Can disease transmission models predict the 2020 election?

EVANSTON, Ill. — No two things sum up 2020 more than the coronavirus pandemic and the U.S. presidential election. So could virus infection rates end up revealing November’s big winners? A study says if political parties are like “viruses,” then how they influence undecided voters may reveal this year’s electoral map.

Researchers from Northwestern and Augusta Universities, UCLA, and The Ohio State University have taken models which predict how infectious diseases spread across the U.S. and are repurposing them to study how one voter may “infect” or influence another person to vote for their candidate. The model compares decided voters to infected patients and undecided voters to the “susceptible” portion of the population. The two diseases spreading across the country: the Democratic and Republican parties.

“Experts like the team at FiveThirtyEight account for the fact that, if you misidentify how Pennsylvania will vote, then you might also misidentify how Ohio will vote because those states have some similar features,” says Northwestern’s Alexandria Volkening in a university release. “Such symmetric relationships between states are important. Using a disease-transmission model, we also introduce the possibility of asymmetric relationships, or influence. For example, a candidate campaigning in Florida might be featured in the news in Ohio and influence the voters there.”

How does a political ‘virus’ spread across America?

Study authors caution they’re not professional election forecasters, but want to see if information spreads the same way epidemics do.

“My background is not in election forecasting,” Volkening, the study’s lead researcher adds. “But I’m interested in problems in complex systems, where individuals come together to create group dynamics. Mathematical models can be used to describe the behavior of cells in developmental-biology applications and the interactions of voters leading up to elections.”

The study adapted a “susceptible-infected-susceptible” model that typically examines infection rates for illnesses like the flu. Researchers analyzed situations such as when a Republican voter speaking with undecided voters influences them to vote for the GOP. Other scenarios looked at how a campaign event for former Vice President Joe Biden may “infect” undecided voters to vote Democrat.

“In the future, we may be able to tease out how states are influencing each other and pinpoint more influential states,” Volkening explains. “We’d like to explore how interactions among states change over time.”

And the 2020 presidential election winner is…

Using polling data from FiveThirtyEight to play out 10,000 potential outcomes, the results find Democratic candidate Joe Biden wins in 89 percent virus-based electoral maps. President Donald Trump wins reelection in just under 11 percent of infection-based election models.

“It’s been exciting to run the model continuously over time,” says Northwestern sophomore William He. “We don’t just have a single forecast. We update our website regularly, so we can track how opinions are changing.”

While the electoral map looks decidedly favorable for Democrats in 2020, Volkening points out voter turnout could play a big role in flipping the script, just like 2016. “In many states, the margin of victory that we are forecasting for Biden is lower than the percentage of undecided voters,” Volkening concludes. “If undecided voters turn out strongly for Trump, we could certainly see a Republican outcome.”

The study appears in the journal SIAM Review.