Computational Biology, Epidemiology
The University of Chicago
Cholera and malaria outbreaks wax and wane in endemic regions of the world from year to year. Although the outbreaks can be geographically isolated and differ in size, they can sometimes grow into full-blown epidemics that encompass much broader swaths of land and affect many more people.
Mercedes Pascual's mathematical models are changing the way scientists think about how climate variability influences the dynamics of infectious diseases. One of the long-term goals of her research is to build computational tools that will help scientists identify when epidemics will occur. With that information in hand, researchers could then alert public health agencies. Those agencies, in turn, would be in a better position to meet the increased demand for lifesaving medicine and supplies when an epidemic occurs.
It's a plan that is still a long way off, however. Conventional approaches to quantitatively assess the role of climate variability on infectious disease dynamics have been limited by uncertainties about the relative importance of the different factors that can drive epidemics, says Pascual, who is on the faculty at the University of Michigan. "One challenge is how to determine whether outbreak patterns are innate—resulting from the central role of population immunity—or are driven by variations in climate, or by interactions between them," she says.
Predictive modeling is made more complex—and more pressing—by long-term environmental trends such as global warming that have to be factored in. "This is a tremendously important area at the interface of environment, ecology, infectious disease, and epidemiological modeling," says Pascual. "But the funding for this type of research has been limited—it's an area that falls between the cracks."
Becoming an HHMI investigator will enable Pascual, whose expertise is in epidemiology and computational biology, to expand her work building models of the dynamics of cholera and malaria in different locations in South Asia and Africa.
Born in Uruguay, Pascual had a "nomadic" childhood, as she describes it, living in four Latin American countries while her father, an engineer, moved from job to job. After college, she came to the United States as a visiting student and met Simon Levin, a theoretical ecologist at Cornell University, who is now at Princeton University. He suggested that she bring together her interests in ecology and mathematics.
Her early research focused on the response of ecological systems—specifically, plankton populations in the oceans—to environmental variability. One main goal of the models was to disentangle the roles of different environmental factors. More recently, Pascual has harnessed these ideas and further developed these mathematical tools to model infectious disease epidemics. She has authored several papers in the past eight years that have resolved a long-standing debate about whether annual variations in cholera infections in Bangladesh are driven mainly by intrinsic factors. such as the level of immunity in the population, or by outside forces, such as the influence of El Niño sea-surface temperature fluctuations on regional climate.
These studies revealed that El Niño conditions promote epidemics. But it's clear, she says, that climate factors are only part of the story, and forecasting efforts must take into account the interplay between climate variations and changing patterns of immunity. "Could we predict these epidemics six months to a year in advance?" asks Pascual. "We're having some success, but we need to collect more data and expand our efforts to consider other locations in Bangladesh and in Africa."
Climate can play an even larger role in diseases like malaria that are transmitted by insect vectors, especially in transition regions such as highlands and desert fringes where temperature and rainfall limit the abundance of mosquitoes. One of Pascual's most recent studies took advantage of long-term climate records of the highlands of Africa, where previous research had found little evidence of rising mean temperatures. Her analysis, however, showed a rise of approximately 0.5 degrees Celsius in the last half of the 20th century.
When she plugged the numbers into a model that included the size of mosquito populations, she found that "hypothetically, this small change in temperature could cause a large change in mosquito abundance—a nonlinear response and therefore quite significant." Going forward, she plans to calculate the potential impact of rising temperatures on levels of disease and to integrate other factors such as drug resistance. She also intends to study the roles played by rainfall variability and changes in land use in desert regions of India.
"I'm excited, because this is an area of research that HHMI hasn't funded before," Pascual says, "and it's an important area that we need to develop further."