tetano
Editor, Senior Moderator
Infect Dis Model
. 2021 Sep 20;6:1135-1143.
doi: 10.1016/j.idm.2021.09.001. eCollection 2021.
Tail risks and infectious disease: Influenza mortality in the U.S., 1900-2018
Michele Campolieti[SUP] 1 [/SUP]
Affiliations
Abstract
I use extreme values theory and data on influenza mortality from the U.S. for 1900 to 2018 to estimate the tail risks of mortality. I find that the distribution for influenza mortality rates is heavy-tailed, which suggests that the tails of the mortality distribution are more informative than the events of high frequency (i.e., years of low mortality). I also discuss the implications of my estimates for risk management and pandemic planning.
Keywords: Extremes value theory; Generalized Pareto distribution; Heavy-tails; Influenza mortality rates; Tail risks.
. 2021 Sep 20;6:1135-1143.
doi: 10.1016/j.idm.2021.09.001. eCollection 2021.
Tail risks and infectious disease: Influenza mortality in the U.S., 1900-2018
Michele Campolieti[SUP] 1 [/SUP]
Affiliations
- PMID: 34632167
- PMCID: PMC8477200
- DOI: 10.1016/j.idm.2021.09.001
Abstract
I use extreme values theory and data on influenza mortality from the U.S. for 1900 to 2018 to estimate the tail risks of mortality. I find that the distribution for influenza mortality rates is heavy-tailed, which suggests that the tails of the mortality distribution are more informative than the events of high frequency (i.e., years of low mortality). I also discuss the implications of my estimates for risk management and pandemic planning.
Keywords: Extremes value theory; Generalized Pareto distribution; Heavy-tails; Influenza mortality rates; Tail risks.