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Spatial Associations Of Liver Disease Rates With Socioeconomic And Health Risk Factors In Georgia, Nguyet Le
Spatial Associations Of Liver Disease Rates With Socioeconomic And Health Risk Factors In Georgia, Nguyet Le
Symposium of Student Scholars
According to the CDC Cancer Statistics Report in 2020, Liver and Intrahepatic Bile Duct is the 6th leading cancer in both USA and the State of Georgia ranked by Rates of Cancer Death. Aflatoxin-containing foods, alcohol consumption, smoking, overeating, and other risky behaviors are among the factors linked to liver diseases. They have also been related to the socioeconomic status (SES) of individuals. The behaviors and SES of individuals are affected by the socioeconomic characteristics of the communities where they live. However, the relationships between the rates of liver diseases and community-level socioeconomic factors are not well studied. The objective …
An Agent-Based Modeling Approach To Spatial Accessibility, Alexander C. Michels, Shaowen Wang
An Agent-Based Modeling Approach To Spatial Accessibility, Alexander C. Michels, Shaowen Wang
I-GUIDE Forum
Place-based spatial accessibility represents the ability of populations within geographic units to access goods and services, and thus is an important indicator for sustainable development. Existing spatial accessibility models treat population as simply demand, calculating statistics or optimizing average cost for the population within each geographic unit, rather than modeling individual decisions. This paper proposes AgentAccess, a general-purpose Agent-Based Model (ABM) for spatial accessibility analysis. An ABM framework brings us closer to reality by simulating individual and imperfect decision-making. We introduce the model and compare its results against existing spatial accessibility models using a case study of hospital beds in …
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …