Armin R. Mikler

Towards Computational Epidemiology

Designing an Infectious Disease Outbreak Simulator

Armin R. MiklerDepartment of Computer Science and Engineering

Department of Biological Sciences

University of North Texas

Armin R. Mikler

Towards Computational Epidemiology

Address broader aspects of EpidemiologyAddress broader aspects of EpidemiologyDisease Tracking, Analysis, and Surveillance

High Performance Computing (HPC)

Simulation

Data visualization.

Design and implement computational tools Design and implement computational tools – investigating Tuberculosis outbreaks and risk assessment

in spatially delineated environments – modeling and simulating details of specific instances of

Tuberculosis occurrences in North Texas – applicable to a wide variety of disease outbreaks in spatially well-defined settings

Contribute towards establishing computational Contribute towards establishing computational epidemiology as a new research domain!!epidemiology as a new research domain!!

Armin R. Mikler

Disease Outbreak Model

Local Global

• Global – Demography– Socio-economics– Travel

– Transportation

– Geography– Culture

• Local– Delineated space

• Factory, homeless shelter, school

– Airflow– Heating and cooling– Distances in feet– Architectural properties

Armin R. Mikler

Global Stochastic Cellular Automata Global Stochastic Cellular Automata and the SWARMand the SWARM

Top Layer:Cellular Automata

Global

Middle Layer: Cellular Automata

Regional

Bottom Layer: SWARM

Local

Armin R. Mikler

The Focus of Study--Locality basedThe Focus of Study--Locality based

This study proposes to model the dynamics of tuberculosis transmission within two facilities in North Texas - a homeless shelter facility providing both long and short-term occupancy with 800 beds, and a factory.

Data was previously collected through interviews during targeted surveillance screening of workers in the factory and homeless people who use the shelter.

Data has been Deidentified !!!

Armin R. Mikler

Homeless Shelter Data and FindingsHomeless Shelter Data and Findings

For the homeless shelter, the data set comprises screening records for each case including: •Date tested (relative to t0)•Status of tuberculosis•Location in the facility•Length of time spent in the facility•Other variables

Results of initial analysis suggest that TB risk is not uniformly distributed but depends on the location of the sleeping bed and duration and frequency of stay at the night shelter.

Armin R. Mikler

Armin R. Mikler

Factory Data and FindingsFactory Data and Findings

In addition to basic screening records as collected for the homeless shelter, other available data for the factory include measures of duration and proximity to infected person such as: • Hours per week in the factory• Hours per week in the same workspace• Hours per week within 3 feet of infected person• Usual work area.

Results of initial analysis indicate that proximity of workspace to infected person was a major determinant of infection.

In fact 100% of those who worked directly in the same space with one infected person were infected with the same strain of TB.

Armin R. Mikler

Factory LayoutFactory Layout

Armin R. Mikler

The Paint Area

The Eating AreaAir vent system

The Restroom

Armin R. Mikler

Modeling ApproachesModeling Approaches

Agent based modeling Level of exposure Emergent behavior defined by individuals’ actions. The average number of bacilli that are emitted (through

coughing, sneezing, etc.) Spatial interaction.

Stochastic Cellular Automata Ambient temperature and airflow Particle Suspension and Dispersion Intrinsically stochastic.

Armin R. Mikler

  From GIS data to Agent-Based From GIS data to Agent-Based SimulationSimulation to Visualization to Visualization

GIS/ Epidemiologic Data

Social Interactions

Visualization

Particle suspension & Airflow

Armin R. Mikler

Movement and DesireMovement and Desire

Desire Functions

0

1

2

3

4

5

6

7

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96

Time (t)

f(x)

Smoking

ThirstSmoking Threshold

Thirst Threshold Example of functions that model different types of desire as a function of time.

