This Club EvMed event occurred on February 15, 2024. Learn more about Club EvMed at https://clubevmed.org.
This conversation was led by Dr. Marco Marani & Dr. William Pan.
Human-natural processes that generate extreme events with large financial, social, and health consequences, are inherently non-stationary due to ever-changing anthropogenic pressures and societal exposure. The issues posed by non-stationarity are recognized in Earth system science and are being addressed with a variety of tools and varying degrees of success. These developments are possible because a large amount of observational and modelling information is available. Extensive epidemiological information remains fragmented and virtually unexplored from this perspective due to the lack of approaches to leverage observations of a heterogeneous past. To address this gap, here we describe and analyze a long historical record (1600-present) of infectious disease epidemics assembled from existing literature. This new record enabled the development and applications of methods to quantify the time-varying probability of occurrence of extreme epidemic events. We define the intensity of epidemic events, the number of deaths/time/global population, and find that observations from several hundred years, covering almost four orders of magnitude of epidemic intensity, follow a probability distribution with a slowly-decaying power-law tail (Generalized Pareto Distribution, asymptotic exponent = -0.71). To the contrary, the yearly number of epidemics is non-stationary, implying that conventional extreme value analyses are inappropriate. We find that the rate of occurrence of extreme epidemics varies nine-fold over centennial time scales, from about 0.4 to 3.6 epidemics/year. As a result, yearly occurrence probabilities of extreme epidemics are far from constant: The intensity computed for the most extreme event on record – the “Spanish Influenza” of 1918-1920 – has a probability of occurrence varying from 0.11 to 0.89 %/year in the time frame from 1600 to present. A COVID19-like event is estimated currently having a probability of occurrence of 0.19 % / year. Should the probability of emergence of new diseases remain constant, this translates to a probability of 17% of observing such an event in one’s lifetime.
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