Mention the word “virus” to most of us during the past 10 years and we would have replied “computer”. We have lived through WannaCry, CryptoLocker, ILoveYou and MyDoom – and learnt to associate the concept of a virus with the digital and data driven world we now live in.
No matter how crippling computer viruses have been, none have proved anything like as damaging and scary as COVID-19.
The biological world has now reclaimed the word “virus” for its own and it has even become synonymous with COVID-19. The irony is that while the world of IT may have lost ownership of the term, it is at the forefront of fight to combat the virus.
The effectiveness of the response to a COVID-19 outbreak is also dependent on the quality of the data. Macro data has led European countries to the conclusion that only social distancing and home isolation will combat the spread of the virus, while in Singapore the use of contact tracking has proved highly productive in containment.
In countries such as the US where there is no national health service, obtaining clear data on the state of the epidemic is much harder and further challenged by the 25% of the population who do not have healthcare and are unlikely to present with symptoms.
In every country though, all the measures we see going into place today - from social distancing, transport restrictions, to self-isolation - are based on the computational models used to forecast the spread of the disease. Data is driving the decisions and for the first time in history, medical science and computer science are becoming indistinguishable.
In a recent announcement, IBM announced that it would be devoting 330 petaflops of compute power to various projects in epidemiology, bioinformatics and molecular modelling. Google, Microsoft and Amazon are also donating resources to the cause. What these IT giants can provide is a massive acceleration in the analysis of the epidemiological data and the development of potential treatments and vaccines.
This confluence of medical and computer science could go much further though; our approach to a virus outbreak like COVID-19 is to first measure its transmission and fatality rates, and then study measures for how to combat the disease. All of these are reacting to circumstance and trying to deliver empirical solutions.
In what is sometimes termed “rational medicine” a different scientific approach is being pioneered that would take a fully informed, knowledge-based approach to disease.
Rather than chasing the pandemic with empirical based remedies, the belief of rational medicine is that the entire route of a virus can be anticipated, modelled and prevented before the virus even comes into existence.
The basis of the claim is that with around 100,000 proteins in the human body (the number is debatable and also varies by person and age), the mechanism for how a virus can gain access could be anticipated and stopped.
COVID-19, for example, is an intracellular parasite that tricks its way into the ACE2 protein and then can replicate at will until antibodies come along. Since ACE2 is there to regulate blood pressure by constricting blood vessels, it causes coughing as the blood vessels in the lungs are affected and is also particularly dangerous to anyone on blood pressure medication as this leads to an increase in ACE2.
What rational medicine advocates is the change from medicine as a therapy to medicine as a science. This would mean the mapping of every protein in the human body, and the modelling of how a virus might attack and gain access. The approach of simulating the attack could be done in silico and then used to construct vaccines that would produce the antibodies to protect against the potential invasion.
Put simply, we could be taking measures to protect against virus threat vectors that do not exist today and may never exist – much in the same way that we protect IT networks against potential as yet unleashed threat vectors. Which all seems highly appropriate given that COVID-19 has been described as a molecular phishing scam.