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Ebola: Where next and how bad?

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Forecasting Ebola spread has been problematic

LONDON, 1 December 2014 (IRIN) – In the past few months huge amounts of time and energy have been spent trying to second-guess the progress of the Ebola outbreak in West Africa. Where will the next hotspot be? Is the outbreak still exploding or is it starting to burn itself out? And how many beds will be needed next week, next month or next year?

Predictions so far have been off the mark, so better ways of modelling are clearly needed. Research for Health in Humanitarian Crises (R2HC), a UK funding body, is now financing two Ebola-related projects aimed at improving epidemiological prognosis.

“The first thing we asked was whether this was something answering the urgent needs of Ebola response, and addressing the question, ‘What don’t we know about how to do this effectively?’ Also whether it was likely to yield useful results and how quickly those results would be available,” Daniel Davies, R2HC’s programme manager, told IRIN.

Mobile data tracking

One of the research projects (by a team at Oxford University’s Spatial Ecology and Epidemiology Group) is looking into mobile phone data to track movement in and out of Ebola-hit areas in order to assess the spread of the virus.

Negotiations are still going on with telecom companies about what type of data they will release, but typically in such situations they are willing to provide figures about how many mobile handsets have been seen to move from one place to another in a given week. So, for instance, when the first Ebola cases in Liberia appeared in Foya District near the border with Guinea, this kind of data might have shown whether Foya residents typically stayed in their own vicinity, or whether – since it is a border town and a major trading centre – there is brisk traffic between Foya and the nearest big town, Voinjama, and between Foya and the capital, Monrovia.

“The only other way you could do it,” says Nick Golding, one of the ecologists with the group, “would be to go out there and give everyone a GPS, but that’s not going to happen. The problem with mobile phone data is that it tends to stop at country borders. So to get an idea of cross-border movement we are supplementing it with census data, which tells us something about longer term patterns of how people move between countries. It’s not ideal, but it’s the best information we have.”

The speed with which the virus spread down to Monrovia showed Foya was indeed very “connected”. Golding says that being able to predict the next likely flare-up is going to get more rather than less important as the outbreak is brought under control and reduced to isolated hotspots in rural areas.

“Resources are limited, and we need to spot each flare-up as it happens. In the past, Ebola was brought under control just because isolated outbreaks were spotted and dealt with,” he explained.

Currently there is an outbreak in Liberia’s Rivercess County, which has few roads and where travel is difficult. Mobile phone data might be able to predict the likelihood of the virus spreading further east, or into neighbouring Grand Gedeh County, an area which has so far reported few cases. That would show health teams where they might need to concentrate their efforts.

The Oxford team is hoping to present their initial findings to the World Health Organization (WHO) within three weeks.

Predictions wrong-footed

Mathematical modellers have a difficult task predicting the spread of Ebola as it has wrong-footed previous forecasts, making those working on the ground wary of the figures. In mid-October, for instance, WHO predicted that, assuming things carried on the way they were, there would be 5,000-10,000 new cases a week by early December. WHO’s 26 November updates show just 600 new cases across the three most affected countries. Even allowing for under-reporting, the US Centers for Disease Control estimated the number to be between 1,000-2,000. 

“I don’t want to discredit the efforts of the modellers, but what we have learned from this epidemic is that it is very hard to predict, so we have made very few decisions based on these kinds of models up till now”

Michaela Serafini, Médecins Sans Frontières (MSF) Switzerland’s medical director, told IRIN: “Previous predictions used so many assumptions that it has been difficult to rely on them, so mostly MSF has been working on the evidence we have ourselves. We are operating isolation centres across four countries, which means we can be extra sensitive to any changes if, for instance, we have fewer cases one week than the week before. I don’t want to discredit the efforts of the modellers, but what we have learned from this epidemic is that it is very hard to predict, so we have made very few decisions based on these kinds of models up till now.”

Another R2HC-funded research project, in this case being conducted by a team from the London School of Hygiene and Tropical Medicine, has steered clear of those risky, epidemic-wide predictions. It is trying to bring the models as close as possible to the real world. The Centre for the Mathematical Modelling of Infectious Diseases works with day-to-day figures from treatment centres in the affected countries. They stress the need to stay responsive and flexible, and not look too far ahead.

“From the beginning we have worked hand-in-hand with MSF,” said Sebastian Funk, director of the Mathematical Modelling Centre. “Initially it was to predict how many beds they would need. They send us data collected on the ground and we analyse it for them, and I think they have found that useful.”

The group now wants to collect data from many different treatment centres on the ages of patients, the severity of their symptoms, how early they were admitted, how long they stay and the fatality rate. The results, they say, could give clues to better control of infection, better treatment regimes, and potentially hint at changes in community behaviour or the evolution of the virus.

They are also going to be working with Save the Children UK, to help evaluate the impact of their Ebola community care units, whether they help check the spread of the disease and whether they create additional risk for caregivers in the units.

“What we want to know is how best to distribute a vaccine”

Another project is to look at issues around possible Ebola vaccines. Funk says: “We know from the WHO when we might expect to have vaccines available and in what kind of quantities. What we want to know is how best to issue those doses, whether certain areas should be prioritized or whether they should be distributed everywhere equally. But obviously nothing is set in stone. We have to look at different scenarios, because we don’t know what path the epidemic will follow up to the point where the vaccine becomes available.”

Funk and his colleagues hope their results will be there in time to provide guidance as soon as the vaccine is ready.