We could probably predict zika outbreaks if humans weren’t so unpredictable

Early last year, President Trump was just the punchline to jokes about the motley ensemble of Republican presidential candidates and the Zika virus was the national story of the moment. The

mosquito-borne pathogen dominated headlines: “Senate Democrats Urge Obama to Form a Response Plan to Zika Virus,” “How Scared Should You Be About Zika?” At the height of the panic, Andy

Monaghan, a meteorologist at the National Center for Atmospheric Research, got an email from his boss. He asked if NCAR was doing anything to address Zika. “No,” Monaghan replied. The center

is an atmospheric science organization, he thought, what would we do? But that night after he got home, he reconsidered. He knew the Zika-carrying mosquitoes could only survive in a

relatively narrow temperature range. How hard would it be to throw together a climate model to figure out whether conditions were right for a national outbreak if local transmission of Zika

began in the U.S.? Eight weeks later, he published a paper with several other climate scientists, entomologists and public health officials from across the country, in which they used

historical weather data and travel patterns to project that the Zika virus would enter the U.S. but that low temperatures in most of the country would keep it confined to isolated outbreaks

in southern Florida and Texas, at least during the winter months. The paper was a smash hit, making it all the way to a White House press briefing, where then-press secretary Josh Earnest

used the findings to urge Congress to approve Obama’s request for funding to fight Zika. “We knew going in that there would be public appetite for this kind of information,” Monaghan said.

“But we were pretty surprised at how much attention it got.” The public has shown a growing appetite to have scientists use the weather to forecast the risk of disease outbreaks the way

they’d forecast the chance of rain. As global temperatures change, the distribution of infectious diseases spread by insects, such as Zika, malaria and Lyme disease, appears to be changing

as well. Seasonal and geographic distributions of diseases are less predictable. Avian malaria, a close cousin of the human disease, has been found infecting birds as far north as Alaska. At

the same time, advances in global climate modeling, combined with our pre-existing understanding of how weather affects mosquito life cycles, are enabling some scientists to peek into the

near-term future, looking to get ahead of the next epidemic. It has long been predicted that climate change will cause vector-borne diseases to spread into new areas. Now, that general trend

is upon us, so the next frontier is predicting specific epidemics on a useful time scale. But how realistic is that goal, and how useful can these predictions actually be? In December,

months after Monaghan published his findings and one month after the World Health Organization declared the Zika public health emergency ended, scientists from the University of Liverpool

published the results of a new global risk model, showing that weather was a key factor in Brazil’s Zika outbreak. The virus is believed to have arrived in the country in 2013, but their

data suggested that the warm weather brought by 2015-16’s “Godzilla” El Niño — when added to the warming baseline temperatures caused by climate change — was responsible for unleashing the

outbreak two years later. Their model, which combined climate data with mosquito virus transmission patterns, found that warm, wet weather made conditions especially conducive to a Zika

outbreak in Brazil in 2015. Even if Zika had been present in South America for decades, weather conditions during El Niño raised the risk of an outbreak to a level higher than it would have

been at any point in more than 50 years. This information was published after the disease had already been linked to at least 1,326 cases of microcephaly in infants in Brazil. But “I think

we’re moving towards forecasting systems, slowly but surely,” lead author Cyril Caminade said in an interview, and he’s working on a prototype to make the model available to public health

agencies. The patterns revealed by Caminade’s model were groundbreaking and made headlines around the world. But he readily acknowledges the model’s limitations: According to his results,

conditions were also ripe for a Zika outbreak in Angola, where no cases were reported in 2015, even though the virus was known to be present in the mosquito population. This might be because