A

D

B

CS/D A B C D …A - B C B …B A - C C …C A B - D …D C C C - …… … … … … …Agent at (xi, yi)

Armin R. Mikler

Particle Suspension and DispersionParticle Suspension and Dispersion

Settling of bacilli

Time

As a function of time, bacilli settle toward the ground and may spread to neighboring cells

Armin R. Mikler

State of each cell Ci,j depends on Ci,j+1, Ci,j-1, Ci+1,j, Ci-1,j, Ci+1,j-1, Ci+1,j+1, Ci-1,j-1, Ci-1,j+1

The color of a cell changes based on the majority color of its neighbors

T0 T1

Armin R. Mikler

Visualization--‘Simulated’ ‘Simulated’ SimulationSimulation

Healthy Person Normal

Weaker Person Low/Med TB

Sick Person High TB

Removed Floor

Obstacle

Wall

Pathogen Content

Obstructability

Armin R. Mikler

Armin R. Mikler

Armin R. Mikler

Armin R. Mikler

Armin R. Mikler

The Future: Clusters and the GRID

Faster hardware and new high-bandwidth networks demand that we explore new cluster architectures.

Larger, more complex cluster environments make it imperative to invest in new efficient and scalable tools.

Grand Challenge problems will continue to drive the development of computing infrastructure.

Distributed HPC will become common place. (DOE SciDAC)

Management Tools designed for single hosts or small clusters are likely NOT to scale.

New types of Middleware is needed to decouple the underlying distributed infrastructure from the applications.

Armin R. Mikler

Grid Layers…virtualization

Internet / PrivateNetworks

GridEngine

GridEngine

GridEngine

GridEngine

GridEngine

GridEngine

General Grid Services

Application-Specific Grid Services (APIs)

Applications

Middleware

Grid Access

i.e., ScientificDiscovery throughAdvance Computing

Data Grid

Comp.Grid

BioGrid

Armin R. Mikler

Matter of Facts….

There is increasing demand for harnessing computational resources Increasing demand for Grid-based computing at the private sector

Computing Power will become a commodity like Water, Gas, etc. As with ISPs, Grid Access Providers (GAPs) will have to guarantee

Quality of Service.

Through Grid Services, we can provide a global computing infrastructure and facilitate services for a large number of application domains at the private and public sector!

Examples: Healthcare, Education, Industrial R&D, Entertainment, Sciences, etc.

Armin R. Mikler

Cluster SemanticsCluster Semantics

MASTERNODE

NetworkingInterconnect

Cluster Nodes

Armin R. Mikler

Armin R. Mikler

Armin R. Mikler

People Behind - The GroupPeople Behind - The Group

Armin R. Mikler

A Final Push to Control TB

Because the number of cases of TB in the U.S. are lower than they’ve ever been, we have the opportunity to finally control TB in the U.S.

Recent research suggests that focusing on the dynamics of how TB is transmitted in specific locations is a much-needed final push to TB control.

Homeless shelters and overcrowded areas constitute reservoirs of TB infection.

Yet little research exists on the dynamics of localized TB transmission in homeless shelters.

Little attention has been given to places like factories, warehouses, healthcare facilities, or schools where people work in close proximity for long periods of time.

Armin R. Mikler

Cray Y-MP & IBM Power4Cray Y-MP & IBM Power4

“Common” supercomputer in early 1990's

~$1 million from Cray Max speed: 2.3 gigaflops (record

speed)

• Pentium III 1Ghz processors. Same processors sold “off the shelf”

• 64 gigaflops• 198th on Top500 list

(http://www.top500.org)

Armin R. Mikler

Big Mac @ Virginia Tech

Macintosh G5 workstations

Infiniband networking interconnect

3rd fastest supercomputer in the world

Armin R. Mikler

Cellular Automata (4 Neighbors – von Newman)

State of each cell Ci,j depends on the neighbors Ci,j+1, Ci,j-1, Ci+1,j, Ci-1,j

For example, the color of a cell depends on the majority color of its neighbors

T0 T1