IMSc Workshop on
Modeling Infectious Diseases
September 4-6, 2006
Venue: Ramanujan Auditorium, IMSc
Workshop Schedule
4/9/06 (9:15-9:45): Registration
TIME
|
MONDAY (4/9/06)
|
TUESDAY (5/9/06)
|
WEDNESDAY (6/9/06) |
9:45-10:10
|
Inauguration & Opening Remarks
|
Niloy Ganguly
|
|
10:10-11:00
|
B Raveendran
|
Somdatta Sinha
|
Discussion Summaries by
Group Members
|
11:00-11:30
|
Tea/Coffee |
Tea/Coffee |
Tea/Coffee |
11:30-12:20
|
Vineeta Bal |
Mohan D Gupte |
Discussion Summaries by
Group Members
|
12:20-1:10
|
Debashish Chowdhury
|
Sudeshna Sinha
|
Concluding Session
|
1:10-2:10
|
Lunch
|
Lunch
|
Lunch |
2:10-3:00
|
Bhaskar Saha
|
Aparup Das
|
|
3:00-3:30
|
Tea/Coffee
|
Tea/Coffee
|
|
3:30-4:20
|
Parongama Sen
|
S S Manna
|
|
4:20-5:10
|
Gautam Menon
Sitabhra Sinha
|
Sunita Gakkhar
|
|
5:30-6:30
|
Discussion, Informal Group formation
|
Discussion, Informal Group formation |
|
List of Talks
B Raveendran
|
Hygine Hypothesis: Is the proof too far ?
|
| Vineeta Bal |
Vaccines to prevent infectious diseases:
Why do we have very few success stories? |
| Debashish Chowdhury |
Modelling Immune Response: Discrete and
Continuum Approaches |
| Bhaskar Saha |
Reciprocal signaling through CD40 induces
counteractive effector functions |
| Parongama Sen |
Spatial Models of Epidemics
|
Gautam Menon
|
Using Agent-Based Models to study Epidemic
Spreading
|
| Sitabhra Sinha |
Excitable Media with
long-range connections: Modeling waves of epidemic spreading
|
| Niloy Ganguly |
Epidemic spreading on networks: A
topographic view |
| Somdatta Sinha |
Parasite Invasion in Space: Modelling and
Data Analysis
|
| Mohan D Gupte |
Epidemiological Modelling of (a) Leprosy
and (b) HIV |
| Sudeshna Sinha |
Dynamic Transitions in a Model
of Infection Spreading
|
| Aparup Das |
Evolutionary
Genomic Perspective of Malaria
|
| S S Manna |
Disease Spreading in a
Diffusive System |
| Sunita Gakkhar |
Complex dynamical behavior
in epidemiological systems |
Abstracts
Vaccines to prevent infectious
diseases:
Why do we have very few success stories?
Vineeta
Bal
National Institute of Immunology,
Aruna Asaf Ali Road, New Delhi 110067.
In today’s date vaccines are extremely fashionable.
It is a general perception that vaccines provide the safest, most
efficient and permanent way to prevent illnesses. Traditionally
vaccines are used for preventing infectious diseases. In some cases
vaccines are used for limiting further spread of an infectious disease
as well. More recently, vaccines are being developed for prevention of
cancer such as cervical cancer in women; or prevention of metastasis in
cancers such as melanoma or prostate; or preventing worsening of
neurodegenerative diseases such as Alzheimer’s disease. Since a
significant role for vaccines in preventing infectious diseases is
well-established and as the focus of the conference is infectious
diseases, here an attempt will be made to understand how vaccines are
supposed to prevent infectious diseases. With that other questions
would automatically emerge - what is expected out of a ‘successful’
vaccination, are all vaccines ‘successful’, do successful vaccines
provide uniformly good response in every recipient, is it necessary to
trigger such a response in 100% of the individuals, does the same
strategy of vaccine development work for every infectious disease, do
vaccines generate very long lasting immune responses and so on. While
small pox was the first viral disease which was eradicated from the
world with the help of a vaccine, there is hardly any other success
story which matches with small pox eradication. For some diseases many
vaccines have been tried and failed e.g. malaria. Incidence of some
infections has come down significantly with vaccination but eradication
is still a dream e.g. polio. For a new world disease such as AIDS, it
is still unclear what would be the best target for vaccine development!
Many infections prominently found in the third world such as
leshmaniasis [kala azaar], filariasis, infections leading to diarrhoeas
and dysenteries are also the cases where no successful vaccine has been
developed. Are the vaccine failure stories leading to failure in
controlling infections only to do with our limited understanding of
immunology of vaccine development or there are other factors too?!
