Wayne Gretzky may be an unlikely inspiration for an infectious disease researcher. Yet here Dr. Kamran Khan is, on a demonically busy Monday evening, referencing the Great One.

“Skating to where the puck is going, not where it’s been” — this is Khan’s goal for himself and his colleagues at BlueDot, the company he launched to help decision-makers prepare for and respond to infectious disease outbreaks. Since January, when the Zika virus sent public health officials in Brazil scrambling, Khan has been deluged with requests — everyone from the BBC to the CDC (the U.S. Centers for Disease Control).

Conceived in the wake of Toronto’s 2003 SARS outbreak and launched in 2013, BlueDot, housed at St. Michael’s Hospital’s Li Ka Shing Knowledge Institute, draws on big data to create predictive models of where, when and how an outbreak will spread — not where the puck is, but where it will be.

Sports teams, stock markets, climate science and election campaigns have all been transformed by mathematical modelling. Likewise, infectious disease modelling has become a critical piece in the public-health tool kit, especially during epidemics and emergencies.

But disease modellers grapple with unique disadvantages. “One of our big challenges is really related to data availability,” says Amy Greer, Canada Research Chair in Population Disease Modelling at the University of Guelph.

“We don’t have a satellite circling the earth giving us all the inputs we need,” says Dr. David Fisman, an epidemiologist at the University of Toronto’s Dalla Lana School of Public Health.

In the midst of an outbreak, stricken regions may be unable — or unwilling — to provide information as simple as case counts. Patient confidentiality limits who can see clinical records. And the influence of emotions like fear can be impossible to quantify.

“It’s not obvious that we really know how to model people’s behaviour yet,” says Jonathan Dushoff, an infectious disease modeller at McMaster University. “It can be very unpredictable.”

In late January, the World Health Organization released a headline-grabbing figure: an estimated three to four million people in the Americas will be infected by Zika in the next year. To find that number, WHO researchers used models based on the spread of dengue fever, a related virus transmitted by the same mosquito.

Such predictions are the bread and butter of disease modelling, and rely on concepts established a century ago. Yet even such seemingly basic calculations are notoriously imprecise. In September 2014, the CDC used a model that, accounting for under-reporting and assuming no interventions, predicted a shocking 1.4 million Ebola cases in West Africa in just four months. When the epidemic was finally brought under control a year later, only 28,600 people had been sickened (and 11,300 were dead).

Fisman was also following the Ebola outbreak closely, and developed his own model that, for a time, performed “freakishly” accurately. But at some point in October 2014, it too started to fail: the situation on the ground had begun to diverge from predictions.

“Something (happened) that fundamentally changed the dynamics of this disease system,” Fisman says. But what?

In mid-September, the U.S. announced a major aid package. The same week, villagers in Guinea hacked a group of health-care workers to death. Fear can prompt people to quarantine themselves, or it can prompt them to drive away help. Either way, says Fisman, “that’s awfully hard to measure in real time: how scared are people?”

“Ebola stopped on a dime, and nobody really quite understands why,” says Dushoff, who also studied that epidemic. “It’s a safe bet it was largely driven by a combination of fear and education.”

More complicated models can answer more complicated questions. In May 2015, Khan and his collaborators began noticing reports from Brazil of an unusual viral infection. BlueDot was founded to provide timely information to decision-makers, so instead of reacting as the crisis developed — chasing the puck — the company had already gathered reams of data, including more than 30 billion global flight itineraries and hourly climate data from every commercial airport in the world.

As the Zika crisis was swelling in January, Khan and collaborators from Oxford, Harvard and elsewhere published a paper in the Lancet anticipating the virus’s international spread. Their model used Brazilian flight itineraries, temperature maps, population densities, ranges for known and possible Zika-transmitting mosquitoes, and more — and most of the data was already on hand.

Among other things, their risk map showed that Florida receives huge volumes of travellers from Brazil, and has the right climate and the right mosquitoes for Zika transmission (though Khan says that better housing and less stagnant water in Florida make substantial local transmission unlikely).

“The questions constantly keep changing, and you have to keep responding to them,” says Khan. For decision-makers, his team must “work to answer those questions in a timely way so they can make better decisions in the face of imperfect information and uncertainty.”

