Relevant bibliographies by topics / Epidemiological modelling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Epidemiological modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Epidemiological modelling"

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GARNER, M. G., and S. A. HAMILTON. "Principles of epidemiological modelling." Revue Scientifique et Technique de l'OIE 30, no. 2 (August 1, 2011): 407–16. http://dx.doi.org/10.20506/rst.30.2.2045.

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Crépey, Pascal, Harold Noël, and Samuel Alizon. "Challenges for mathematical epidemiological modelling." Anaesthesia Critical Care & Pain Medicine 41, no. 2 (April 2022): 101053. http://dx.doi.org/10.1016/j.accpm.2022.101053.

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Habbema, J. D. F., E. S. Alley, A. P. Plaisier, G. J. van Oortmarssen, and J. H. F. Remme. "Epidemiological modelling for onchocerciasis control." Parasitology Today 8, no. 3 (March 1992): 99–103. http://dx.doi.org/10.1016/0169-4758(92)90248-z.

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Lambrou, George I., Kyriaki Hatziagapiou, Petros Toumpaniaris, Penelope Ioannidou, and Dimitrios Koutsouris. "Computational Modelling in Epidemiological Dispersion Using Diffusion and Epidemiological Equations." International Journal of Reliable and Quality E-Healthcare 8, no. 4 (October 2019): 1–37. http://dx.doi.org/10.4018/ijrqeh.2019100101.

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Although a considerable amount of knowledge is gathered concerning diseases and their transmission, still more is to learn on their mathematical modelling. The present work reviews the existent knowledge on models of epidemiological dispersion, the creation of a new form of an epidemiological diffusion equation, and the subsequent application of this equation to the investigation of epidemiological phenomena. Towards that scope, the authors have used mathematical models which have been previously reported, as well as algorithmic approaches of stochastic nature for the solution of complex functions. In particular, they have used dynamic programming algorithms, Robbins-Monro and Kiefer-Wolfowitz stochastic optimization algorithms, Markov chains and cellular automata. The modified diffusion equation could potentially provide a useful tool to the investigation of epidemiological phenomena. More research is required in order to explore the extent of its possibilities and uses.
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Furtat, І. E. "Modelling the Optimal Schemes of Population Vaccination Using Epidemiological Data." Mathematical and computer modelling. Series: Technical sciences 1, no. 20 (September 20, 2019): 104–13. http://dx.doi.org/10.32626/2308-5916.2019-20.104-113.

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Soloviov, S., and O. Bandurka. "Modelling the Optimal Schemes of Population Vaccination Using Epidemiological Data." Mathematical and computer modelling. Series: Technical sciences 1, no. 20 (September 20, 2019): 99–103. http://dx.doi.org/10.32626/2308-5916.2019-20.99-103.

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D, Raja. "The Power of Epidemiological Modelling inUnderstanding and Managing Infectious Diseases." Chettinad Health City Medical Journal 12, no. 1 (March 31, 2023): 1–2. http://dx.doi.org/10.24321/2278.2044.202301.

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Jere, Stanley, and Edwin Moyo. "Modelling Epidemiological Data Using Box-Jenkins Procedure." Open Journal of Statistics 06, no. 02 (2016): 295–302. http://dx.doi.org/10.4236/ojs.2016.62025.

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Friston, Karl, Anthony Costello, and Deenan Pillay. "‘Dark matter’, second waves and epidemiological modelling." BMJ Global Health 5, no. 12 (December 2020): e003978. http://dx.doi.org/10.1136/bmjgh-2020-003978.

