Why is there so much data?
Numerous mathematical models have been produced to predict the behavior of the new coronavirus, COVID-19. With new data coming in everyday and health professionals getting a deeper understanding of the disease, our models are becoming more accurate. However, if this is the case then why is mass media sharing a new estimated death count every week? Why was the world going to run out of hospital space and then suddenly didn't?
It is because these mathematical models are not clairvoyant. Scientists can only guess how the future will turn out, and we update those models accordingly. With such a rapidly changing virus, our models are changing just as fast.
Too many numbers?
If you watch or read the news it is almost impossible to miss the latest COVID-19 prediction. There is a new death toll and infection forecast almost every day; some sites are updating infection and death rates every minute. When the virus was new to our country, one estimate claimed almost 500,000 deaths in the US alone. The White House coronavirus task force estimated between 100,000-250,000. More recent forecasts suggest 50,000-100,000 deaths. These numbers can confuse the public and cause unnecessary anxiety. To understand why there are conflicting models and new ones published every week, we have to understand what parameters go into making a model to predict something that is so unpredictable.
Behind the Models
Statisticians estimate things all the time. They attempt to guess everything from the incidence rate of a disease to how many people buy ice cream in the summer. These data points are filtered into models. They make models that try to solve real-world problems in business, engineering, healthcare, and more. It is important to note that some are more accurate than others. This is because of what they are testing. In the COVID-19 case, they would estimate how fast the disease will spread in different demographics, what age groups gets affected the most, how long does it last, whether social distancing actually works. These are all things that statisticians and scientists alike are trying to guess.
This is a very difficult task in our case because the United States is huge. The US is one of the most populated countries in the world, with a wide variety of population density, age, race, climate, and other parameters that go into these models. Moreover, unlike countries with a dictatorship rule, the US values freedom of choice and movement, leaving no real enforceable stay-at-home orders. With such a diverse population pool and degrees of freedom, no wonder it is so hard to get an accurate count of how this virus will behave.
Should you trust these models?
A little bit. That's the short answer. Models are extremely important for governments to assess the readiness of their healthcare systems and introduce new policies for pandemics. However, we do know that these models cannot be 100% accurate given the diverse range of data present, especially in the US. Mass media must be cautious before praising some models as gospel. We have seen the estimated death tolls slowly decrease which should provide everyone with some solace.
Jewell, Nicholas P. “Predictive Mathematical Models of the COVID-19 Pandemic.” 2020 American Medical Association , 16 Apr. 2020.