The spatio-temporal distribution of COVID-19 infection in England between January and June 2020.

ABSTRACT: The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary g

SUBMITTER: Elson R 

PROVIDER: S-EPMC7985908 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature