Geospatial digital monitoring of COVID-19 cases
SARS-CoV-2 disseminates via close contact during daily activities, forming clusters of cases. A crucial challenge to contain the spread lies in the early detection of these outbreak clusters by means of geospatial tools and statistics
The pooling of medical, epidemiological (Unit of Population Epidemiology, Geneva University Hospitals - HUG) and geospatial (LASIG, EPFL) skills within the GIRAPH Lab made it possible to analyze the spatiotemporal diffusion dynamics of SARS-CoV-2 clustering, based on RT-PCR test results of 2877 georeferenced, confirmed positive cases among 12 918 individuals tested in the canton of Geneva, Switzerland, between Feb 26 and April 16, 2020 (51 days). This research was published today in The Lancet Digital Health.
The Virology Laboratory at HUG, as the reference laboratory for the canton of Geneva, did the tests and provided anonymised data. We used the address of residence of individuals testing positive for SARS-CoV-2 and disease spatial clustering techniques (modified space–time density-based spatial clustering of applications with noise algorithm) to highlight the diffusion dynamics. A video shows the daily clustering dynamics of the 2877 COVID-19 confirmed cases and gradually characterises the respective behaviour of clusters (eg, emergence and reduction).
Such an ongoing description of the geographical clustering of positive cases across space and time combined with an effective testing strategy has potential to 1) inform on the origin of the disease outbreak by identifying the first emerging clusters; 2) rapidly identify current spreading zones; and 3) enable accurate prevention and containment measures and timely resource allocation to mitigate any re-emergence of the epidemic.