A Global Stochastic Modeling Framework to Simulate and Visualize Epidemics

A Global Stochastic Modeling Framework to Simulate and Visualize Epidemics

Date: May 2012
Creator: Indrakanti, Saratchandra
Description: Epidemics have caused major human and monetary losses through the course of human civilization. It is very important that epidemiologists and public health personnel are prepared to handle an impending infectious disease outbreak. the ever-changing demographics, evolving infrastructural resources of geographic regions, emerging and re-emerging diseases, compel the use of simulation to predict disease dynamics. By the means of simulation, public health personnel and epidemiologists can predict the disease dynamics, population groups at risk and their geographic locations beforehand, so that they are prepared to respond in case of an epidemic outbreak. As a consequence of the large numbers of individuals and inter-personal interactions involved in simulating infectious disease spread in a region such as a county, sizeable amounts of data may be produced that have to be analyzed. Methods to visualize this data would be effective in facilitating people from diverse disciplines understand and analyze the simulation. This thesis proposes a framework to simulate and visualize the spread of an infectious disease in a population of a region such as a county. As real-world populations have a non-homogeneous demographic and spatial distribution, this framework models the spread of an infectious disease based on population of and geographic distance between ...
Contributing Partner: UNT Libraries
Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies

Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies

Date: August 2015
Creator: Indrakanti, Saratchandra
Description: POD (Point of Dispensing)-based emergency response plans involving mass prophylaxis may seem feasible when considering the choice of dispensing points within a region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable sub-populations, resulting in access disparities during emergency response. Federal authorities emphasize on the need to identify sub-populations that cannot avail regular services during an emergency due to their special needs to ensure effective response. Vulnerable individuals require the targeted allocation of appropriate resources to serve their special needs. Devising schemes to address the needs of vulnerable sub-populations is essential for the effectiveness of response plans. This research focuses on data-driven computational methods to quantify and address vulnerabilities in response plans that require the allocation of targeted resources. Data-driven methods to identify and quantify vulnerabilities in response plans are developed as part of this research. Addressing vulnerabilities requires the targeted allocation of appropriate resources to PODs. The problem of resource allocation to PODs during public health emergencies is introduced and the variants of the resource allocation problem such as the spatial allocation, spatio-temporal allocation and optimal resource subset variants are formulated. Generating optimal resource allocation and scheduling solutions can be computationally hard ...
Contributing Partner: UNT Libraries
A Framework to Simulate and Visualize Epidemics

A Framework to Simulate and Visualize Epidemics

Date: June 21, 2013
Creator: Mikler, Armin R.; O'Neill, Marty; Helsing, Joseph; Camp, Taylor & Indrakanti, Saratchandra
Description: This poster was featured at the 2013 Perot Museum of Nature and Science's 'Social Science' exhibit. The poster discusses a framework to simulate and visualize epidemics.
Contributing Partner: UNT College of Engineering
Global Stochastic Field Simulator

Global Stochastic Field Simulator

Date: June 21, 2013
Creator: Mikler, Armin R.; O'Neill, Marty; Helsing, Joseph; Camp, Taylor & Indrakanti, Saratchandra
Description: This poster was featured at the 2013 Perot Museum of Nature and Science's 'Social Science' exhibit. It discusses the Global Stochastic Field Simulator, conceived in the summer of 2011.
Contributing Partner: UNT College of Engineering
Quantifying Access Disparities in Response Plans

Quantifying Access Disparities in Response Plans

Date: January 15, 2016
Creator: Indrakanti, Saratchandra; Mikler, Armin R.; O'Neil II, Martin & Tiwari, Chetan
Description: This article develops and explores data driven methods to quantify vulnerabilities in the context of response plans, addressing limitations on the availability, granularity, and currency of data to identify vulnerable populations.
Contributing Partner: UNT College of Engineering