To beat Covid-19, find today’s superspreading ‘Typhoid Marys’
A more informative factor than R is the ‘dispersion parameter’ known as k
by Anjana AhujaIn the early 1880s, Irishwoman Mary Mallon emigrated to New York and began working as a cook. Her meals came with a side order of typhoid: as an asymptomatic carrier of the disease, she infected about 50 people, three of whom died.
That diseases could be spread by the symptomless was not yet known; Typhoid Mary, as she was called, was quarantined for life on North Brother Island, near the Bronx. She is now a historic case study of how individual liberty should be judged against the greater public good when it comes to controlling infectious diseases.
Typhoid Mary is also perhaps history’s most famous superspreader, a person who plays a disproportionate role in spreading a disease. A superspreading trend is evident for Covid-19 too. One preprint of a study, yet to be peer-reviewed, used tracking and tracing data in Hong Kong to estimate that about 80 per cent of local Covid-19 transmission was caused by 20 per cent of infected individuals.
If the pathogen is to be contained, then the analysis of its spread needs to be more granular than simply measuring R, the reproduction number. R is the average number of people a carrier passes the disease to, but is just that: an average.
“The consistent pattern is that the most common number is zero,” professor Jamie Lloyd-Smith, from the University of California, Los Angeles, told the journal Science. “Most people do not transmit.”
A more informative factor than R is the “dispersion parameter”, known as k, which captures how evenly a disease spreads. The higher k is, the more uniform the transmission. The lower k is, the more clustering there is.
Editor’s note
The Financial Times is making key coronavirus coverage free to read to help everyone stay informed.
The Spanish flu of 1918 had an estimated k of 0.94. Severe acute respiratory syndrome, another coronavirus, showed a k of 0.16, indicating significantly more clustering; one Sars hospital patient in Beijing was found to have infected 76 others across four generations of transmission. During one outbreak of Mers, another coronavirus, in South Korea, about 89 per cent of primary cases were found not to have infected anyone else. These cases are known as “dead ends”.
As for today’s pandemic, researchers at the University of Hong Kong used extensive Covid-19 tracing data on the island to come up with an estimate for k of 0.45. That roughly translates into 80 per cent of spread being seeded by 20 per cent of cases. A lower k emerged in April from a peer-reviewed analysis by the London School of Hygiene and Tropical Medicine, attributing 80 per cent of spread to just 10 per cent of cases.
Recommended
Coronavirus: free to read
Coronavirus tracked: has the epidemic peaked near you?
Wherever the true figure lies, Covid-19 is clearly subject to superspreading; the prevalence of dead-ends may also explain why it did not take off everywhere at exactly the same time.
While individual factors boost a person’s chances of becoming a superspreader — such as how much virus they shed — environment matters too. Clusters, the Hong Kong academics found, were more common in social venues, such as bars and music clubs, than at home or work. Large outbreaks have also struck worker dormitories, hospitals, care homes, churches, ships, meatpacking plants and schools.
Knowing that Covid-19 cases spread unevenly is a mixed blessing for the many countries, including the UK, which are still finalising their track and trace systems. They can focus on catching the relatively few events that spread the pandemic coronavirus explosively.
But it also means surveillance systems need to be comprehensive, quick and watertight.
On a good day, missing a case means missing a dead-end. On a bad day, it means failing to stamp out a superspreading event that kick-starts chains of transmission. As countries try to return to normality, there will be little room for bad days.
The writer is a science commentator