Zika has been present in Africa for longer and Angolans have developed some immunity, or it might be that a lack of public health services and surveillance made it difficult to detect the

disease — no one knows for sure. People, diseases, bugs and weather interact in complex ways. Some things are certain: Temperature plays a crucial role in every stage of a mosquito’s life

cycle. Too cold, they die. Too hot, they die. But in the sweet spot, around 77 to 90 degrees Fahrenheit, mosquitoes are hungry and full of energy. Mosquitoes bite more as it gets hotter, and

the amount of time it takes them to become infectious after biting a virus-infected animal is shorter at higher temperatures. And rainfall plays an important role in providing a habitat for

larvae and pupae. Other factors are much less predictable: human travel, human immune response and the likelihood of an extreme weather event such as a hurricane, which could interfere with

insect-control efforts and leave standing water behind for mosquito breeding. Even things that seem well-established in the scientific literature, like the temperature range in which

mosquitoes can survive, are up for re-evaluation. Sara Paull, a colleague of Monaghan’s at the NCAR, is studying the insect’s potential to thermoregulate (i.e., go fly around in the shade

when it’s too hot). Despite these uncertainties, models like Caminade’s and Monagahan’s could be valuable to public health officials. “Our model can be useful to look at temporal changes,

for example to use seasonal climate forecasts to issue a ‘good or bad mosquito season’ forecast,” Caminade said in an email. But there are nontechnical obstacles to creating even these basic

forecasts. First, who should be in charge, and who should pay? Access to climate data and computing power is expensive. Plus, scientists and research groups face a risk when they put their

models to use in real life. “We’re dealing with highly nonlinear, uncertain systems. Nobody wants to be that person or group who’s wrong in these things, particularly when you’re dealing

with human health outcomes,” Monaghan said. And someone is inevitably going to get it wrong. But “I think we need to get over that and at least get some tools out there, as rudimentary as

they are,” he said. Other research and economic sectors have long relied on predictive modeling to forecast weather-dependent changes that could affect their interests. Farmers have been

using drought and seasonal climate predictions for years. Businesses try to anticipate diseases and the potential aftereffects of epidemics in order to plan supply chains and minimize

disruption. Animal disease forecasting is a sort of testing ground for potential human outbreak tools. Scientists successfully used a weather-based model to predict an outbreak of Rift

Valley fever among livestock around the Horn of Africa in 2006-07. But as much as these fields suggest promise, they also supply plenty of cautionary tales. An early-warning model developed

by respected scientists to project crop yields and food security in West Africa failed twice in three years “People stopped trusting them,” Caminade said. Caminade, Monaghan and their

colleagues don’t want to turn people off of predictive, climate-based modeling — but they don’t want to get anyone too excited either. Because the truth is, climate modeling can only predict

how the _climate_ will affect the problem under consideration, whether that’s drought, crop yields, or the spread of mosquito-borne diseases like Zika or malaria. But the most important

factor in determining how much damage a disease can do isn’t always the weather. “The big unknowns, in my view, really lie with the human factors,” Monaghan said. “Fifty years from now, what

will be changes in medical technology? What type of vaccination technology will there be, and how widespread will its use be? What will human exposure be in a different climate? What will

public health capacity be?” The spread of disease largely depends on human population growth and socioeconomic factors, such as whether households have protections like window screens and

whether communities have public health and insect-control services. England or California could start to see mosquitoes bearing tropical diseases, but because the people there can relatively

easily control their exposure by buying repellent or by staying inside and using window screens, and because both locations’ governments have public health resources, a disastrous outbreak

is less likely in these places. Public health workers in Brazil reported that Zika hit the poorest regions the hardest, places where most homes don’t have air conditioning and are otherwise

more open to mosquitoes, or where there’s no running water, forcing people to store standing water near their homes, creating areas where mosquitoes can breed. “Climate change is going to

have an important impact on the potential suitability for future virus transmission and vectors that transmit them,” Monaghan said. But “human factors could swamp some of the climate-change

things that we see.” Developing early-warning systems for disease is an important part of what humans can do to prepare for a warmer, wetter world. Caminade is working on a prototype he’ll

make available online to give people information on their risk of exposure to specific diseases. Monaghan is working on seasonal risk forecasts. But Caminade and Monaghan agree that their

work is a small part of the most urgently needed disease-fighting technique: sharing resources and building public health capacity around the world to be ready for any disease, even if we

can’t see it coming ahead of time. “These are the types of steps that need to be taken,” Monaghan said, “building near-term capacity to deal with long-term problems.”