: Mathematical modeling traces the spread of SARS and ...
		She uses mathematical modeling to track and predict the spread of infectious diseases in a community.
		Using mathematical models to analyze the spread of the disease isn’t new, but Meyers and other researchers are approaching modeling in a new way, using network theory.
		In the past, most mathematical modeling of epidemics was undertaken by separating a population into three or more distinct groups: those who are susceptible to a disease, those who are already infected and those who have recovered.
	www.utexas.edu /features/archive/2003/meyers.html (1959 words)

	Wiley::Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation (Site not responding. Last check: 2007-10-20)
		The mathematical modelling of epidemics in populations is a vast and important area of study.
		Model assumptions are formulated in terms of, usually stochastic, behaviour of individuals and then the resulting phenomena, at the population level, are unravelled.
		The text is aimed at applied mathematicians with an interest in population biology and epidemiology, at theoretical biologists and epidemiologists.
	www.wiley.com /WileyCDA/WileyTitle/productCd-0471492418,subjectCd-ST22.html (294 words)

	Epidemiology, HIV and drugs: mathematical models and data.
		The utility of mathematical models in understanding the dynamics of HIV transmission among injecting drug users (IDUs) and their non-IDU sex partners is discussed.
		We emphasize the need for collaborative relationships between modellers and drug-use researchers, and we stress that models should be based on data in both their formulation and development stages.
		We outline some of the possible data requirements of transmission models and we highlight the need for the collection of appropriate quantitative data, so that modellers can estimate specific parameters for their models.
	www.aegis.com /aidsline/1992/jul/M9270599.html (371 words)

	RIVM - Mathematical Modelling
		Increasigly, mathematical methods and models are being used for quantitative analysis of infections data and the possible effects of intervention.
		The project group Mathematical Modelling develops and analyzes models based on data from various sources and directly supports policy makers in their decisions about future policies.
		Examples are the analysis of effects of vaccionation on the incidence of infectious diseases, or estimates of how many persons and in which population groups should be vaccinated to control an outbreak.
	rivm.nl /en/aboutrivm/organization/cib/cie/mathematical_modelling.jsp (104 words)

	Newsletter Item
		Mathematics is at the heart of representing and reasoning about scientific and engineering data and knowledge, and the role of mathematics in e-Science is potentially profound.
		Hence new ways of doing mathematics enabled by the Grid, and the identification of how the Grid can best handle mathematical computation and data, whether numeric or symbolic, have the potential to impact mathematics itself, and mathematical modelling, such as epidemiology or weather forecasting.
		Mathematics, in particular the discrete mathematics and logic which underpin computer science, provides the tool for understanding and modelling the Grid itself, for example new techniques for resource allocation and modelling, handling and mining data or modelling network infrastructure.
	www.lms.ac.uk /newsletter/0306/articles.html (1752 words)

	Commentary: Modelling the epidemiology of hepatitis C and its complications -- Armstrong 32 (5): 725 -- International ...
		Commentary: Modelling the epidemiology of hepatitis C and its complications
		Modelling hepatitis C virus incidence, prevalence and long-term sequelae in Australia, 2001.
		Griffiths J, Nix B. Modeling the hepatitis C virus epidemic in France using the temporal pattern of hepatocellular carcinoma deaths.
	ije.oxfordjournals.org /cgi/content/full/32/5/725 (1442 words)

	New Zealand Mathematical Societu Newsletter Number 84, April 2002
		I was at the colloquium at Massey in December, the summer workshop of the New Zealand Mathematics Research Institute in Napier in January, and ANZIAM 2002 in Canberra in February.
		At ANZIAM I presented an invited paper "Mathematical models for intestinal parasites", and at ANZIAM and the colloquium I was on the judging panel for the student prize.
		His interests are in the mathematical modeling of cardiac tissue (particularly metabolism) and applying the finite element method to multiscale models of muscle contraction.
	ifs.massey.ac.nz /mathnews/Nzms84/news84.htm (7833 words)

	HPA \| Seroepidemiology \| Contribution to public health policy
		Cross-sectional antibody prevalence studies carried out through the HPA Seroepidemiology Programme have been particularly useful when formulating, evaluating, and monitoring health policy in a multidisciplinary environment involving epidemiology, microbiology, mathematical modelling and health economics.
		The collection was first used to provide the baseline MMR antibody prevalence data that was needed to assist with the decision to introduce the MMR vaccine in 1988.
		The decision to introduce the two-dose schedule of MMR in 1996 was based on data provided by the programme and similarly it provided valuable evidence to support the need for an acellular pertussis booster vaccine in 2001.
	www.hpa.org.uk /infections/seroepidemiology/policy.htm (132 words)

	Environmental Mathematics and Statistics - Stochastic Population Models in Epidemiology and Ecology Workshop (Site not responding. Last check: 2007-10-20)
		Workshop on Inference for Stochastic Population Models in Epidemiology and Ecology
		This workshop will bring together researchers from the fields of infectious epidemiology, ecology, stochastic modelling, mathematical biology and statistics with an interest in inference for stochastic models of population processes.
		Powerful computational methods such as MCMC and the EM algorithm now allow stochastic models to be fitted to observations of population processes within a sound statistical framework.
	www.ma.hw.ac.uk /icms/ems/epideco (223 words)

