Want to know when the pandemic will be over? Computer science may have the answer
The million-dollar question: Are there worse variants of concern to come?
Definitions and diagrams
Iconducted an ontological analysisof “pandemic”. First, I needed to find definitions of a pandemic.
Informally, an epidemic is an occurrence during which there are multiple instances of an infectious disease in organisms, for a limited duration of time, that affects a community of said organisms living in some region. A pandemic, as a minimum, extends the region where the infections take place.
Next, I drew from existing foundational ontologies. This contains generic categories like “object”, “process”, and “quality”. I also used domain ontologies, which contain entities specific to a subject domain, like infectious diseases. Among other resources, I consulted theInfectious Disease Ontologyand theDescriptive Ontology for Linguistic and Cognitive Engineering.
First, I aligned “pandemic” to a foundational ontology, using adecision diagramto simplify the process. This helped to work out what kind ofthing and generic category“pandemic” is:
(1) Is [pandemic] something that is happening or occurring? Yes (perdurant, i.e., something that unfolds in time, rather than be wholly present).
(2) Are you able to be present or participate in [a pandemic]? Yes (event).
(3) Is [a pandemic] atomic, i.e., has no subdivisions and has a definite endpoint? No (accomplishment).
The word “accomplishment” may seem strange here. But, in this context, it makes clear that a pandemic is atemporal entitywith a limited lifespan and will evolve – that is,cease to be a pandemic and evolve back to epidemic, as indicated in this diagram.
Characteristics
Next, I examined a pandemic’s characteristics described in the literature. A comprehensive list is described ina paperby US infectious disease specialists published in 2009 during the global H1N1 influenza virus outbreak. They collated eight characteristics of a pandemic.
I listed them and assessed them from an ontological perspective:
Properties with imprecise boundaries annoy epidemiologists because they may lead todifferent outcomes of their prediction models. But from my ontologist’s viewpoint, we’re getting somewhere with these properties. From the computational side,automated reasoning with fuzzy featuresis possible.
COVID, at least early in 2020, easily ticked all eight boxes. A suitably automated reasoner would have classified that situation as a pandemic. But now, in early 2022? Severity (point 8) has largely decreased and immunity (point 4) has risen. Point 5 – are there worse variants of concern to come – is the million-dollar question. More ontological analysis is needed.
Highlighting the difficulties
Ontologically speaking, then, a pandemic is an event (“accomplishment”) that unfolds in time. To be classified as a pandemic, there are a number of features that aren’t all crisp and for which the imprecise boundaries haven’t all been set. Conversely, it implies that classifying the event as “not a pandemic” is just as imprecise.
This isn’t a full answer as to what a pandemic is ontologically, but it does shed light on the difficulties of calling it “over” – and illustrates well that there will be disagreement about it.
This article byMaria Keet, Associate professor in Computer Science,University of Cape Townis republished fromThe Conversationunder a Creative Commons license. Read theoriginal article.
Story byThe Conversation
An independent news and commentary website produced by academics and journalists.An independent news and commentary website produced by academics and journalists.
Get the TNW newsletter
Get the most important tech news in your inbox each week.
