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Out of Context COVID Stats are Misleading

Since the start of the pandemic, public health authorities have been fastidiously counting the number of people infected with the coronavirus. For both the medical profession and the media, these rising figures have been the principal way of framing the pandemic in the U.S.: “124,000 new cases a day,” “802,000 COVID deaths since February 2020.” But this information offers an incomplete picture of the crisis, potentially warping the public’s understanding in ways that could prolong the pandemic and even add to its toll.

What’s missing from the day-to-day conversation is the number of uninfected people and the number of infected people who survive COVID-19. That provides a denominator to put the other figures in context. If there were 124,000 new infections per day, how many people were exposed? If 802,000 people died from COVID, how many were infected but didn’t die?

Indeed, such information is the most underreported story of the pandemic. But it has long been an important piece of public health information. It advances our understanding of the nature of the disease; it hints at the power of precautions such as masks and vaccines; and it can allay fears and trauma that people are experiencing about the seemingly never-ending nature of the pandemic.

Our reliance on numbers to understand epidemics can be traced to the development of epidemiology — when medical and scientific authorities had not yet uncovered how microbes caused the spread of infectious disease. Between 1755 and 1866, when epidemiology emerged, medical practitioners believed that environmental factors caused disease. Based on this inaccurate view, they had few effective metrics to understand the origins of epidemics. As such, they counted the number of uninfected and infected patients; the number who contracted a disease and the number who died; they examined those who were hospitalized and those released.

Counting was a way to rationalize infectious disease and to create a narrative about it. For example, during the Crimean War in the 1850s, the nurse and statistician Florence Nightingale witnessed that more British soldiers died once they were admitted to the hospital, but she couldn’t see the germs that were infecting them. What she could see, she counted: the number of healthy and the number of sick soldiers, inside and outside hospitals. By creating a clear analytical assessment, she then observed how the unsanitary conditions within hospitals correlated with alarming mortality rates. According to Nightingale, a “complete system of sanitary statistics in the army” was necessary “to administer the laws of health with that certainty.”

Statistics, and exploring the behaviors behind them, became a key component in epidemiological analysis because that’s all that health experts had — and it helped them craft treatment strategies.

Read entire article at Los Angeles Times