Name
Abstract | ||
|---|---|---|
Extreme value theory can address the tail risk of a pandemic. In particular, a generalized Pareto distribution accommodates well the data from 72 major historical pandemics. One interesting finding is that the distribution of fatalities is heavy-tailed. Here, we analyze the duration of such historical pandemics. We find pandemic duration is heavy-tailed, too, with infinite variance. We also find power laws that help predict the lower bound of pandemic duration in-sample. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.cnsns.2022.106565 | COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION |
Keywords | DocType | Volume |
Tail risk, Generalized pareto distribution, Pandemics | Journal | 113 |
ISSN | Citations | PageRank |
1007-5704 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raul Matsushita | 1 | 0 | 0.68 |
| Mateus Nagata | 2 | 0 | 0.34 |
| sergio ceroni da silva | 3 | 25 | 4.88 |