COVID-19 and a lack of PPEs

Andreas Voss (@AVIPNL) Uncategorized

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By Andreas Voss, Jan Kluytmans and Alexander Friedrich

As the surge of COVID-19 cases is hitting some of the Dutch hospitals hard, healthcare, in the areas being overwhelmed with cases, experience a shortage of PPEs and especially masks. In other Dutch regions with no or only a few cases, colleagues still believe that life is normal and PPEs can be ordered with a click on the computer. They look with awe at what colleagues in the midst of battling COVID-19 and shortages are facing. In addition, all healthcare-settings that do not usually use a lot of PPE’s (e.g. nursing homes and GPs), will be heavily understocked.

Still, infection control advice seems to be based on standard, safety-maximized procedures, thereby wasting valuable resources. As a consequence, HCWs in the Netherlands are still following these recommendations, by using FFP masks routinely, in low risk situations, while they should be saved for the high-risk procedures.

We believe that it is time to rethink our protocols, based on the fact that we still assume that COVID-19, in general, is based on droplet and contact transmission.

  1. Restricted and risk-based use of FFP masks
  2. Use of surgical masks for normal care of COVID patients
  3. Efficient and extended use of FFP masks and other PPEs
  4. Re-use of FFP masks

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COVID-19: hello social distancing

Jon Otter (@jonotter) COVID-19 , , , ,

The UK government yesterday announced a far-reaching package of social distancing measures to suppress the spread of COVID-19. These are based on some Imperial College London modelling work, published here. The model predicts that the UK approach to mitigate the impact of the UK epidemic would indeed reduce the overall number of people affected and those who die, but would still leave hundreds of thousands dead in an overwhelmed healthcare system. In contrast, a more intensive suppression approach would be effective in reversing the epidemic trend and keep the number of new cases to a low level – in the short term, at least.

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Considering the role of environmental contamination in the spread of COVID-19

Jon Otter (@jonotter) COVID-19 , , , , , , , , ,

We know that respiratory viruses can be spread through droplets, occasionally aerosols, and contact routes (see Figure 1). But what is the relative importance of these transmission routes for the SARS-CoV-2 virus, which causes COVID-19? A new pre-print paper published yesterday provides evidence that the stability of the SARS-CoV-2 coronavirus is broadly comparable to the ‘original’ SARS coronavirus (SARS-CoV-1) on dry surfaces and in aerosols. This paper supports an important role for dry surface contamination and aerosols in the spread of SARS-CoV-2, and suggests that improved environmental persistence isn’t the key to the relative success of SARS-CoV-2 over SARS-CoV-1.

Figure 1: Transmission routes of respiratory viruses (from this review article).

covid transmission routes

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Update on COVID-19: part 14, the changing picture

marcbonten Uncategorized

Where the world is gradually (or instantaneously) facing the COVID-19 reality, China claims victory. Yet, it ain’t over till it’s over, and many fear a rebound once daily life has returned to its normal practices and contact patterns. In the meantime our Chinese colleagues keep on producing very impressive epidemiological studies. Such as this one, published today. Continue reading →

Developing antimicrobial “smart surfaces” to tackle HCAI and AMR

Jon Otter (@jonotter) Antimicrobial surfaces , , , ,

I participated in a launch event by the Institute of Molecular Science and Engineering (IMSE) at Imperial College London yesterday for a new white paper on developing “smart surfaces” to tackle HCAI and AMR.

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Using machine learning to super-charge anti-infective drug discovery: the case of Halicin

Jon Otter (@jonotter) Antibiotic resistance , , , ,

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Yes, it’s true. There is more to HCAI & AMR (and this blog) than COVID-19! To prove it, I’m posting on something different today – the use of AI to streamline the anti-infective drug discovery process. Scientists at MIT have used machine learning (aka “deep learning”) to improve the drug discovery process, by predicting antimicrobial activity in molecules that are different from known antibiotics. This process has yielded Halicin, a promising candidate molecule for a broad-spectrum antimicrobial agent – which is, of course, a long way from clinical trials!

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