Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern (preprint)

ABSTRACT

The SARS-CoV-2 pandemic has been characterized by the repeated emergence of genetically distinct virus variants of increased transmissibility and immune evasion compared to pre-existing lineages. In many countries, their containment required the intervention of public health authorities and the imposition of control measures. While the primary role of testing is to identify infection, target treatment, and limit spread (through isolation and contact tracing), a secondary benefit is in terms of surveillance and the early detection of new variants. Here we study the spatial invasion and early spread of the Alpha, Delta, and Omicron (BA.1 and BA.2) variants in England from September 2020 to February 2022 using the random neighbourhood covering (RaNCover) method, a statistical technique for the detection of aberrations in spatial point processes, applied to community PCR (polymerase-chain-reaction) test data where the TaqPath kit provides a proxy measure of the switch between variants. The application of RaNCover method could rapidly detect outbreaks of future SARS-CoV-2 variants of concern and hence inform optimal spatial interventions.