Скачать или смотреть Understanding the relationship between the epidemiology of, and immune ... by Rebecca Chisholm

DISCUSSION MEETING : MATHEMATICAL AND STATISTICAL EXPLORATIONS IN DISEASE MODELLING AND PUBLIC HEALTH
ORGANIZERS : Nagasuma Chandra, Martin Lopez-Garcia, Carmen Molina-Paris and Saumyadipta Pyne
DATE & TIME : 01 July 2019 to 11 July 2019
VENUE : Madhava Lecture Hall, ICTS, Bangalore

In this program, we will discuss current challenges and recent advances in Health and Disease. The aim of the program is to explore different mathematical, statistical and computational approaches to integrate experimental and clinical data, and to discuss how mathematical modeling can help to interpret and integrate experimental data, frame and test hypotheses, and suggest novel experiments allowing for more conclusive and quantitative interpretations of biological, immunological and disease-related processes. Among others, the following problems will be addressed in this program:

The analysis of disease-related processes occurring across different scales: from the genetic, to the cellular, host and population levels.
At the cellular level, the mechanisms by which cells regulate proliferation, death, differentiation, in childhood, adulthood and old age, and how receptor-mediated signaling and intra-cellular receptor trafficking correlate with cellular fate.
The mechanisms that can affect, by maintaining or avoiding, pathogen diversity, from mutation and genetic drift to antibiotic consumption and selective pressure.
The effect of co-infection in pathogen evolution, and the interplay between the immune response and antimicrobial resistance.
New approaches for incorporating existing individual heterogeneities at the population level into mathematical and computational models.
The need for incorporating host immunity and the immune response into mathematical models for the spread of infectious diseases at the population level, as well as recent attempts to incorporate human behavior into these models.
The applicability of Bayesian statistical techniques as a powerful tool for linking stochastic (or deterministic) mathematical and computational models with clinical or experimental data.

This program is also partially supported by The University of Leeds (UOL) and Medical Research Council (MRC).

APPLICATION DEADLINE : 15 April 2019
CONTACT US : [email protected]
PROGRAM LINK : https://www.icts.res.in/discussion-me...

Table of Contents (powered by https://videoken.com)
0:00:00 Understanding the relationship between the epidemiology of, and immune response to,Group A Streptococcus infection
0:00:33 Thank you
0:00:45 Group A Streptococcus
0:01:55 Global epidemiology of Group A Streptococcus
0:03:02 Low-prevalence population: USA
0:03:55 Hyper-endemic population: Indigenous Australians
0:04:49 Group A Strep disease in Australia - A preventable injustice
0:08:00 What is the best strategy to reduce the burden of Group A Strep disease in Indigenous Australians?
0:09:16 Developing a Group A Strep transmission model
0:10:31 Can we translate global epidemiological data into understanding of within-host dynamics?
0:11:29 Step 1: Build model
0:11:31 Model requirements
0:12:17 Model features
0:14:04 Within-host dynamics
0:15:51 Between-host dynamics of the ABM
0:19:54 Step 2: What within-host conditions (x, sigma, omega, 1/theta) lead to this type of epidemiology?
0:20:08 Measuring prevalence and strain diversity
0:20:55 Diversity regimes in the ABM (governed by x, sigma, omega)
0:24:05 The impact of within-host dynamics on D(t) and P(t)
0:30:13 Interaction between within-host dynamics, D(t) and P(t)
0:31:55 The impact of Ro on diversity and prevalence
0:32:53 Hypothesis for the within-host dynamics of Group A Strep
0:33:46 Fitting model to longitudinal NT data
0:35:31 Fitting model to NT data using BOLFI
0:37:19 Preliminary results
0:38:59 Towards modelling the impact of interventions
0:41:51 Acknowledgements