Worldwide, travel bans have been implemented to try and stem the tide of COVID-19 coronavirus. Here in the US, Democrat lawmakers heaped scorn on President Trump for his travel bans, calling them racist and xenophobic. Now, a Stanford University study says they have saved millions from infection and death.
When President Trump imposed a ban on travel from China on January 31, 2020, Democrat Presidential candidate Joe Biden called it “racist and xenophobic.” Several weeks later, Biden said the ban didn’t go far enough.
When President Trump banned travel from Europe on March 11, 2020, the same predictable group of people got worked up again, claiming travel bans don’t work. In fact that became the talking point of just about every news media outlet across the American landscape. They rolled out “expert” after “expert” to tell us that closing the borders wouldn’t slow the spread of COVID-19.
In other words, the logic was that preventing the flow of people whose recent whereabouts and contacts couldn’t possibly be known, and whose exposure to COVID-19 was a guessing game, into the US wouldn’t make it easier to control the virus here in the USA. Let that sink in for a minute. The very thought defies logic in ways that should make your head hurt. But that was the position of the breathless hair hats in the media, as well as the many of the geniuses over in Congress. They even claimed to have “science” to back it up. They didn’t.
In Europe, travel bans became almost a routine move on the part of governments who were serious about reducing the effect of the pandemic on their citizens. Virtually every nation in the EU imposed travel bans from China and other places where the virus was spreading. For the anti-travel ban crowd in the US, this was barely noticed.
But now, science has spoken and the hair hats should shut it. A new report by the computer modeling experts at Stanford University shows that, if travel bans had not been implemented, millions more people would have been infected. In case you’ve forgotten, the Stanford folks are the ones who first pointed out that the Institute for Health Metrics and Evaluation (IHME) model was flawed and far overestimated US COVID-19 hospitalizations and deaths. The IHME model created the panic-driven response to the virus that we’ve seen in the US.
This new study was published in Computer Methods in Biomechanics and Biomedical Engineering. It uses a freshly developed mathematical epidemiology simulation to predict the massive and positive impact on the spread of SARS-CoV-2 which resulted from air travel limitations imposed across the 27 EU nations.
As important, this simulation can provide immediate estimates of how the virus would spread in each country if the travel bans were ended today. The picture shown above reflect the spread of COVID-19 both with and without air travel bans. The dates represented are March 23, April 6 and April 20, from left to right.
Using this model, politicians and public health officials can virtually lift their travel bans between various countries and see the resultant change in the spread of the virus. That means this model can provide logical support for deciding if and when to lift travel bans while still limiting the spread of COVID-19.
“There is a well-reasoned fear that easing of current (travel restriction) measures, even slightly, could trigger a new outbreak and accelerate the spread to an unmanageable degree,” lead author Ellen Kuhl, Professor of Mechanical Engineering at Standford University comments.
“Global network mobility models, combined with local epidemiology models, can provide valuable insight into different exit strategies. Our results demonstrate that mathematical modelling can provide guidelines for political decision making with the ultimate goal to gradually return to normal while keeping the rate of new COVID-19 infections steady and manageable,” says Kevin Linka, lead author and postdoctoral researcher in Dr. Kuhl’s group.
When the SARS-CoV-2 virus began spreading out of Italy, countries which were less connected to the rest of Europe like Slovenia, Slovakia and Estonia saw it reach them later and with a less forceful impact. Well-connected countries like France, Spain and Germany saw a rapid viral spread.
Currently the levels of population known to be infected with the disease varies from country to country, however as of April 18, with flight being reduced by 89% in Germany, 93% in France, 94% in Italy, and 95% in Spain (Eurostat 2020), the graphs in this study show how the spread has been contained.
“Strikingly, our results suggest that the emerging pattern of the COVID-19 outbreak closely followed global mobility patterns of air passenger travel,” confirms Professor Kuhl, whose model can also predict the emerging global diffusion pattern of a pandemic at the early stages of the outbreak.
“Our results suggest that an unconstrained mobility would have significantly accelerated the spreading of COVID-19, especially in Central Europe, Spain, and France.”
The model also confirms a painful truth. The travel bans could possibly have helped stop or minimize the outbreak across Europe if they had been imposed earlier.
“A recent study based on a global metapopulation disease transmission model for the COVID-19 outbreak in China has shown that the Wuhan travel ban essentially came too late, at a point where most Chinese cities had already received many infected travellers (Chinazzi et al. 2020). Our study shows a similar trend for Europe, where travel restrictions were only implemented a week after every country had reported cases of COVID-19 (European Centre for Disease Prevention and Control 2020).
“As a natural consequence, unfortunately, no European country was protected from the outbreak,” Professor Kuhl, who is the Robert Bosch Chair of Mechanical Engineering at Standford added.
France reported Europe’s first official case of COVID-19 on January 24, 2020. Three and five days later, respectively, Germany and Finland reported cases as well. It only took six weeks for every European Union nation to have active cases. The last holdout nations were Cyprus, Malta and Bulgaria, reporting cases on March 9, 2020. By that time, the case count was doubling every three to four days and Europe had over 13,900 cases, according to the European Centre for Disease Prevention and Control.
Dr. Kuhl adds that although air travel is certainly not the only determinant of the outbreak dynamics, their findings indicate that “mobility is a strong contributor to the global spreading of COVID-19”. This is becoming especially important now that many countries are beginning to lift their travel restrictions in an attempt to gradually return to normal.
Like any infectious disease model, this one has its limitations. The biggest of these is the variables and data uncertainties of testing differences. Incomplete counting, inconsistent diagnostics and delays in reporting across all nations are also issues. All that said, the Stanford group has had a better track record predicting cases, hospitalizations and deaths than almost any other modeling group.
There are a lot of questions about preparation for and handling of this coronavirus by public health officials and government agencies. We’ve listened some people who have questions to answer about what they told us they knew and what they told us to do. We’ve made some hard decisions using data and models that turned out to be far afield.
But it turns out that travel bans, in spite of what the media and the usual characters in the “establishment” had to say about them, actually worked! In fact, millions of people are probably alive and well right now because of them. Whichever side of all of this you come down on, that should be good news. If you don’t think so, I’m a little concerned about your logic.
Keep the faith and keep after it!
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Journal Reference – https://www.tandfonline.com/doi/full/10.1080/10255842.2020.1759560