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Recent reports using conventional Susceptible, Exposed, Infected and Removed models suggest that the next wave of the COVID-19 pandemic in the UK could overwhelm health services, with fatalities exceeding the first wave. We used Bayesian model comparison to revisit these conclusions, allowing for heterogeneity of exposure, susceptibility and transmission. We used dynamic causal modelling to estimate the evidence for alternative models of daily cases and deaths from the USA, the UK, Brazil, Italy, France, Spain, Mexico, Belgium, Germany and Canada over the period 25 January 2020 to 15 June 2020. These data were used to estimate the proportions of people (i) not exposed to the virus, (ii) not susceptible to infection when exposed and (iii) not infectious when susceptible to infection. Bayesian model comparison furnished overwhelming evidence for heterogeneity of exposure, susceptibility and transmission. Furthermore, both lockdown and the build-up of population immunity contributed to viral transmission in all but one country. Small variations in heterogeneity were sufficient to explain large differences in mortality rates. The best model of UK data predicts a second surge of fatalities will be much less than the first peak. The size of the second wave depends sensitively on the loss of immunity and the efficacy of Find-Test-Trace-Isolate-Support programmes. In summary, accounting for heterogeneity of exposure, susceptibility and transmission suggests that the next wave of the SARS-CoV-2 pandemic will be much smaller than conventional models predict, with less economic and health disruption. This heterogeneity means that seroprevalence underestimates effective herd immunity and, crucially, the potential of public health programmes.
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Brotto Rebuli, Karina, Mario Giacobini, and Luigi Bertolotti. "Caprine Arthritis Encephalitis Virus Disease Modelling Review." Animals 11, no. 5 (May 19, 2021): 1457. http://dx.doi.org/10.3390/ani11051457.

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Mathematical modelling is used in disease studies to assess the economical impacts of diseases, as well as to better understand the epidemiological dynamics of the biological and environmental factors that are associated with disease spreading. For an incurable disease such as Caprine Arthritis Encephalitis (CAE), this knowledge is extremely valuable. However, the application of modelling techniques to CAE disease studies has not been significantly explored in the literature. The purpose of the present work was to review the published studies, highlighting their scope, strengths and limitations, as well to provide ideas for future modelling approaches for studying CAE disease. The reviewed studies were divided into the following two major themes: Mathematical epidemiological modelling and statistical modelling. Regarding the epidemiological modelling studies, two groups of models have been addressed in the literature: With and without the sexual transmission component. Regarding the statistical modelling studies, the reviewed articles varied on modelling assumptions and goals. These studies modelled the dairy production, the CAE risk factors and the hypothesis of CAE being a risk factor for other diseases. Finally, the present work concludes with further suggestions for modelling studies on CAE.
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Dissertations / Theses on the topic "Epidemiological modelling"

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Rayman, John F. "Epidemiological modelling of bovine tuberculosis in badgers and cattle." Thesis, University of Surrey, 2008. http://epubs.surrey.ac.uk/821/.

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This thesis covers the formulation and analysis of a number of deterministic, continuous models of infection by a disease such as bovine tuberculosis in one species (essentially badgers) and in two mutually infective species (badgers and cattle). We examine the dynamics of the disease in each model and then consider the effects of the application of different badger culling strategies which have the objective of eliminating the disease in cattle.
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Zhang, Hui S. M. Massachusetts Institute of Technology. "Modelling pandemic influenza progression using Spatiotemporal Epidemiological Modeller (STEM)." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/55088.

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Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 69-70).
The purpose of this project is to incorporate a Poisson disease model into the Spatiotemporal Epidemiological Modeler (STEM) and visualize the disease spread on Google Earth. It is done through developing a Poisson disease model plug-in using the Eclipse Modeling Framework (EMF), a modeling framework and code generation facility for building tools and other applications based on a structured data model. The project consists of two stages. First, it develops a disease model plug-in of a Poisson disease model of a homogenous population, which is built as an extension of the implemented SI disease model in the STEM. Next, it proposes an algorithm to port a Poisson disease model of a heterogeneous population into the STEM. The development of the two new diseases plugins explores the maximum compatibility of the STEM and sets model for potential users to flexibly construct their own disease model for simulation.
by Hui Zhang.
S.M.
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Mancy, Rebecca. "Modelling persistence in spatially-explicit ecological and epidemiological systems." Thesis, University of Glasgow, 2015. http://theses.gla.ac.uk/6219/.

