Disease Modelling And Public Health Part A
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Author | : |
Publisher | : North Holland |
Total Pages | : 0 |
Release | : 2017-10-13 |
Genre | : Mathematics |
ISBN | : 9780444639684 |
Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk factor of death, Alternative Sampling Designs for Time-To-Event Data with Applications to Biomarker Discovery in Alzheimer's Disease, Dynamic risk prediction for cardiovascular disease: An illustration using the ARIC Study, Theoretical advances in type 2 diabetes, Finite Mixture Models in Biostatistics, and Models of Individual and Collective Behavior for Public Health Epidemiology. As a two part volume, the series covers an extensive range of techniques in the field. It present a vital resource for statisticians who need to access a number of different methods for assessing epidemic spread in population, or in formulating public health policy.
Author | : Emilia Vynnycky |
Publisher | : OUP Oxford |
Total Pages | : 400 |
Release | : 2010-05-13 |
Genre | : Medical |
ISBN | : 0191511358 |
Mathematical models are increasingly being used to examine questions in infectious disease control. Applications include predicting the impact of vaccination strategies against common infections and determining optimal control strategies against HIV and pandemic influenza. This book introduces individuals interested in infectious diseases to this exciting and expanding area. The mathematical level of the book is kept as simple as possible, which makes the book accessible to those who have not studied mathematics to university level. Understanding is further enhanced by models that can be accessed online, which will allow readers to explore the impact of different factors and control strategies, and further adapt and develop the models themselves. The book is based on successful courses developed by the authors at the London School of Hygiene and Tropical Medicine. It will be of interest to epidemiologists, public health researchers, policy makers, veterinary scientists, medical statisticians and infectious disease researchers.
Author | : |
Publisher | : Elsevier |
Total Pages | : 392 |
Release | : 2017-10-31 |
Genre | : Mathematics |
ISBN | : 0444639764 |
Handbook of Statistics: Disease Modelling and Public Health, Part B, Volume 37 addresses new challenges in existing and emerging diseases. As a two part volume, this title covers an extensive range of techniques in the field, with this book including chapters on Reaction diffusion equations and their application on bacterial communication, Spike and slab methods in disease modeling, Mathematical modeling of mass screening and parameter estimation, Individual-based and agent-based models for infectious disease transmission and evolution: an overview, and a section on Visual Clustering of Static and Dynamic High Dimensional Data. This volume covers the lack of availability of complete data relating to disease symptoms and disease epidemiology, one of the biggest challenges facing vaccine developers, public health planners, epidemiologists and health sector researchers. Presents a comprehensive, two-part volume written by leading subject experts Provides a unique breadth and depth of content coverage Addresses the most cutting-edge developments in the field
Author | : Michael Y. Li |
Publisher | : Springer |
Total Pages | : 163 |
Release | : 2018-01-30 |
Genre | : Mathematics |
ISBN | : 3319721224 |
This text provides essential modeling skills and methodology for the study of infectious diseases through a one-semester modeling course or directed individual studies. The book includes mathematical descriptions of epidemiological concepts, and uses classic epidemic models to introduce different mathematical methods in model analysis. Matlab codes are also included for numerical implementations. It is primarily written for upper undergraduate and beginning graduate students in mathematical sciences who have an interest in mathematical modeling of infectious diseases. Although written in a rigorous mathematical manner, the style is not unfriendly to non-mathematicians.
Author | : Arni S. R. Srinivasa Rao |
Publisher | : |
Total Pages | : 0 |
Release | : 2017 |
Genre | : Diseases |
ISBN | : |
Author | : Saak, Alexander E. |
Publisher | : Intl Food Policy Res Inst |
Total Pages | : 48 |
Release | : 2016-05-03 |
Genre | : Social Science |
ISBN | : |
When an outbreak of an infectious disease is suspected, a local health agency may notify a state or federal agency and request additional resources to investigate and, if necessary, contain it. However, due to capacity constraints, state and federal health agencies may not be able to grant all such requests, which may give an incentive to local agencies to request help strategically. We study a model of detection and control of an infectious disease by local health agencies in the presence of imperfect information about the likelihood of an outbreak and limited diagnostic capacity. When diagnostic capacity is rationed based on reports of symptoms, the decision to report symptoms or not creates a trade-off. On the one hand, rigorous testing allows one to make an informed disease control decision. On the other hand, it also increases the probability that the disease will spread from an untested area where fewer precautionary measures are taken. Symptoms are overreported (respectively, reported truthfully, or underreported) when the cost of disease control is sufficiently small (respectively, in some intermediate range, or sufficiently large). If the disease incidence decreases or infectiousness increases, symptoms are reported less frequently. If the precision of private signals increases, the extent of overreporting of symptoms may increase. For different values of the parameters it can be socially optimal to subsidize or tax requests for additional investigations and confirmatory testing.
