The models cannot, however, tell them how to achieve the necessary benchmarks, because there is no way to model for human behavior.
“In particular Ebola is strongly determined by human behavior, and it’s pretty impossible to predict how humans are going to start doing things. At the moment there’s a lot of resistance to some of the classic public health interventions,” Lewis said, citing the recent looting of a treatment center in Monrovia. On September 18, Reuters reported that three journalists and five health care workers were brutally killed while spreading Ebola awareness in Liberia.
“It makes a lot of sense that the population doesn’t trust authority figures, because why should they? Those are the people that burned down their villages previously. It’s going to take a longer period of time for the population to understand that the people showing up in these scary white suits are actually helping people instead of killing them.”
“The trouble is to get people to believe that going to the hospitals is in their best interest,” said Meltzer. “We’ve got to get people to understand that. You can go around to villages and cities and slums all you want and say, ‘If you’re ill, go to the hospital.’ Why should anybody believe? We can’t model that.”
They can collect empirical data from aid workers in different locations. They can see how effective a message was in one community, and see if that effect would be worth the effort in other areas, but no matter what, they can’t model human behavior.
The interventions seem to be working in Guinea, where the rate of transmission is now less than one, according to Meltzer. They have cut off the chain of the disease there, he said, and must stay vigilant in order to keep it that way. Across West Africa as a whole, though, the average transmission rate is still higher than two new infections per infectious person, according to Maia Majumder. Majumder is a Ph.D. student at MIT Engineering Systems and research fellow at HealthMap. Her group is working with an IDEA (Incidence Decay and Exponential Adjustment) model in order to estimate the growth and longevity of the outbreak, and how transmission rates change when various interventions are attempted. They are looking at some of the more recent interventions, such as closing borders and opening new treatment centers.
Their outcomes show “that what we’ve done so far has not yet been enough to make a real dent in decreasing the growth rate of the outbreak,” she said. “If nothing changes in the disease control and prevention department, case counts will continue to soar.”
It will start to subside, though, if the interventions start to make an impact. But it’s impossible to predict if the interventions will make an impact, because that depends on human behavior.
Even if the average is brought below the target of one new infection per infectious person across the entire region, though, there will still be dangerous outliers that the models do not take into account. “Some sick people won't infect anyone, and some will be super-spreaders, transmitting to perhaps a dozen people,” Rivers said. Regardless, the goal remains lowering the average rate of transmission as much as possible.