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In this thesis, we consider the problem of long-term persistence in ecological and epidemiological systems. This is important in conservation biology for protecting species at risk of extinction and in epidemiology for reducing disease prevalence and working towards elimination. Understanding how to predict and control persistence is critical for these aims. In Chapter 2, we discuss existing ways of characterising persistence and their relationship with the modelling paradigms employed in ecology and epidemiology. We note that data are often limited to information on the state of particular patches or populations and are modelled using a metapopulation approach. In Chapter 3, we define persistence in relation to a pre-specified time horizon in stochastic single-species and two-species competition models, comparing results between discrete and continuous time simulations. We find that discrete and continuous time simulations can result in different persistence predictions, especially in the case of inter-specific competition. The study also serves to illustrate the shortcomings of defining persistence in relation to a specific time horizon. A more mathematically rigorous interpretation of persistence in stochastic models can be found by considering the quasi-stationary distribution (QSD) and the associated measure of mean time to extinction from quasi-stationarity. In Chapter 4, we investigate the contribution of individual patches to extinction times and metapopulation size, and provide predictors of patch value that can be calculated easily from readily available data. In Chapter 5, we focus directly on the QSD of heterogeneous systems. Through simulation, we investigate possible compressions of the QSD that could be used when standard numerical approaches fail due to high system dimensionality, and provide guidance on appropriate compression choices for different purposes. In Chapter 6, we consider deterministic models and investigate the effect of introducing additional patch states on the persistence threshold. We suggest a possible model that might be appropriate for making predictions that extend to stochastic systems. By considering a family of models as limiting cases of a more general model, we demonstrate a novel approach for deriving quantities of interest for linked models that should help guide modelling decisions. Finally, in Chapter 7, we draw out implications for conservation biology and disease control, as well as for future work on biological persistence.
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Delfino, Doriana. "Economic-epidemiological analysis of tuberculosis : modelling the demographic-epidemiological implications of economic growth and public health investment." Thesis, University of York, 2001. http://etheses.whiterose.ac.uk/10936/.

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Semple, Sean. "Exposure modelling : estimating dermal and inhalation exposures for epidemiological research." Thesis, University of Aberdeen, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.395143.

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This study reviews available methods of exposure assessment, examines the effects of exposure misclassification on the ability to identify an association, and focuses on recent progress in subjective exposure modelling. Subjective exposure modelling utilises a framework of parameters identified as likely to control personal exposure levels together with detailed guidance and expert judgement in order to estimate exposure concentrations. As part of a case-control study, the Neurotoxicity of Paint Solvents (NPS) study, the process of evaluating subjects' lifetime exposure to solvents was reviewed. A training program and detailed guidance material was produced and the ability of assessors to reconstruct inhalation exposures from textual data was tested. In the training study, assessors were shown to estimate exposures that were well correlated with measured levels (correlation coefficients for log estimate compared to log measured values ranging from 0.73 to 0.85). The assessors tended to overestimate levels with the estimates ranging from 1.6 to 3.5 times the measured results. A series of painting simulation exercises was carried out to validate the use of certain guidance values for the model parameters. Using different paint application methods and different paint types, the influence of these variables on exposure levels was assessed. The results agreed closely with the guidance produced for the inhalation exposure model. Analysis of the solvent exposure histories of the NPS study group suggested that dermal exposure and uptake of solvents was important. To this end a novel dermal exposure model was developed for spray painting tasks. Using a conceptual model of the process, a method to describe both the likely dermal solvent exposure and solvent uptake through the skin was created. Mechanisms for combining exposures from the dermal and inhalation exposure pathways are described. Using occupational history information together with workplace monitoring records and data from paint manufacturers, both inhalation and dermal exposure to solvents was estimated for the one-hundred and twenty NPS study subjects. Two solvent exposure metrics were calculated. Cumulative exposure was the product of exposure level and time, while average annual intensity was the cumulative exposure figure divided by the number of years in solvent using employment.
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Getachew, Mulugeta Adako. "Endoparasites of working donkeys in Ethiopia : epidemiological study and mathematical modelling." Thesis, University of Glasgow, 2006. http://theses.gla.ac.uk/1444/.

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A mathematical approach was used to model seasonal variation of cyathostomin faecal egg output, and in simulating anthelmintic control strategy. The model is based on parameters of biological development of cyathostomins and climatic data. A good fit of the model prediction to the field data was obtained after some parameter adjustments. The development rate of ingested larvae to egg laying adults, survival time of adults and the assumption made in modelling the peak pasture larval availability were the main driving forces for the model prediction to fit to the observed data. The apparent fit of the model prediction to the field data obtained after parameter adjustment generally indicated some major differences between donkeys and horse in their reaction to the parasite and/or between cyathostomins of donkeys and horses. The results of the stimulation of the effect of various protocols for the timing and frequency of anthelmintic treatment on the adult cyathostomin worm burden have shown that treating donkeys only once in a year or a combination of once in a year followed by every two or even four years can substantially reduces and maintains the parasite burden far below the pre-treatment level for many years. Generally the study made has revealed that the non-strongyle gastrointestinal parasites of donkeys are highly prevalent and have a high pathogenic potential, and the findings of cestodes and trematodes are not accidental or unusual, as previously suggested.
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Martens, Willem Jozef Meine. "Health impacts of climate change and ozone depletion an eco-epidemiological modelling approach /." Maastricht : Maastricht : Universiteit Maastricht ; University Library, Maastricht University [Host], 1997. http://arno.unimaas.nl/show.cgi?fid=5797.

