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Forecasting Covid-19 cases to help the NHS

Last updated

30/04/20

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Ashleigh Myall, a PhD student on our National PhD Training Programme in AMR Research, is using mathematical modelling to help Imperial College Healthcare NHS Trust forecast and prepare for incoming patients with COVID-19. In a new blog post, he describes the experience so far.

It’s been 4 months since the first case of pneumonia from an unknown cause was reported to the WHO China Office.

First detected in the city of Wuhan in Hubei province, this was the start of a pandemic caused by a novel coronavirus disease, later labelled as Covid-19. Since then a wave of Covid-19 has swept over the world, leaving few countries untouched, and hitting European countries especially hard, including here in the UK.

Although hospitalisation rates are relatively low, Covid-19’s ease of spread makes it especially challenging for modern healthcare systems. Not designed to cope with such large waves of patients requiring hospitalisation and intensive care, many health systems are beginning to feel the strain.

At the forefront of this fight in the UK are our NHS healthcare workers who are doing phenomenal work even when lacking essential resources. However, just behind this frontline are computer modellers glued to computer screens, trying to offer glimpses into the future. These insights are essential for planning and without them, many hospitals would likely be unprepared and overrun with Covid-19 infected patients.

I first heard about Covid-19 in January while, coincidentally, sitting in on a meeting with ProMED (the International Society for Infectious Diseases) aimed at developing tools to detect emerging infectious disease; and three weeks ago I joined the epidemiology team in Imperial’s NHS trust to help fight this Covid-19 pandemic. Now, I’m joining daily conference calls from quarantine in my countryside home.

As part of this group of mathematicians, epidemiologists, and doctors, I’ve been working to forecast one- and two-week pictures of what the likely scenarios will be for Imperial’s NHS Trust. Combining Imperial’s own Covid-19 patient numbers with data taken from published research on length of stays and mortality rates, we’re able to specifically forecast demand for beds. Now we’re also beginning to incorporate techniques aimed at picking up on the constantly changing number of cases - investigating the slow down as we reach the ‘peak’.

It’s essential to tailor these forecasts to specific hospitals and bring in experts that understand both the mathematical models and the operational needs of each hospital, as the picture of COVID-19 across the UK can vary hugely.

Working alongside the NHS in this pandemic situation has highlighted the need for interdisciplinary teams, linking experts key in the fight against infectious disease. It’s amazing being in this maths-epi-operations team where we’re all building off each other’s strengths. I hope coming out of this, we are all pushed to incorporate more interdisciplinary teams into the world of pandemic response.

I’m grateful to the Medical Research Foundation for enabling me to help the NHS whilst I’m studying on their PhD programme. With all the skills I’m learning in and around infectious disease modelling, I’m keen to see just how I can use them for fighting antimicrobial resistance, once this initial Covid-19 outbreak is behind us.

Ashleigh Myall – Centre of Mathematics for Precision Healthcare, Imperial College London.

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