The US has seen a surge in its coronavirus cases as a direct result of its quarantine laws, and a few days ago, a new study found that US residents may be better prepared to deal with the pandemics than people in other parts of the world.
However, a paper released this week from the University of Texas at Austin points out that the US is not alone in the way it has dealt with its pandemic.
The study’s authors, Dr. Christopher Harms and Dr. Jules Dufresne, used a new method called the PLD, which is a statistical approach that aims to show whether or not certain variables can influence a model’s results.
They found that when you take away some variables, the model’s predictive ability decreases.
“The question is how can you make it worse?”
Harms said in a statement.
“What you want is a model that is able to predict the likelihood of an event happening, not the likelihood it will happen.”
For example, a model like the one above might be able to correctly predict that the next major pandemic will happen in 2030.
However if the models predictions were wrong in the past decade, then the likelihood for the next pandemic to happen could be as low as 2 percent.
In a follow-up paper, the researchers also found that it can be useful to remove some of the factors that can affect the model.
If the model is predicting a small increase in the risk of contracting the virus, that can be removed.
But Harms added that this method does not necessarily show that the model correctly predicts what the actual risk is going to be.
“If you remove all of these factors, then it becomes a little bit more difficult,” Harms explained.
“So in some cases you may have a model which is able, for example, to predict a 2 percent increase in risk.
In other cases you don’t.”
This means that it is still not clear how the US has managed to reduce its risk of acquiring the virus.
But for now, the data suggests that the country is on track to reduce the number of cases and deaths, and hopefully reduce the spread of the pandems deadly coronaviruses.