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Riordan, P. "Spatial modelling of epidemiological events : Geographical aspects of world influenza epidemics 1945-1977." Thesis, University of Bristol, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372046.

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Harris, R. C. "Informing development strategies for new tuberculosis vaccines : mathematical modelling and novel epidemiological tools." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2018. http://researchonline.lshtm.ac.uk/4648987/.

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Background: With an estimated 10.4 million incident tuberculosis (TB) cases in 2015, and the current trajectory of 1.5%/year incidence rate decline, new TB vaccines are urgently needed to help meet the WHO goal of tuberculosis elimination by 2050. However, insufficient epidemiological evidence exists to inform TB vaccine development strategies and to assist clinical trial site selection and design. Research to meet these data needs is critical to accelerate TB vaccine development. To maximise the future impact of new TB vaccines, estimates of the population-level impact of vaccine characteristics and implementation strategies are needed to inform design of TB vaccine target product profiles. To accelerate and de-risk clinical trials, appropriate epidemiological data are required to inform trial site selection, sample size calculations and recruitment strategy. However, data availability at trial sites is limited, and prospective studies are resource-intensive, so new methods are needed to collect appropriate data to inform TB vaccine trial design. To inform data-driven development strategies for new TB vaccines, the aims of this thesis were to 1) estimate the epidemiological impact of new TB vaccine characteristics and implementation in China to inform design of target product profiles; and 2) to develop a novel epidemiological spatial mapping tool capable of informing clinical trial design for new TB vaccines in low-income, high-burden settings. Methods: A deterministic, age-structured, Mycobacterium tuberculosis transmission model was developed and calibrated to age-stratified epidemiological and demographic data from China. This was employed to estimate the population-level epidemiological impact of new TB vaccines over the 2025-2050 time horizon, through an exploration of potential vaccine characteristics and implementation strategies. A new methodology for empirical data collection to determine spatial distribution of TB notifications was developed. The electronic PArticipant Locator application (ePAL app) combined 3,243 community-identified points of interest with high resolution satellite maps, within an electronic tablet-based case report form. The app was integrated in to the National Tuberculosis Programme in Blantyre, Malawi, for collection of demographics, health status and coordinates of place of residence for patients ≥18 years initiating TB treatment. Accuracy of ePAL-recorded co-ordinates was evaluated against GPS coordinates obtained at the participant’s place of residence. Results: Mathematical modelling predicted a shift towards a reactivation-driven, ageing TB epidemic in China by 2050. Vaccines protective against disease, effective post-infection and providing at least 5 years protection were essential for achieving higher levels of impact. Vaccination of older adults provided greater population-level impact than vaccinating adolescents for all equivalent vaccines explored, even if much lower coverage were achieved in older adult vaccination. Recommendations for post-infection vaccines were robust to substantial reductions in efficacy and duration of protection in older adults, whereas for pre-infection vaccines in some of these scenarios adolescent vaccination may be equivalent or preferred. Vaccinating older adults with post-infection vaccines provided substantially higher impact than pre-infection vaccines. 1,899 TB patients were registered using ePAL in the 12-month study period, with high patient acceptance (98.7%, 1,899/1,924). ePAL achieved clinic-based collection of patient location of residence accurate to a median of 84 metres (IQR: 35-317 metres) in a high population density urban setting without a municipal address system. Advantages of the ePAL system included real-time availability of high-resolution spatial data, low set up costs, and ease of use by health staff as part of routine TB registration. Data were used to identify areas with high TB burden, potentially suitable for TB vaccine trials. Conclusions: The research presented in this thesis informs the development of appropriate TB vaccines and target populations to maximise future population-level impact. A prevention of disease vaccine efficacious post-infection and delivered to older adults would contribute towards maximising population-level impact in China. Adolescent-targeted tuberculosis vaccines are likely to have low impact in ageing, reactivation-driven epidemics like China, which suggests a modification of the current strategic focus on adolescents among certain funders. Clinical trials should assess disease endpoints, include M.tb-infected and older adult populations, and extend beyond the usual 2-3 years follow up. To support design of disease endpoint trials, ePAL may provide an accurate, easily implementable, low-cost tool for identification of areas of high TB burden in settings without addresses.
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Chen, I.-Cheng Mark. "Gonorrhoea and resistant gonorrhoea in England and Wales : epidemiological modelling for insight and control." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590549.

