Applications of Extreme Value Theory in Public Health

• Published in: PloS one Vol. 11; no. 7; p. e0159312
• Main Authors: Thomas, Maud, Lemaitre, Magali, Wilson, Mark L, Viboud, Cécile, Yordanov, Youri, Wackernagel, Hans, Carrat, Fabrice
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 15-07-2016; Public Library of Science (PLoS)
• Subjects: Adolescent; Adult; Age Factors; Aged; Biology and Life Sciences; Child; Child, Preschool; Emergency medical services; Emergency Service, Hospital; Epidemics; Epidemiology; Extreme value distribution; Extreme value theory; Extreme values; France - epidemiology; Health planning; Health surveillance; Humans; Infant; Influenza; Influenza, Human - epidemiology; Influenza, Human - mortality; Life Sciences; Maxima; Medicine and Health Sciences; Middle Aged; Mortality; People and Places; Physical Sciences; Pneumonia; Pneumonia - epidemiology; Pneumonia - mortality; Probability; Probability Theory and Statistics; Public Health; Sannolikhetsteori och statistik; Santé publique et épidémiologie; Seasons; Surveillance; Time series; Values; Young Adult; France; United States; Sweden; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0159312

We present how Extreme Value Theory (EVT) can be used in public health to predict future extreme events.
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.
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.
The EVT method can be applied to various topics in epidemiology thus contributing to public health planning for extreme events.