
A report from the Academy of Medical Royal Colleges in the U.K. is calling on healthcare providers to take urgent action on infection control and personal protective equipment (PPE) to prepare for COVID-19 surges in winter 2020.
The document, called "Preparing for COVID-19 surges and winter" and backed by the Royal College of Radiologists, particularly emphasizes ensuring the availability of PPE to control infection from SARS-CoV-2.
The document proposes the following local and regional actions:
- Establish clear integrated primary care arrangements, including best use of space as defined by patients' COVID-19 status.
- Establish a clear plan for dealing with hospital outbreaks of SARS-CoV-2 infection.
It also proposes the following national actions:
- Continue to purchase PPE so that it is available to the National Health Service (NHS) network.
- Ensure PPE guidance is current.
- Provide adequate beds for COVID-19 care, whether in the hospital or in secondary settings.
- Communicate infection control measures clearly to the public.
"One of the significant concerns in the first phase of the pandemic was over the lack of availability of PPE," the authors noted. "Managing this and ensuring effective wider infection control is an essential part of preparations for winter and further surges."












![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)