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Books on the topic "Epidemiological modelling"

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S, Cooper B., and National Co-ordinating Centre for HTA (Great Britain), eds. Systematic review of isolation policies in the hospital management of methicillin-resistant staphylococcus aureus: A review of the literature with epidemiological and economic modelling. Tunbridge Wells: Gray Publishing, on behalf of NCCHTA, 2003.

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Michel, Tchuenche Jean, ed. Infectious disease modelling research progress. Hauppauge, NY: Nova Science Publishers, 2009.

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Manton, Kenneth G. Chronic disease modelling: Measurement and evaluation of the risks of chronic disease processes. London: Charles Griffin & Co. Ltd., 1988.

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Eric, Stallard, ed. Chronic disease modelling: Measurement and evaluation of the risks of chronic disease processes. London: Charles Griffin & Co., 1988.

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George, Christakos, ed. Interdisciplinary public health reasoning and epidemic modelling: The case of Black Death. Berlin: Springer, 2005.

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Intelligent Modelling Prediction and Diagnosis from Epidemiological Data. Taylor & Francis Group, 2021.

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Bhattacharyya, Siddhartha. Intelligent Modelling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond. CRC Press LLC, 2021.

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Bhattacharyya, Siddhartha. Intelligent Modelling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond. Taylor & Francis Group, 2021.

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Bhattacharyya, Siddhartha. Intelligent Modelling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond. Taylor & Francis Group, 2021.

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Bhattacharyya, Siddhartha. Intelligent Modelling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond. Taylor & Francis Group, 2021.

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Book chapters on the topic "Epidemiological modelling"

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Collett, D. "Modelling data from epidemiological studies." In Modelling Binary Data, 223–76. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-4475-7_7.

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Friedman, Avner. "Epidemiological Models with Seasonality." In Lecture Notes on Mathematical Modelling in the Life Sciences, 389–410. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4178-6_14.

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Raw, Sharada Nandan, Ranjit Kumar Upadhyay, and Nilesh Kumar Thakur. "Crisis-Limited Chaotic Dynamics in an Eco-epidemiological System of the Salton Sea." In Mathematical Modelling and Scientific Computation, 201–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28926-2_21.

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Dodd, P. J., C. Pretorius, and B. G. Williams. "Modelling the HIV-Associated TB Epidemic and the Impact of Interventions Aimed at Epidemic Control." In HIV and Tuberculosis, 25–55. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29108-2_3.

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Abstract In this chapter, we focus on mathematical models of tuberculosis epidemiology (TB) that include interactions with HIV and an explicit representation of transmission. We review the natural history of TB and illustrate how its features are simplified and incorporated in mathematical models. We then review the ways HIV influences the natural history of TB, the interventions that have been considered in models, and the way these individual-level effects are represented in models. We then go on to consider population-level effects, reviewing the TB/HIV modelling literature. We first review studies whose focus was on purely epidemiological modelling, and then studies whose focus was on modelling the impact of interventions. We conclude with a summary of the uses and achievements of TB/HIV modelling and some suggested future directions.
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Korir, Evans Kiptoo, and Zsolt Vizi. "Clustering of Countries Based on the Associated Social Contact Patterns in Epidemiological Modelling." In Trends in Biomathematics: Modeling Epidemiological, Neuronal, and Social Dynamics, 253–71. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33050-6_15.

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Mu, Chuping, Jovern Teo, and Joshua Cheong. "Modelling Singapore’s Covid-19 Pandemic Using SEIRQV and Hybrid Epidemiological Models." In IRC-SET 2022, 559–75. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7222-5_42.

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Kumar, Devendra, and Jagdev Singh. "New Aspects of Fractional Epidemiological Model for Computer Viruses with Mittag–Leffler Law." In Mathematical Modelling in Health, Social and Applied Sciences, 283–301. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2286-4_9.

