It is hard to think that there was a time before the COVID-19 pandemic disrupted all of our lives. Although it seems like an eternity ago, it was only on December 31, 2019, that China reported serious cases of pneumonia to the World Health Organization (WHO). Within days, the cause was identified as a virus, named severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2. It is widely believed that SARS-CoV-2 jumped over to humans from bats either directly or through an intermediate host in late 2019. Since then, lakhs of people have been infected all across the globe; tens of thousands have perished. Our complex, interconnected world has been upended by an invisible virus — a tiny, self-assembling nanoparticle with less than 30,000 nucleotides of genetic information with the simple evolutionary prerogative of making more copies of itself.
People from all walks of life have had their hopes and dreams dashed by SARS-CoV-2. These are doctors, nurses, political leaders, sportspersons and actors, among others. Like many others, since the start of the pandemic, I have consumed with great interest the human stories of those who suffered because of COVID-19. I have seen the photos of doctors with battle-scars from wearing personal protective equipment during exhausting long hours of duty. I’ve heard anguished debates over triage: which critically-ill patients will get access to limited resources like intensive-care-unit beds and ventilators? I’ve seen photos of army trucks lined up to take away the bodies of the deceased. I’ve read the Twitter threads of those who have been hospitalised and the Instagram posts of quarantined celebrities. These stories have filled me with sorrow.
People are not numbers. But in a pandemic, we must also flip the paradigm and think of numbers as people. I believe each of us must not only look at personal individual stories, but at data concerning COVID-19 — how fast it spreads, how many people are infected, who is at risk of suffering the most and of dying — and humanise it. Joseph Stalin is thought to have said, “One death is a tragedy. A million deaths is just a statistic.” During the COVID-19 pandemic, we must negate this assumption. We must give statistics names and faces.
A pandemic is not a single destructive event like a cyclone; it is not a prolonged, but comparatively subdued event like a recession. A pandemic combines the destructive nature of a cyclone with the length of a recession. Actions we take individually have meaningful life-or-death consequences for others. Given the ferocity and speed by which the virus has spread, those of us who are not yet infected also have to consider the implications of SARS-CoV-2 now and in the immediate future. Humanising data helps each of us define parameters of the pandemic and understand the significance of our actions.
If all goes well, the earliest a vaccine might be available for SARS-CoV-2 would be 2021 (and that would be a record of sorts, given that vaccines often take a decade or longer to develop). Developing a drug to cure COVID-19 will also take time, and our best hope right now is that an approved drug for another disease works to contain it. Given these circumstances, and given that there is mounting data that non-pharmaceutical interventions like social distancing and hand-washing slow the spread of SARS-CoV-2, doing so becomes everyone’s responsibility. Relying on data to understand that these approaches are effective is empowering, because it shifts momentum from the virus to us: as humans we have the ability to change our habits.
One of the most effective approaches is to visualise the number of people who are infected over time and see how the curve changes due to interventions, also called “flattening the curve.” The idea here is that if no actions are taken, SARS-CoV-2 spreads unhindered: each infected person infects at least two more and the total number of infected people doubles every two or three days. This doesn’t sound like much until the data is humanised. Now, if I think of it like this: if no actions are taken, one infected person will infect everyone in a city the size of Varanasi in around two months, I have context. I can imagine the toll it will take on the people and the hospitals there and I am more likely to wash my hands and stay at home. My actions help to flatten the curve; SARS-CoV-2 spreads slowly and fewer people are infected at any given time.
Demographic data should also be seen through a human perspective. One of the few silver linings gleaned from the early data from China and the United States is that not as many children suffer from severe COVID-19 as adults do: indeed, there is a correlation between the severity of symptoms and age. Those with heart disease, diabetes, respiratory disease, and high blood pressure also tend to have worse outcomes, including death. The problem is that this has led to a lackadaisical attitude among young adults in many parts of the world.
Unfortunately, while symptoms in young adults may be mild or nonexistent, they can spread it to someone older through their actions and cause severe COVID-19. Here, a 15 per cent death rate among those who are above 80, and an 8 per cent death rate among those who are between 70 and 79 should be seen through a human perspective. Once someone sees the numbers as parents, grandparents, elderly neighbours, and relatives, he or she is more likely to take preventative measures.
Broadly speaking, it is true most of those who are infected will get better. But that is not the entire picture. Even among middle-aged adults, the burden on hospitals can be substantial. Up to 20 per cent of those with COVID-19 might need urgent care. It helps to think in personal terms — thinking of five friends and imagining that one of them becomes so acutely sick in days that he or she needs to be hospitalised, it becomes easier to grasp the seriousness of COVID-19.
Data gives us a picture, but over-reliance on data also has flaws, because it is fluid. With a broader testing of the population for SARS-CoV-2, we will find that more people had mild or no symptoms, and that we probably overestimated the severity of COVID-19. But data with a human face allows us to consider all angles and take action now.
Individual stories are compelling, but we can never really be sure that they are representative. There could be a news story about a 30-year-old who died from COVID-19 right next to one about a person who didn’t feel a thing. Depending on which one we read, we might come to a conclusion about the severity of COVID-19. Data, on the other hand, seems cold and distant. But data that is put into the context of real people is invaluable, and along with individual stories, gives us a clearer perspective on the ongoing pandemic.
(Anirban Mahapatra trained as a scientist and is now tracking the pandemic while maintaining appropriate social distance)
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