Sussex Scientists Give Away New Covid Rate Prediction Method

A team working with The Brighton And Sussex Medical School has developed a new mathematical method to predict Covid's impact at a local level with 'unprecedented' accuracy.

This has been made freely available for other local authorities to use online — at a time when a further wave of infections is troubling many areas, especially, in Sussex alone, the city of Brighton and Hove, and Hastings.

The study used data from local Sussex hospitals and daily Covid-19 situation reports, including admissions, discharges, bed occupancy and deaths. 

Through the pandemic, the newly published modelling has been used by local NHS and public health services to predict infection levels so that public services can plan when and how to allocate health resources.

Within the bounds of scientific acceptability, it has been conclusively shown to be accurate.

The medical school said the team is now making its modelling available to other local authorities to use.

Professor Anjum Memon, Chair in Epidemiology and Public Health Medicine at BSMS, co-authored the study.

He said:

“The world is on the cusp of experiencing local and regional hotspots and spikes of Covid-19 infections.

"Our epidemiological model, which is based on local data, can be used by all local authorities in the UK and other countries to inform healthcare demand and capacity, emergency planning and response to the supply of medications and oxygen, formulation, tightening or lifting of legal restrictions and implementation of preventive measures.” 

“The model will also serve as an excellent tool to monitor the situation after the legal Covid-19 restrictions are lifted in England on 19 July, and during winter months with competing respiratory infections."

Anotida Madzvamuse, Professor of Mathematical and Computational Biology at the University of Sussex and leader of the study, added:

“We undertook this study as a rapid response to the Covid-19 pandemic.

"Our objective was to provide support and enhance the capability of local NHS and Public Health teams to accurately predict and forecast the impact of local outbreaks to guide healthcare demand and capacity, policy making, and public health decisions.” 

“I'm really pleased that our modelling has been of such value to local health services and people.

"The modelling approach can be used by local authorities to predict the dynamics of other conditions such as winter flu and mental health problems".

This study was supported by the Higher Education Innovation Fund (University of Sussex); Global Challenges Research Fund (Engineering and Physical Sciences Research Council); UK-Africa Postgraduate Advanced Study Institute in Mathematical Sciences; Wellcome Trust; Health Foundation; the NIHR; and Dr Perry James (Jim) Browne Research Centre on Mathematics and its Applications (University of Sussex).  

The full article is published in International Journal of Epidemiology, and is available for other local authorities to use online.