Real-time surveillance of covid-19 using routinely collected data [COVID-19]
Research type
Research Study
Full title
Real-time surveillance of covid-19 using routinely collected spatially-referenced and time-stamped data
IRAS ID
288478
Contact name
Samuel I Watson
Contact email
Sponsor organisation
University of Birmingham
Duration of Study in the UK
0 years, 3 months, 0 days
Research summary
The Covid-19 pandemic has a long course to run. While the “first wave” of infections has passed in many high-income countries, intense surveillance will be required to target public health policy to prevent resurgences in infections. Governments and other international agencies will want to understand how the pandemic evolves over time and space. The spatial and temporal scales over which increases in cases occur can inform bespoke and localised containment policies. The evaluation of these changes in real-time can therefore provide an invaluable tool for public health. In the absence of continuous population screening and testing, routine data sources exist that can provide input on the nature of cases in the population, particularly from health systems.
The aim of this project is to build a software tool for the real-time surveillance of covid-19 that applies geostatistical methods to routine health system data to make reliable predictions of the incidence and geographic spread of cases.
REC name
London - Bloomsbury Research Ethics Committee
REC reference
20/HRA/4250
Date of REC Opinion
14 Sep 2020
REC opinion
Further Information Favourable Opinion