Feature: Researchers explore the possibility of using geostatistics to track COVID-19 transmission hot spots

A decades-old method called geostatistics, used by miners to determine where to dig for gold, could be used to help understand emerging hot spots in the COVID-19 pandemic.

The method uses a small number of data points in order to reconstruct a complex situation or environment. Peter Rogan, PhD, Professor in the Departments of Biochemistry and Oncology, demonstrated in a recent publication that geostatistical analysis could be accurately used to pinpoint the location of a radiation plume in the event of a nuclear accident.

Rogan and his team modelled 30 scenarios under various weather conditions, and determined that geostatistical analysis could expedite triaging of acute radiation exposure during nuclear events.

“The paper uses geostatistics to derive a radiation plume from a very limited number of samples,” Rogan said. “While this paper isn’t about COVID-19, the methods we describe could be used for late stage epidemiology in the current pandemic. It could fill a gap in assessment after community transmission, when patient tracking is no longer an effective mitigation strategy to identify sources of infection transmission.”

The idea is to estimate the amount of exposure at locations that have not been tested using results from locations or individuals close by. Initially, the researchers randomly test individuals or locations and create a rough map of exposures. They then choose locations for a subsequent round of sampling by first responders based on the level of confidence in these estimates in the previous round. After several rounds of sampling, the radiation map is no longer improved by adding more samples.

“We believe this could be useful for monitoring COVID-19 for potential resurgence of viral transmission after most individuals have recovered and thought to be non-infectious,” he said. “In such instances, we expect that new infections will emerge in a neighborhood or region where the virus is otherwise under control. It may not be possible to trace the origins of the infections to specific sources, but geostatistical analysis may point to the likely locations that may be the source of these hotspots.”

Rogan uses the example of a New York City subway station as a transmission source of COVID-19. Individuals who present with the virus may live in different neighborhoods surrounding the station and present at different hospitals or community clinics.

“It may not be obvious to epidemiologists that they all passed through the same station. However, if we had a geostatistically-derived map based on likely positive, or positive test results for COVID-19 for that neighborhood that is updated over time, it could be used to monitor for locations of hot spots where viral transmission has occurred.”

Rogan says in theory the location of the subway station could be inferred from the locations of newly diagnosed individuals in the adjacent neighborhoods.

The paper, “Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling,” was published in the journal PLOS one today.