Drawing on work developing a universal law to discern patterns in coincidences, Luczak-Roesch is mapping the pandemic in real-time from the genetic similarities of the virus found in patients across the country and around the world.
Using an approach called Transcendental Information Cascades, he and his team are analysing the data as a network of chronologically ordered cases, with the strength of connections between cases reflecting the similarity of the virus’ genetic code that was isolated from the respective patients.
In contrast to conventional tools such as phylogenetic trees, Luczak-Roesch’s method enables further layers of information to be added in order to link analyses that would usually be done independently. Symptoms that Covid-19 patients experienced, and even sleep patterns, are examples of additional information that can help link cases and map the outbreak.
“A lot of that data is available these days, as people make use of tools such as smart watches to monitor their daily activities and sleep,” says Luczak-Roesch.
“When patients make that data available to the contact tracing teams, it may contain essential information about how cases are similar and therefore may be of the same origin.”
The result is a model linking previously unconnected cases, and a unique tool that can be used by epidemiologists and others involved in the response “to support the forensic work about where and when a patient who contracted the virus from an unknown source may have been in contact with another infected person”.
“This tool can be used to map pathways of the virus’ spread that may not be visible from what we know about the places the patients reported to have visited,” says Luczak-Roesch.
To keep up with the swiftly changing landscape of the crisis, Luczak-Roesch and his team at the Complexity & Connection Science Lab continuously update their analysis as new samples are made available. Results are then shared with the Institute of Environmental Science and Research (ESR) to collate with work by other researchers and provide the National Crisis Management Centre with a detailed picture of the virus’s prevalance in New Zealand.
"It’s an almost daily process that provides epidemiologists and others with a live model of how and where the disease is spreading.
“It complements conventional methods, and could become part of the standard toolbox when trying to understand epidemic disease outbreaks in near real-time and with patchy data.”
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