Stephen Eubank
Biographic Data
| ID | 3571043 |
|---|---|
| NAME | Stephen Eubank |
| GIVEN NAMES | Stephen |
| FAMILY NAME | Eubank |
| SIGNATURE | EUBANK S |
| AFFILIATIONS | Los Alamos National Laboratory |
| ORCID | 0000-0002-7177-309X |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 9 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2017 |
| H-INDEX | 1 |
Addressing the Race Gap in Incarceration Rates
Using an agent-based model of incarceration, the authors conduct a series of simulation experiments testing the efficacy of policy interventions designed to address racial disparities in incarceration rates. The first experiment eliminates race-based sentencing disparities, and additional experiments eliminate race-based sentencing disparities and disrupt the clustering of incarcerated individuals in their social networks. Findings suggest that e…
Impact of Paid Sick Leave Policy
AffiliationsAchla Marathe, Jiangzhuo Chen, and Stephen Eubank are with the Virginia Bioinformatics Institute, Virginia Tech, Blacksburg. Achla Marathe is also with the Department of Agricultural and Applied Economics and Stephen Eubank is also with the Department of Population Health Sciences, Virginia Tech. Shaojuan Liao is with Freddie Mac, Washington, DC. Yifei Ma is with Teradata
Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California
Objectives. We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. Methods. Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with in…
Mixing patterns between age groups in social networks
Modelling disease outbreaks in realistic urban social networks
Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California
Objectives. We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. Methods. Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with in…
Modelling disease outbreaks in realistic urban social networks
Mixing patterns between age groups in social networks
Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California
Objectives. We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. Methods. Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with in…
Impact of Paid Sick Leave Policy
AffiliationsAchla Marathe, Jiangzhuo Chen, and Stephen Eubank are with the Virginia Bioinformatics Institute, Virginia Tech, Blacksburg. Achla Marathe is also with the Department of Agricultural and Applied Economics and Stephen Eubank is also with the Department of Population Health Sciences, Virginia Tech. Shaojuan Liao is with Freddie Mac, Washington, DC. Yifei Ma is with Teradata
Addressing the Race Gap in Incarceration Rates
Using an agent-based model of incarceration, the authors conduct a series of simulation experiments testing the efficacy of policy interventions designed to address racial disparities in incarceration rates. The first experiment eliminates race-based sentencing disparities, and additional experiments eliminate race-based sentencing disparities and disrupt the clustering of incarcerated individuals in their social networks. Findings suggest that e…
Computer Science (4 works) · COVID-19 epidemiological studies (3 works) · Medicine (3 works) · Population (3 works) · Complex Network Analysis Techniques (2 works) · Mathematical and Theoretical Epidemiology and Ecology Models (2 works) · Nursing (2 works) · Political science (2 works) · Public health (2 works) · Sociology (2 works)