In early 2022, practically two years after Covid was declared a pandemic by the World Well being Group, consultants are mulling a big question: when is a pandemic “over”?
So, what’s the reply? What standards must be used to find out the “finish” of Covid’s pandemic part? These are deceptively easy questions and there are not any straightforward solutions.
I’m a pc scientist who investigates the event of ontologies. In computing, ontologies are a method to formally construction data of a topic area, with its entities, relations, and constraints, in order that a pc can course of it in numerous purposes and assist people to be extra exact.
Ontologies can uncover data that’s been missed till now: in one instance, an ontology recognized two further practical domains in phosphatases (a bunch of enzymes) and a novel area structure of part of the enzyme. Ontologies additionally underlie Google’s Knowledge Graph that’s behind these data panels on the right-hand facet of a search consequence.
Making use of ontologies to the questions I posed firstly is helpful. This method helps to make clear why it’s tough to specify a cut-off level at which a pandemic may be declared “over”. The method includes accumulating definitions and characterizations from area consultants, like epidemiologists and infectious illness scientists, consulting related analysis and different ontologies, and investigating the character of what entity “X” is.
“X”, right here, could be the pandemic itself – not a mere shorthand definition, however trying into the properties of that entity. Such a exact characterization of the “X” will even reveal when an entity is “not an X”. For example, if X = home, a property of homes is that all of them should have a roof; if some object doesn’t have a roof, it positively isn’t a home.
With these traits in hand, a exact, formal specification may be formulated, aided by further strategies and instruments. From that, the what or when of “X” – the pandemic is over or it isn’t – would logically comply with. If it doesn’t, at the least it will likely be doable to clarify why issues should not that easy.
This kind of precision enhances well being consultants’ efforts, serving to people to be extra exact and talk extra exactly. It forces us to make implicit assumptions express and clarifies the place disagreements could also be.
Definitions and diagrams
I conducted an ontological analysis of “pandemic”. First, I wanted to seek out definitions of a pandemic.
Informally, an epidemic is an prevalence throughout which there are a number of cases of an infectious illness in organisms, for a restricted period of time, that impacts a group of stated organisms dwelling in some area. A pandemic, at the least, extends the area the place the infections happen.
Subsequent, I drew from current foundational ontologies. This accommodates generic classes like “object”, “course of”, and “high quality”. I additionally used area ontologies, which include entities particular to a topic area, like infectious ailments. Amongst different assets, I consulted the Infectious Disease Ontology and the Descriptive Ontology for Linguistic and Cognitive Engineering.
First, I aligned “pandemic” to a foundational ontology, utilizing a decision diagram to simplify the method. This helped to work out what sort of thing and generic category “pandemic” is:
(1) Is [pandemic] one thing that’s taking place or occurring? Sure (perdurant, i.e., one thing that unfolds in time, relatively than be wholly current).
(2) Can you be current or take part in [a pandemic]? Sure (occasion).
(3) Is [a pandemic] atomic, i.e., has no subdivisions and has a particular endpoint? No (accomplishment).
The phrase “accomplishment” could appear unusual right here. However, on this context, it makes clear {that a} pandemic is a temporal entity with a restricted lifespan and can evolve – that’s, cease to be a pandemic and evolve back to epidemic, as indicated on this diagram.
Traits
Subsequent, I examined a pandemic’s traits described within the literature. A complete listing is described in a paper by US infectious illness specialists revealed in 2009 throughout the world H1N1 influenza virus outbreak. They collated eight traits of a pandemic.
I listed them and assessed them from an ontological perspective:
- Broad geographic extension. That is an imprecise function – be it fuzzy within the mathematical sense or estimated by different means: there isn’t a crisp threshold when “large” begins or ends.
- Illness motion: there’s transmission from place to position and that may be traced. A sure/no attribute, nevertheless it may very well be made categorical or with ranges of how slowly or quick it strikes.
- Excessive assault charges and explosiveness, or: many individuals are affected in a short while span. Many, quick, quick – all point out imprecision.
- Minimal inhabitants immunity: immunity is relative. You have got it to a level to some or all the variants of the infectious agent, and likewise for the inhabitants. That is an inherently fuzzy function.
- Novelty: A sure/no function, however one may add “partial”.
- Infectiousness: it have to be infectious (excluding non-infectious issues, like weight problems), so a transparent sure/no.
- Contagiousness: this can be from individual to individual or by means of another medium. This property consists of human-to-human, human-animal middleman (e.g., fleas, rats), and human-environment (notably: water, as with cholera), and their attendant points.
- Severity: Traditionally, the time period “pandemic” has been utilized extra usually for extreme ailments or these with excessive fatality charges (e.g., HIV/AIDS) than for milder ones. This has some subjectivity, and thus could also be fuzzy.
Properties with imprecise boundaries annoy epidemiologists as a result of they could result in different outcomes of their prediction models. However from my ontologist’s viewpoint, we’re getting someplace with these properties. From the computational facet, automated reasoning with fuzzy features is feasible.
COVID, at the least early in 2020, simply ticked all eight packing containers. A suitably automated reasoner would have categorized that scenario as a pandemic. However now, in early 2022? Severity (level 8) has largely decreased and immunity (level 4) has risen. Level 5 – are there worse variants of concern to come back – is the million-dollar query. Extra ontological evaluation is required.
Highlighting the difficulties
Ontologically talking, then, a pandemic is an occasion (“accomplishment”) that unfolds in time. To be categorized as a pandemic, there are a selection of options that aren’t all crisp and for which the imprecise boundaries haven’t all been set. Conversely, it implies that classifying the occasion as “not a pandemic” is simply as imprecise.
This isn’t a full reply as to what a pandemic is ontologically, nevertheless it does make clear the difficulties of calling it “over” – and illustrates nicely that there will likely be disagreement about it.
This text by Maria Keet, Affiliate professor in Pc Science, University of Cape Town is republished from The Conversation beneath a Inventive Commons license. Learn the original article.
