» Articles » PMID: 27419853

Applications of Extreme Value Theory in Public Health

Overview
Journal PLoS One
Date 2016 Jul 16
PMID 27419853
Citations 10
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: We present how Extreme Value Theory (EVT) can be used in public health to predict future extreme events.

Methods: We applied EVT to weekly rates of Pneumonia and Influenza (P&I) deaths over 1979-2011. We further explored the daily number of emergency department visits in a network of 37 hospitals over 2004-2014. Maxima of grouped consecutive observations were fitted to a generalized extreme value distribution. The distribution was used to estimate the probability of extreme values in specified time periods.

Results: An annual P&I death rate of 12 per 100,000 (the highest maximum observed) should be exceeded once over the next 30 years and each year, there should be a 3% risk that the P&I death rate will exceed this value. Over the past 10 years, the observed maximum increase in the daily number of visits from the same weekday between two consecutive weeks was 1133. We estimated at 0.37% the probability of exceeding a daily increase of 1000 on each month.

Conclusion: The EVT method can be applied to various topics in epidemiology thus contributing to public health planning for extreme events.

Citing Articles

Research on the Collision Risk of Fusion Operation of Manned Aircraft and Unmanned Aircraft at Zigong Airport.

Huang L, Huang C, Zhou C, Xie C, Zhao Z, Huang T Sensors (Basel). 2024; 24(15).

PMID: 39123889 PMC: 11314915. DOI: 10.3390/s24154842.


Extreme value analysis of the number of student absences in Jiangsu, China: Based on extreme value theory.

Liu M, Yang W, Tian T, Yang J, Ding Z PLoS One. 2024; 19(5):e0302360.

PMID: 38768155 PMC: 11104677. DOI: 10.1371/journal.pone.0302360.


Glomerular hyperfiltration and hypertrophy: an evaluation of maximum values in pathological indicators to discriminate "diseased" from "normal".

Kataoka H, Nitta K, Hoshino J Front Med (Lausanne). 2023; 10:1179834.

PMID: 37521339 PMC: 10372422. DOI: 10.3389/fmed.2023.1179834.


Spatial Methods for Inferring Extremes in Dengue Outbreak Risk in Singapore.

Soh S, Ho S, Seah A, Ong J, Richards D, Gaw L Viruses. 2022; 14(11).

PMID: 36366548 PMC: 9695662. DOI: 10.3390/v14112450.


Cardiovascular Health Peaks and Meteorological Conditions: A Quantile Regression Approach.

Chiu Y, Chebana F, Abdous B, Belanger D, Gosselin P Int J Environ Res Public Health. 2021; 18(24).

PMID: 34948883 PMC: 8701630. DOI: 10.3390/ijerph182413277.


References
1.
Josseran L, Nicolau J, Caillere N, Astagneau P, Brucker G . Syndromic surveillance based on emergency department activity and crude mortality: two examples. Euro Surveill. 2007; 11(12):225-9. View

2.
Guillou A, Kratz M, Le Strat Y . An extreme value theory approach for the early detection of time clusters. A simulation-based assessment and an illustration to the surveillance of Salmonella. Stat Med. 2014; 33(28):5015-27. DOI: 10.1002/sim.6275. View

3.
Simonsen L, Clarke M, Williamson G, Stroup D, Arden N, Schonberger L . The impact of influenza epidemics on mortality: introducing a severity index. Am J Public Health. 1998; 87(12):1944-50. PMC: 1381234. DOI: 10.2105/ajph.87.12.1944. View

4.
Chen J, Lei X, Zhang L, Peng B . Using extreme value theory approaches to forecast the probability of outbreak of highly pathogenic influenza in Zhejiang, China. PLoS One. 2015; 10(2):e0118521. PMC: 4339379. DOI: 10.1371/journal.pone.0118521. View

5.
Khan A, Lurie N . Health security in 2014: building on preparedness knowledge for emerging health threats. Lancet. 2014; 384(9937):93-7. PMC: 7133592. DOI: 10.1016/S0140-6736(14)60260-9. View