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The spatio-temporal distribution of COVID-19 infection in England between January and June 2020.
Elson, Richard; Davies, Tilman M; Lake, Iain R; Vivancos, Roberto; Blomquist, Paula B; Charlett, Andre; Dabrera, Gavin.
  • Elson R; National Infection Service, Public Health England, London, UK.
  • Davies TM; National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Gastrointestinal Infections, Liverpool, UK.
  • Lake IR; School of Environmental Sciences, University of East Anglia, Norwich, UK.
  • Vivancos R; Department of Mathematics & Statistics, University of Otago, Dunedin, New Zealand.
  • Blomquist PB; School of Environmental Sciences, University of East Anglia, Norwich, UK.
  • Charlett A; National Infection Service, Public Health England, London, UK.
  • Dabrera G; National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Gastrointestinal Infections, Liverpool, UK.
Epidemiol Infect ; 149: e73, 2021 03 08.
Article in English | MEDLINE | ID: covidwho-1145031
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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 geographical boundaries, to produce a continuous estimate of spatially varying risk.Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first 6 months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on 23 March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.In terms of controlling transmission, the most important practical application of our results is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Time Factors / COVID-19 Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: Epidemiol Infect Journal subject: Communicable Diseases / Epidemiology Year: 2021 Document Type: Article Affiliation country: S0950268821000534

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Time Factors / COVID-19 Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: Epidemiol Infect Journal subject: Communicable Diseases / Epidemiology Year: 2021 Document Type: Article Affiliation country: S0950268821000534