Abstract
Black swan events in infectious disease describe rare but devastatingly large outbreaks. While experts are skeptical that such events are predictable, it might be possible to identify the warning signs of a black swan event. Specifically, following the initiation of an outbreak, key differentiating features could serve as alerts. Such features could be derived from meta-analyses of large outbreaks for multiple infectious diseases. We hypothesized there may be common features among the pathogen, environment, and host epidemiological triad that characterize an infectious disease black swan event. Using Los Alamos National Laboratory’s tool, Analytics for Investigation of Disease Outbreaks, we investigated historical disease outbreak information and anomalous events for several infectious diseases. By studying 32 different infectious diseases and global outbreaks, we observed that in the past 20–30 years, there have been potential black swan events in the majority of infectious diseases analyzed. Importantly, these potential black swan events cannot be attributed to the first introduction of the disease to a susceptible host population. This paper describes our observations and perspectives and illustrates the value of broad analysis of data across the infectious disease realm, providing insights that may not be possible when we focus on singular infectious agents or diseases. Data analytics could be developed to warn health authorities at the beginning of an outbreak of an impending black swan event. Such tools could complement traditional epidemiological modeling to help forecast future large outbreaks and facilitate timely warning and effective, targeted resource allocation for mitigation efforts.
Highlights
Disease outbreaks are primarily influenced by three factors, the pathogen, environment, and host, which form an epidemiological triangle influencing disease severity and pathogen dissemination (Scholthof, 2007)
We investigated whether there were (1) anomalous outbreaks that could be described for the diseases we researched, and (2) key common differentiating features that could be classified as warning signs of a potential black swan event
Having potential black swan outbreaks (PBSO) identified in 17 of the 32 diseases investigated in our study strongly suggests that all types of infectious outbreaks have the potential to become black swan events
Summary
Disease outbreaks are primarily influenced by three factors, the pathogen, environment, and host, which form an epidemiological triangle influencing disease severity and pathogen dissemination (Scholthof, 2007). We leveraged the large amount of data and analytics present in AIDO for 32 different infectious diseases to test our hypothesis that there may be common features from the pathogen, environment, or host epidemiological triad that characterize a potential infectious disease black swan event. Using the AIDO disease libraries and anomaly detection algorithm, we identified potential black swan outbreaks (PBSO) for 32 infectious diseases. Vaccine-preventable diseases, such as ebola, measles, mumps, novel influenza A, pertussis, rubella, yellow fever, and dengue (has vaccine development potential) had PBSOs caused by convergence of two differentiating factors from the epidemiological triad These were either a convergence of host and pathogen, or host and manmade environmental factors (health infrastructure and behavioral factors such as vaccine hesitancy). There is no requirement for a convergence of the epidemiological triad as is necessary for an outbreak to occur
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