Name
Title | ||
|---|---|---|
Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription |
Abstract | ||
|---|---|---|
•Model represents individual-level contact tracing information using dynamic graphs.•S,E,I,R compartments are treated as probabilistic entities to capture uncertainty.•Model identifies individuals who are likely to be asymptomatic.•Polynomial Chaos Expansion formulation for quantifying uncertainties in the model.•Optimal testing prescription under limited resources to balance risk and uncertainty. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jbi.2021.103901 | Journal of Biomedical Informatics |
Keywords | DocType | Volume |
Covid-19 transmission,Contact tracing data,Dynamic graphs,Probabilistic SEIR model,Polynomial Chaos Expansion,Optimal testing prescription | Journal | 122 |
ISSN | Citations | PageRank |
1532-0464 | 1 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| shashanka ubaru | 1 | 58 | 8.97 |
| Lior Horesh | 2 | 2 | 0.69 |
| Guy Cohen | 3 | 2 | 0.69 |