HomeResourcesBlogsModelling the infection spread of Covid-19 in the Long Term Care (LTC)...

Modelling the infection spread of Covid-19 in the Long Term Care (LTC) facilities of care homes

During the peak of the first wave of Covid-19, Europe has suffered a large number of care homes’ deaths due to Covid-19 infections.  Several media coverages claimed the death toll could be attributed to governments polices. However, the lack of modelling of the disease infection in these LTC facilities left the interpretation of numbers to speculations. It’s publicly debated that the modelling of the infection spread in several countries, including the UK, didn’t include modelling for care homes. The mathematical modelling of infection spread necessary for this context is admittedly challenging; nevertheless, it’s essential to have to protect the vulnerable care home residents, the care workers and the wider public. This research blog suggests a framework for such a model and addresses some of the challenges involved. In doing so, it starts by explaining how the measuring of infection spread of Covid-19 in enclosed geographical areas like Wuhan and North Italy has been carried out before moving to discuss the more challenging case of care homes model.

Image Credit: QFSW Shutterstock.com

Director of Analytical Research Ltd, and Affiliate Research Fellow, Oxford Institute of Population Ageing, University of Oxford, United Kingdom

Mohamed is trained in engineering (MEng – Cairo University), computer science (MSc – Cairo University) and mathematical finance (MSc – CASS Business School, University of London). Mohamed started his career in in the City of London in 1990s, working as a quantitative analyst for leading global financial organisations, such as Merrill Lynch, HSBC, Mizuho and Credit Suisse, before he began to shift his focus onto quantitative social research. Since 2009, he has worked as an independent researcher in the field of social sciences with a particular drive to make use of different statistical and mathematical modelling techniques for the analysis of large and multi-dispersed data sets.

He has worked with universities in the UK, Europe, Australia and the Middle East; publishing a number of peer-reviewed articles. He has also been invited to give talks and presentations at several leading universities and organisations. His current research interests focus on exploring the potential role of mathematical dynamical systems in the field of population ageing across health and social care. Mohamed is the Director of Analytical Research ltd and an affiliate at the Oxford Institute of Population Ageing, University of Oxford.