THE THOMAS FRANCIS, JR. MEDAL IN GLOBAL PUBLIC HEALTH

Disease Detectives Fight Viruses with Math, Sociology, and Policy

When Matthew Boulton sits behind his worn wooden desk in the School of Public Health, his gaze falls naturally onto a large, framed photo of the moment 50 years ago when the world learned the vaccine against polio worked.

In the black and white image, Jonas Salk beams out at a crush of reporters interested in learning more about the polio vaccine they had just heard was safe, potent and effective. To Salk’s right stands Thomas Francis, Jr., his mentor and the mastermind of the field trial that proved the vaccine’s safety.

Boulton’s desk used to belong to Tommy Francis—just one of the ways Public Health’s history connects to its present. And its future.

At the beginning of the last century, major advances such as cleaning up public drinking water, establishing standards for safe food handling and the invention of antibiotics dramatically boosted life expectancy by about 25 years. That was the low-hanging fruit, Boulton said. Making advances in health now takes more technology and sophistication.

Jim Koopman, professor of epidemiology, said it’s no coincidence that modern disease surveillance grew up in the last two decades, which put PCs on every academic’s desktop.

“Back in Tommy Francis’ day, they had very primitive ideas about analyzing infection transmission,” Koopman said. Without an understanding of the mathematics of disease spread, infection control could not be well focused.

Today, disease detectives build a mathematical model around data about who’s getting sick, where they are located and where they’ve been to make an educated guess about where a disease came from and how it might behave without human intervention.

This analysis stems from a better understanding of the infectious agents that make us sick, along with a different way of viewing the population. Instead of looking at the world as collection of individuals, Koopman said he and his peers look at it as a big, interconnected system of sub-populations. If you know where people are most likely to come into contact with an infectious agent, you can aim to block the transmission routes in very specific groups, rather than having to treat everyone with vaccines.

For example, Koopman said Chinese leaders took dramatic actions to stop the spread of SARS in 2003 even before knowing exactly what it was. He said they recognized that the infectious agent seemed to be both directly spread and airborne, so they looked for ways to keep sick people from spreading the bug to others directly or through the air. That meant calling on people to stay home, and temporarily shutting down public transportation.

Understanding transmission also can help researchers formulate approaches for the lab.

Sonja Gerrard, assistant professor of epidemiology, hopes one day to develop a vaccine for Rift Valley Fever virus, which spreads primarily through livestock in some African countries, although it can move into people.

“We really have transmission nailed on Rift Valley Fever,” Gerrard said. “Now we want to stop it, and to do that, we’re thinking in a sort of polio model, where we would like to stop it before it takes hold in the body.”

Modeling the transmission of the virus helped Gerrard and colleagues understand that the virus first starts in livestock who get bitten by mosquitoes, and if one of these mosquitoes bites a person, there’s a potential for the virus to move into the human’s bloodstream. Knowing that it starts in animals has Gerrard thinking about Rift Valley Fever as an overall ecology, not just a human problem.

“We are looking with greater interest into veterinary pathogens—whether they make people sick, or kill off animals causing economic and food source problems, these pathogens have a huge influence on people,” Gerrard said.

Betsy Foxman, professor of epidemiology and director of the Center for Molecular and Clinical Epidemiology of Infectious Diseases, said Francis’ legacy is bringing both the social understanding of how viruses move around and the laboratory research that explains the biology of the infectious agent and how it behaves.

“His strong vision was that epidemiology had to go from the lab bench and into society in order to really understand disease,” Foxman said. She noted that if you have either the biology or the social relationships part of disease modeling wrong, the results will be incorrect, leading to bad recommendations and policy.

Foxman studies antibiotic resistant microbes and said it’s critical to see such a problem in terms of biology, environment and policy combined. “What interests me are interactions, not just an individual disease system in an individual,” Foxman said.

Mark Wilson, director of the Global Health Program at U-M, cites another example: a graduate student he and Koopman are working with is doing her dissertation on climate influences in the movement of people and disease, particularly as it relates to flu. It’s part mathematical modeling, part climatology, part social inference about how people react to changes in seasons and temperatures.

Wilson, a professor of epidemiology and of ecology and evolutionary biology, said scientists seeking to understand disease have little choice but to turn to advanced modeling—disease happens in real-life conditions, and there is no way to recreate a virus’ movements in a controlled lab setting. Instead, they need to look at what has happened in the past, look for patterns and connections, and make projections from there.

Associations might not be causally related—A might not make B happen—but they might routinely show up at the same time and give inspiration about how to go after an infectious agent, Wilson said.

Toward that end, Wilson and Boulton are teaming up with Michigan Department of Community Health officials on something called a syndromic surveillance system. Instead of compiling data on diagnosed disease—how many reported cases of salmonella in Michigan, for example—this system looks at symptoms like sniffles or fever, and takes into account factors like over-the-counter drug sales, ambulance runs and absenteeism, signs that something may be going on even before the medical community is involved.

This broader approach to disease modeling presumes that when there is a spike in food poisoning, for example, it shows up first as increased sales of antidiarrheal over-the-counter drugs before patients start hitting the emergency rooms. That sort of information could give medical facilities an early warning that a particular bug is making the rounds.

Wilson’s expertise is emerging disease—that is, pathogens that are new or behaving in some new way. Monitoring symptoms can act as the early warning for emerging disease, since doctors might not even know how to correctly diagnose a disease they rarely or never see.

“There are no really new agents,” Wilson noted, though. “What’s new and changing are our patterns of contact with them.” New diagnostic tools might help to name diseases that have been around forever, or changes in society might make humans more susceptible to some bugs.

Foxman cautions against using advanced technology simply to escalate the arms race against viruses, though. If modeling of disease transmission helps researchers understand how a virus moves from person to person, she said there are multiple ways to use that information. For example, instead of getting a shot or taking a pill to wipe out the infectious agent, she might advocate for what’s called probiotics—encouraging the growth of beneficial microbes that retard the growth of the bad guys.

“Instead of thinking of the infectious agent as an enemy attacking you, how can we live together in peace?” Foxman said. “I think of an antibiotic as nuclear war, blowing everything up. How can we recognize the beneficial effects of some of these infectious agents, if they’re found in small enough amounts?”