Three SFI External Professors are modeling patterns of flu outbreak and response to help health of financials manage the next pandemic.
Soon after H1N1’s initial emergence last year, mathematical epidemiologist Lauren Ancel Meyers at UT Austin and colleagues used Facebook to gauge initial perceptions about and behaviors toward the flu, then conducted a national poll. As news media attention tapered, they noted that “people’s perception of the risk of flu increased, but their willingness to adopt prevention measures declined,” she says. Now they are surveying New York City and Milwaukee, which had large summer outbreaks, and L.A. and D.C., which did not, to see how local infection levels affect residents’ behaviors.
Regardless of perceptions, optimizing the public health response to the pandemic could affect millions of lives. The U.S. stockpile has 50 million anti-viral drug treatments for national distribution. (Though not vaccines, anti-virals can treat symptoms and reduce transmission.)
In modeling millions of scenarios, according to Lauren, the politically tractable option of distributing five million anti-virals a month distributed proportionally to states populations consistently emerged among the better choices. She is currently looking at how best to distribute vaccines to reduce hospitalizations and deaths.
Carlos’s study of Japanese youths’ high susceptibility to H1N1 raised another dilemma: The u’s severity among youth indicates they should be vaccinated, he explains, but the high transmission rate among them means many likely already have had it, so immunizing them en masse wastes the vaccines.
Another vulnerable – and controversial – cohort is undocumented groups, Carlos says. Transient workers live in higher population densities and use public transport, but often have less access to medical resources.
“Those are the people you want to give access to,” he points out. Add corruption in stressed medical systems and inadequate access to supplies in poor countries, and an increasingly complex landscape emerges.
Behavioral epidemiologist Joshua Epstein at the Brookings Institution has developed the world’s first planetary-scale agent-based model to help address such questions. In his simulated societies, individuals (or agents) exhibit varying levels of susceptibility, stages of disease, and changes in behavior. Josh has modeled coupled contagion dynamics of fear and disease, the effectiveness of global travel restrictions, and the cost of social measures.
“Health care workers are the most important cadre in containing flu and treating the sick, but they’re a big component of the absentee pool,” he explains. “Almost 20 percent could miss work, which would degrade the flu containment strategy in a nonlinear way.”
In a recent PLOS Currents study, he and colleagues showed that closing U.S. schools for a month could run $47 billion in GDP – and trigger other effects.
Carlos Castillo-Chavez, a theoretical epidemiologist at Arizona State University, weaves practical and theoretical elements into what he calls “the big question: How do you weigh interests with risk?”
Mexico, for example, implemented social measures at tremendous economic cost, whereas the U.S. and Canada adopted less stringent measures. Now, people’s cross-immunity may protect sub-populations from later rounds by changing the entire immunological landscape.