The ‘lowhighcovid’ tool is intended to highlight the potential impact of different disease control strategies on the rate of spread of COVID-19. It is designed by the University of Cambridge as an educational tool, and is not intended to be used as a COVID-19 disease management or forecasting tool.
“Our website is intended to demystify infectious disease modelling, and highlight the broad type of model behind government policies for the control of COVID-19,” said Nick Taylor, a PhD researcher in Theoretical and Computational Epidemiology in Cambridge’s Department of Plant Sciences who was involved in developing the tool.
A real-time data feed within the new tool allows users to follow the progress of the current pandemic, and to compare this across different countries. The data feed was designed by Daniel Muthukrishna, a PhD student at the University’s Institute of Astronomy.
Control measures, including social distancing and lockdown, affect the rate at which COVID-19 spreads through a population. The interactive model allows users to see the likely effects of different measures, depending on when they are started and the length of time they are in place.
Users select a country, a control measure, and how long the control is in place. The model then predicts how rapidly coronavirus will spread through the population. It illustrates how various control strategies applied today might impact the number of infections, hospitalisations, ICU bed requirements and deaths.
Explanatory videos, included alongside the interactive model, give users a greater insight into some of the science underlying disease control strategies.
“Biological systems are very complicated, and there are still many uncertainties surrounding COVID-19,” said Dr Cerian Webb, a post-doctoral researcher in the Epidemiology and Modelling Group of the University’s Department of Plant Sciences who provided the videos. “Controlling this disease is a difficult task, and there is no perfect strategy – each has advantages and disadvantages.”