Evolutionary Genomic Perspective of Malaria
Aparup Das
National Institute of Malaria
Research (ICMR), 22 Sham Nath Marg, New Delhi 110 054
Malaria is a serious tropical infectious disease, causing high
morbidity and mortality mainly in the developing countries, resulting
in huge burden to the country of its endemicity and the society. Being
a vector-borne disease caused by the protozoan parasite Plasmodium,
malaria is a continuous threat to the human health. Even though India
contributes only about 10% of the total malaria cases across the globe,
the severity and relapses of the disease have far-reaching social
implications. Researches from various angles are underway to understand
the disease, its mechanism and to design and develop new therauptic
measures, however, with feeble success. Application of different modern
biological tools with interdisciplinary approaches in malaria research
is the ultimate hope to tackle these scourges. In this respect, the
availability of the whole genome sequence information of all the three
taxa involved in malaria (Plasmodium, Anopheles and humans) at the
public domain and rapid development of statistical-mathematical models
have created an opportunity not only to understand the finer details of
the blueprint of life of each individual taxa but also to unravel the
mystery by which the three organisms interact to cause the disease. The
newly emerging field of evolutionary genomics would help in
understanding the genome in a evolutionary standpoint and infer how
genes responded and evolved differentially in the changing environment
each taxa had faced (e.g. drug pressure to the parasites, spraying of
insecticides to the vectors and malaria burden to humans) in the long
history of the disease. Considering the spatial position of India in
the globe covering a wide latitudinal range with heterogeneous
environment, genetic composition of species populations are expected to
be highly diverse. The bright prospect that malaria research provides
in India with evolutionary genomic and bioinformatic approaches would
not only help mitigating this disease but could also serve as a model
for other infectious diseases.
Complex dynamical behavior in epidemiological systems
Sunita
Gakkhar
Department of Mathematics, I I T
Roorkee, 247667
‘Pulse’ vaccination strategies in contrast to
continuous vaccination are cost effective as they help in disease
eradication at relatively low values of vaccination. A planned pulse
vaccination regime reportedly gives a stable disease free solution in a
SIR epidemic model. The introduction of seasonal variation into the
basic SIR model leads to complex dynamical behavior which includes
periodic, quasi periodic and chaotic dynamics for different choices of
parameters.
The impulsive vaccination strategy applied to an
epidemic model with non-linear incidence rate will be discussed. The
model analysis will be presented. The complex dynamical behavior with
pulse vaccination is expected. To study the influence of key parameters
the results of numerical simulations will be discussed out.
Epidemic Spreading on Networks: A
Topographic View
Niloy Ganguly
Department of Computer Science & Engineering, I I T Kharagpur,
Kharagpur 721302
In this talk we give an overview of a
new approach to understand epidemic spreading on networks. The ideas
are basic, however they have ready application to a wide range of
problems, including the control of the spread of data viruses and other
harmful electronic information. A "topographic" picture of the network
is built, in the sense that there are neighborhoods of high and low
spreading power. Close link between eigenvector centrality (EVC) and
spreading power is established. The topographic picture helps to
develop a detailed understanding, at the level of neighborhoods, of
epidemic spreading over the network. The analysis of spreading thus
gives a finer resolution than typical whole-graph studies. The picture
is strongly confirmed by a series of simulations on empirical
social/information networks, and is also supported by some limited
mathematical results. Finally, a set of design suggestions for both
helping and hindering spreading is put forward, and some test results
of these suggestions are presented. Finally we present how the idea can
be used to enhance performance of search algorithms.
Disease Spreading in a Diffusive System
Subhrangshu Sekhar Manna
Satyendra Nath Bose National Centre
for Basic Sciences (SNBNCBS), Block-JD, Sector - III, Salt Lake,
Kolkata - 700098
The susceptible-infected-susceptible
(SIS) model is discussed for the regular
and scale-free graphs - known results are explained. The dynamics is modified by using a system
of diffusing particles (random walkers) and studying the spreading of
infectious diseases among them. In the context of SIS model, a density
dependent critical point is observed. For Scale-free networks (SFNs)
prevalence seems to saturate at small values at the low infection rates.
Parasite Invasion in Space: Modelling and Data Analysis
Somdatta Sinha
Centre for Cellular and Molecular
Biology, Uppal Road, Hyderabad 500 007, India
Spread of infectious disease in space is due to invasion of parasites
through infected/carrier hosts, vectors, or direct and indirect
dispersal of the parasites among subpopulations of hosts. In nature, a
host metapopulation consists of subpopulations having non-identical
behavioural and demographic properties, occupying habitats of variable
extent/quality and connectivity. Functional dynamics of those species,
which have the capability to induce damage to other species
(e.g.,parasite/pathogen), assume larger importance in the
metapopulation context. Thus interaction of local host-parasite
dynamics and migration in space is important for both ecologists and
epidemiologists.
In this lecture, two approaches to study parasite invasion will be
discussed. First, parasite invasion in a model lattice metapopulation
of host-parasite species with spatial and demographic heterogeneity
will be presented. The spatiotemporal dynamics of host and parasite
with short and long range migration will be discussed. Secondly,
spatiotemporal description of Malaria prevalence data in India will be
shown, and how important information from these maps can be extracted
will be discussed.
Dynamic Transitions in a Model of Infection
Spreading
Sudeshna Sinha
The Institute
of Mathematical Sciences, CIT Campus, Taramani, Chennai
We discuss the nature of dynamic
transitions in a model of infection
spreading. Specifically we examine the role of the underlying network structure on the temporal
dynamics of the epidemic. We find that varying the degree of
disorder in the underlying population network yields transitions from low
quasi-fixed states (analogous to endemic infection) to self-sustained
oscillations arising from synchronized periodic disease outbreaks.
Further we show how the timescales of the local dynamics, in
particular the length of the disease cycle, is also crucial in determining
the dynamic transitions.