The known unknowns

As WHO officials predicted the Americas would see millions of Zika cases this year, they added a caveat. “There’s a lot of uncertainty about some of the real basics of the disease,” said Bruce Aylward, an assistant director-general. “Some of the numbers are going to change.”

As researchers study Zika, new data will come to light that alters models — perhaps substantially. Disease modeller David Fisman paraphrases Donald Rumsfeld: “We have known unknowns,” he says. “But there may be something about Zika that we don’t even know we don’t know.”

For now, here are the known unknowns:

Fear factor

“Behaviour is the X-factor for a lot of infectious disease modelling,” says Fisman. But researchers are taking steps to fill in these blanks, with interesting results.

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Neil Seeman, a senior fellow at the University of Toronto’s Massey College and CEO of RIWI Corp., uses a tool called “random domain intercept technology” to survey web users. Essentially, when people surf to a domain that doesn’t exist, they instead see a short series of questions.

RIWI used this technology to find that while only 33 per cent of Brazilians felt confident public health officials could control Zika, nearly half still thought authorities’ advice to delay pregnancy was reasonable. Seeman intends to track these sentiments over time.

Hidden cases

An estimated 80 per cent of Zika patients do not show symptoms, meaning the bulk of cases are hidden. That makes it difficult to establish solid case counts, a vital piece of data.

Compounding the problem, the symptoms of Zika are similar to the symptoms of widespread diseases such as dengue and chikungunya, and these closely related viruses are difficult to tell apart in the lab.

PCR tests, which amplify DNA and RNA and can distinguish between Zika and related viruses, must be used early — usually before patients know they are sick. PCR testing is also not widely available, but the WHO says it is working to enable greater access for affected countries and to upgrade laboratory facilities.

Microcephaly

Zika causes fairly mild symptoms, and would be a far less urgent problem if not for its link to a rash of reports of microcephaly: babies born with abnormally small heads — a congenital defect associated with developmental problems. The Zika virus has been found in the brains of babies with microcephaly who died, and in placental fluid. But the link is still being probed, and the mechanism is unknown.

A primary question for modellers is how often Zika causes microcephaly in the babies of infected patients. Always? Only if the mother has already had a related virus, like dengue? Researchers are investigating.

Guillain-Barré syndrome

When French Polynesia was hit with an outbreak of Zika in 2013-14, the country reported 74 patients who suffered from neurological or autoimmune syndromes after showing Zika-like symptoms. Of those, 42 were diagnosed with Guillain-Barré syndrome, a condition that starts with weakness or tingling in the limbs and can lead to temporary paralysis and even death.

Five South and Central American countries with Zika have also reported increases in Guillain-Barré syndrome. The same questions posed by microcephaly are also at play here: is the rise real or the result of increased vigilance? If it is real, what causes Guillain-Barré in some patients but not others?

Mosquitoes

The WHO says Zika is “primarily” transmitted by the Aedes aegypti mosquito, the same species that spreads chikungunya, dengue and yellow fever.

But there are questions about whether other mosquitoes can transmit Zika too. The WHO says only that other species of Aedes mosquitoes “are believed to be competent” at spreading the virus. Aedes albopictus, the “Asian tiger” mosquito, also transmits dengue and chikungunya, and can survive in much cooler temperatures: its range reaches north to New York.

It can be difficult to prove an insect transmits a disease. Researchers rely on trapping insects in the wild and on lab testing to show the virus can survive inside the insect’s body and be transmitted to humans.

Transmission routes

In early February, doctors diagnosed Zika in a Texas patient whose partner had returned from Venezuela — the first recent evidence that Zika may be transmitted sexually (a scientist who transmitted Zika to his wife co-authored a paper first suggesting the link in 2011). The WHO calls the evidence of sexual transmission “scarce,” but any new way to catch the virus will alter models of how the disease spreads.

The U.S. recently released new guidelines on donating blood for people in affected areas, and there is some evidence that the virus is found in urine and saliva. Bottom line: more research needs to be done on how and when Zika persists in bodily fluids.

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