Author | : Jummy David |
Publisher | : Springer Nature |
Total Pages | : 324 |
Release | : 2023-12-30 |
Genre | : Mathematics |
ISBN | : 3031408055 |
This volume addresses SDG 3 from a mathematical standpoint, sharing novel perspectives of existing communicable disease modelling technologies of the next generation and disseminating new developments in modelling methodologies and simulation techniques. These methodologies are important for training and research in communicable diseases and can be applied to other threats to human health. The contributions contained in this collection/book cover a range of modelling techniques that have been and may be used to support decision-making on critical health related issues such as: Resource allocation Impact of climate change on communicable diseases Interaction of human behaviour change, and disease spread Disease outbreak trajectories projection Public health interventions evaluation Preparedness and mitigation of emerging and re-emerging infectious diseases outbreaks Development of vaccines and decisions around vaccine allocation and optimization The diseases and public health issues in this volume include, but are not limited to COVID-19, HIV, Influenza, antimicrobial resistance (AMR), the opioid epidemic, Lyme Disease, Zika, and Malaria. In addition, this volume compares compartmental models, agent-based models, machine learning and network. Readers have an opportunity to learn from the next generation perspective of evolving methodologies and algorithms in modelling infectious diseases, the mathematics behind them, the motivation for them, and some applications to supporting critical decisions on prevention and control of communicable diseases. This volume was compiled from the weekly seminar series organized by the Mathematics for Public Health (MfPH) Next Generation Network. This network brings together the next generation of modellers from across Canada and the world, developing the latest mathematical models, modeling methodologies, and analytical and simulation tools for communicable diseases of global public health concerns. The weekly seminar series provides a unique forum for this network and their invited guest speakers to share their perspectives on the status and future directions of mathematics of public health.
Author | : |
Publisher | : North Holland |
Total Pages | : 0 |
Release | : 2017-10-31 |
Genre | : Mathematics |
ISBN | : 9780444639752 |
Handbook of Statistics: Disease Modelling and Public Health, Part B, Volume 37 addresses new challenges in existing and emerging diseases. As a two part volume, this title covers an extensive range of techniques in the field, with this book including chapters on Reaction diffusion equations and their application on bacterial communication, Spike and slab methods in disease modeling, Mathematical modeling of mass screening and parameter estimation, Individual-based and agent-based models for infectious disease transmission and evolution: an overview, and a section on Visual Clustering of Static and Dynamic High Dimensional Data. This volume covers the lack of availability of complete data relating to disease symptoms and disease epidemiology, one of the biggest challenges facing vaccine developers, public health planners, epidemiologists and health sector researchers.
Author | : Zhilan Feng |
Publisher | : World Scientific |
Total Pages | : 306 |
Release | : 2014-04-16 |
Genre | : Mathematics |
ISBN | : 9814522368 |
Mathematical models can be very helpful to understand the transmission dynamics of infectious diseases. This book presents examples of epidemiological models and modeling tools that can assist policymakers to assess and evaluate disease control strategies.
Author | : Abba B. Gumel |
Publisher | : American Mathematical Soc. |
Total Pages | : 286 |
Release | : 2010 |
Genre | : Mathematics |
ISBN | : 0821843842 |
This volume stems from two DIMACS activities, the U.S.-Africa Advanced Study Institute and the DIMACS Workshop, both on Mathematical Modeling of Infectious Diseases in Africa, held in South Africa in the summer of 2007. It contains both tutorial papers and research papers. Students and researchers should find the papers on modeling and analyzing certain diseases currently affecting Africa very informative. In particular, they can learn basic principles of disease modeling and stability from the tutorial papers where continuous and discrete time models, optimal control, and stochastic features are introduced.