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David, Walter, Federico Baldassi, Silvia Elena Piovan, Antony Hubervic, and Erwan Le Corre. "Combining Epidemiological and Constructive Simulations for Robotics and Autonomous Systems Supporting Logistic Supply in Infectious Diseases Affected Areas." In Modelling and Simulation for Autonomous Systems, 86–107. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70740-8_6.

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Lamers, M. H., J. N. Kok, and E. Lebret. "Combined Neural Network Models for Epidemiological Data: Modelling Heterogeneity and Reduction of Input Correlations." In Artificial Neural Nets and Genetic Algorithms, 147–51. Vienna: Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1_32.

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Sicard, Vianney, Mathieu Andraud, and Sébastien Picault. "A Declarative Modelling Language for the Design of Complex Structured Agent-Based Epidemiological Models." In Lecture Notes in Computer Science, 385–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18192-4_31.

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Conference papers on the topic "Epidemiological modelling"

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Bui, Thi Mai Anh, Mikal Ziane, Serge Stinckwich, Tuong Vinh Ho, Benjamin Roche, and Nick Papoulias. "Separation of concerns in epidemiological modelling." In Modularity '16: Companion volume of the 15th International Conference on Modularity. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2892664.2892699.

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Patrick, Matthew, Richard O. J. H. Stutt, and Christopher A. Gilligan. "Rasterising Epidemiological Host Data Efficiently." In 2014 UKSim-AMSS 16th International Conference on Modelling and Simulation (UKSim). IEEE, 2014. http://dx.doi.org/10.1109/uksim.2014.42.

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Thommes, R., and M. Coates. "Epidemiological Modelling of Peer-to-Peer Viruses and Pollution." In IEEE INFOCOM 2006. 25th IEEE International Conference on Computer Communications. IEEE, 2006. http://dx.doi.org/10.1109/infocom.2006.101.

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"Bridging the gap between air pollution models and epidemiological studies." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.h14.oxley2.

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Gittens, Curtis, and Jemar Greaves. "Transforming BrowserQuest into an epidemiological tool for modelling disease dissemination." In 2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES). IEEE, 2015. http://dx.doi.org/10.1109/cgames.2015.7272972.

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Lie, Bernt. "Epidemiological Models and Process Engineering." In The First SIMS EUROSIM Conference on Modelling and Simulation, SIMS EUROSIM 2021, and 62nd International Conference of Scandinavian Simulation Society, SIMS 2021, September 21-23, Virtual Conference, Finland. Linköping University Electronic Press, 2022. http://dx.doi.org/10.3384/ecp21185481.

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Bui Thi Mai Anh, Serge Stinckwich, Mikal Ziane, Benjamin Roche, and Ho Tuong Vinh. "KENDRICK: A Domain Specific Language and platform for mathematical epidemiological modelling." In 2015 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF). IEEE, 2015. http://dx.doi.org/10.1109/rivf.2015.7049888.

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Ciunkiewicz, Philip, and Svetlana Yanushkevich. "Decision Support Component for the Localized Epidemiological Modelling of COVID-19." In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2023. http://dx.doi.org/10.1109/ssci52147.2023.10371839.

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Wu, Yu-Heng, and Torbjörn E. M. Nordling. "Towards course of disease based epidemiological modelling: motivation and computational optimization." In 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2023. http://dx.doi.org/10.1109/compsac57700.2023.00035.

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Juuso, Esko K. "Intelligent Epidemiological Models for COVID-19." In The First SIMS EUROSIM Conference on Modelling and Simulation, SIMS EUROSIM 2021, and 62nd International Conference of Scandinavian Simulation Society, SIMS 2021, September 21-23, Virtual Conference, Finland. Linköping University Electronic Press, 2022. http://dx.doi.org/10.3384/ecp21185505.

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Reports on the topic "Epidemiological modelling"

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Novoseltsev, Vassili N., Anatoli I. Michalski, Janna A. Novoseltseva, Anatoli I. Yashin, James R. Carey, and Thomas W. Scott. Senescence can play an essential role in modelling and estimation of vector based epidemiological indicators: demographical approach. Rostock: Max Planck Institute for Demographic Research, August 2007. http://dx.doi.org/10.4054/mpidr-wp-2007-027.

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