	Mathematical modelling of health impacts -- Mindell and Joffe 59 (8): 617 -- Journal of Epidemiology and Community ...
		Mathematical modelling of health impacts -- Mindell and Joffe 59 (8): 617 -- Journal of Epidemiology and Community Health
		Department of Epidemiology and Public Health, University College London, 1–19 Torrington Place, London WC1E 6BT, UK Mathematical modelling is seldom applied to research of global
		the use of modelling to estimate health impacts of a policy.
	jech.bmjjournals.com /cgi/content/extract/59/8/617 (246 words)

	GIS Europe - Feb 2000 - Geofocus: GIS and health (Site not responding. Last check: 2007-10-20)
		This was followed by the development of mathematical models (2)(3)(4) and the refinement of spatial modelling and analytical routines (5-11) to gain a greater understanding of the spatial dynamics of diseases.
		Two multi-disciplinary work teams are involved in the development, with specialist skills in epidemiology, mathematical modelling, cartography and computing all represented.
		Other routines assess the lost potential years of life; model the spatial aggregation of diseases with low incidence levels, and provide demographic comparisons that enable further research (figs 3 and 4).
	www.geoplace.com /ge/2000/0200/0200he.asp (912 words)

	STAMS, University of Strathclyde, UK: Research Interests
		Statistics, mathematical modelling and epidemiology of animal and human diseases
		Statistical models in epidemiology; regional variation in disease risk; meta analysis; stochastic models in infectious disease and vaccinations
		Modelling of bio-artificial liver devices with Bioengineering Unit.
	www.stams.strath.ac.uk /staff/interests.php (155 words)

	Job Listings (Site not responding. Last check: 2007-10-20)
		Requirements include a (1) doctorate in epidemiology or statistics with training/experience in human genetics; (2) doctorate in genetics or related field in which genetic epidemiology or statistical genetics was a focus of training; or (3) MD plus training in both epidemiology and genetics.
		Applicants should have a doctorate in epidemiology, genetics, statistical genetics, medicine, or related fields or the equivalent experience and documented expertise; relevant experience after the doctorate; experience in the design, conduct, analysis, interpretation and publication of results from genetic/molecular epidemiologic investigations of cancer; and experience in working collegially on interdisciplinary teams.
		The project is to develop computational and statistical models of the population histories of several dog breeds, informed by Kennel Club records, and to use these to develop cost-effective study designs for investigating the genetic architecture of various diseases in different dog breeds.
	iges.biostat.wustl.edu /jobads.html (12366 words)

	BAPS Homepage
		We have long been involved in the mathematical modelling of the spread of epidemics.
		Equilibria are of particular interest, since they should correspond to the stochastic quasi-equilibria which describe what is observed in nature; for many of the models, finding the possible equilibria and establishing conditions for convergence to them are problems which are still entirely open.
		We are also interested in the time course of epidemics in structured populations, as in `small world' models, such as the great circle model.
	www.math.unizh.ch /~baps/research (738 words)

	An introduction to mathematical models in sexually transmitted disease epidemiology -- Garnett 78 (1): 7 -- Sexually ...
		An introduction to mathematical models in sexually transmitted disease epidemiology -- Garnett 78 (1): 7 -- Sexually Transmitted Infections
		An introduction to mathematical models in sexually transmitted disease epidemiology
		Mathematical models serve a number of roles in understanding
	sti.bmjjournals.com /cgi/content/abstract/78/1/7 (161 words)

	EMGM 2002 (Site not responding. Last check: 2007-10-20)
		The meeting consisted of two days of talks and posters covering all areas of mathematical genetics with a mix of submitted abstracts and some invited speakers.
		Areas covered included genetic epidemiology, population genetics, association and linkage studies, QTL mapping, complex diseases and phylogenetics.
		Details of the Mathematical Modelling and Genetical Epidemiology group can be found here.
	www.shef.ac.uk /mmge/emgm2002 (304 words)

	[No title]
		I organise, with Dr Christophe Fraser,Â Imperial College's professional Short Course on Epidemiology of Infectious Diseases that is aimed at public health professionals, policy-makers and researchers who want to learn about modern methods including mathematical modelling.
		My current research interests are in mathematical modelling of the epidemiology of sexually transmitted infections â“ including HIV â“ and the impact of health-care interventions.
		Epidemiology of rabbit haemorrhagic disease virus in the UK: evidence for seasonal transmission by both virulent and avirulent modes of infection.
	www1.imperial.ac.uk /medicine/people/p.white.html (925 words)

	Mathematical modelling of AIDS epidemic in IndiaePrints@IISc - Open Access Archive of IISc Research Publications (Site not responding. Last check: 2007-10-20)
		Rao, Arni SR Srinivasa (2003) Mathematical modelling of AIDS epidemic in India.
		Mathematical and statistical models can serve as tools for understanding the epidemiology of human immunodeficiency virus and acquired immunodeficiency syndrome if they are constructed carefully.
		This article is meant to be an introduction to AIDS-related mathematical biology for scientists with a non-mathematical background.
	eprints.iisc.ernet.in /archive/00002633 (107 words)

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