Sunday, February 15, 2015

Ebola Epidemic Should End in May, Say Disease Modelers
A new mathematical model of the way the disease spreads in West Africa predicts that the Ebola epidemic should be over by the middle of the spring.

On March 17, 2014, doctors diagnosed a single case of Ebola in the county of Lofa in Liberia, West Africa. This was the first, patient zero, in an epidemic that has so far infected more than 20,000 people and killed almost 8000.

On August 15, the World Health Organization and other bodies began a major drive in Liberia to halt the epidemic. The strategy has two parts. The first aims to limit the spread of the disease from people who have been infected by ensuring that everyone with symptoms goes to an official treatment center.

The second is to prevent the spread of the disease after death by ensuring that every Ebola victim is buried in a way that prevents further infection. That means wearing protective clothing to place the body in a body bag and then in a coffin before transporting it to a grave. Finally, the aid workers must disinfect the victim’s home and ensure appropriate washing for all those involved in the disposal of the body.

Together, these measures appear to have had a significant effect on the spread of the disease. But an important question remains: when will the epidemic end?

Today, we get an answer thanks to the work of Lucas Valdez from the National University of Mar del Plata in Argentina and a few pals. These guys have created a mathematical model of the way the disease spreads that predicts an end to the epidemic for the first time.

The team started by determining the factors their model needs to take into account. To begin with, it needs to allocate a status to all individuals involved. For example, a person who has not had the disease is classified as susceptible. While an Ebola patient can be classified as one who goes on to die or one who survives. These can be further classified as those who are treated in hospital and those who are not. And the dead can be classified according to those who receive safe burials and those who receive unsafe ones.

The team then builds a mathematical model which captures the likelihood of each individual moving from one state to another. A key part of the work is then to determine the real values of these probabilities from data taken from the field.

It turns out that in Liberia data collection has been relatively good compared to the other two countries involved in the epidemic, Sierra Leone and Guinea. So the team runs its model on data from this country alone.

One important factor in the rate of infection is the mobility of people from one part of the country to another. Valdez and co can capture this using other work that shows how mobility varies during an Ebola outbreak using mobile phone network data to monitor population movements.

That provides an important insight into how movement contributes to the epidemic. “Unlike other models used to describe Ebola outbreaks, our model enables us to explain how the spreading inside Liberia is due to mobility between different counties,” they say.

One potential response is to minimize or even ban travel entirely. Indeed, mobility drops during an Ebola outbreak anyway because of people’s fears of catching the disease. However, Valdez and co say their model shows that a travel ban would have little impact on the overall size of an epidemic.

That’s because people manage to travel regardless of a ban and the spread of infection is inevitable. Instead, the effect of any travel ban would only be to delay the onset of an outbreak.

However, the model shows there are much more effective measures. Valdez and co say that the two strategies employed by the World Health Organization and others significantly reduce the rate at which the disease spreads. And this lowers the infection rate falls below the critical threshold necessary to maintain an epidemic. Their model goes on to show that the epidemic should be extinguished by mid-May this year.

That’s a brave prediction but one that will surely be warmly welcomed in West Africa. One reason to have faith in this prediction is that the model accurately predicts the evolution of the disease as it has occurred so far. So it is not so hard to imagine that the model should be correct over the next couple of months.

Valdez and co point out that the disease could have been tamed much more quickly. They show that if the same strategy had been implemented in July, then the epidemic would have been extinguished in March. “If the health authorities and the international community had acted sooner the number of infected people would have been much lower,” they conclude.

That is something of an indictment of the international response. Clearly, an effective intervention earlier would have saved a significant number of lives.

Nevertheless, the intervention in August looks to be an incipient success. “Our study indicates that the intervention implemented in August 2014 reduced the total number of infected individuals significantly when compared to a scenario in which there is no strategy implementation,” they say.

And they point out that the same methods they have used for Liberia can also be applied to Guinea and Sierra Leone as soon as good enough data emerges.

There is an important lesson to be learned here about the way that future outbreaks should be handled. “A rapid and early intervention that increases the hospitalization and reduces the disease transmission in hospitals and at funerals is the most important response to any possible reemerging Ebola epidemic,” say Valdez and co. And the sooner it is implemented, the better.

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