A new computer model that takes into account not only features of the virus and how it transmits, but also what is being done to halt its spread, predicts that the Ebola epidemic in Liberia could end by June if current high rates of hospitalization and surveillance continue.
“That’s a realistic possibility but not a foregone conclusion,” says John Drake, an ecology professor at the University of Georgia (UGA), who led the project to develop the model with other ecologists at UGA and also at Pennsylvania State University.
The team reports how they developed the model and ran some scenarios through it, in the open access journal PLOS Biology.
Prof. Drake says their epidemic model is probably the first to take into account factors such as where infections occur, where patients are treated, growth in hospital bed numbers, and the adoption of safe burial practices.
He and his colleagues hope the tool will help public health authorities fight the Ebola epidemic, because unlike many other models, it offers realistic forecasts.
Public health officials use epidemic modeling to help them devise and implement disease controls. Several models of the 2014 Ebola epidemic in West Africa have been published. For example, in September 2014, a Centers for Disease Control and Prevention (CDC) model predicted Ebola cases could exceed half a million by January if efforts to contain the spread did not improve dramatically.
Prof. Drake says many of the models that have been published seek to estimate Ebola’s reproductive number – the number of new infections that a single infected person can generate.
He says that while this is useful – and their model does it too – to get a realistic picture, it is also necessary to take other things into account, but not to the point of making it too complicated. He says their model “aims to be intermediate in complexity – it captures all the things we think to be most important and ignores the rest.”
In their paper, the team describes how back in the fall of 2014 – after a period of great uncertainty about the Ebola epidemic in West Africa – they ran five different scenarios through the model, each with a different set of assumptions about hospital capacity.
In the worst case scenario – which assumed no increase in hospital beds – the model predicted there would be around 130,000 total cases of Ebola by the end of 2014.
In the best case scenario – which assumed an 85% hospitalization rate, or 1,400 more beds per roughly 1,700 more cases – there would be around 50,000 total cases.
The authors then updated the model with data collected up to the beginning of December 2014. Based on that information, the model predicted that if the 85% hospitalization rate can be sustained, then the Ebola epidemic will be largely contained by June 2015 in Liberia.
“What’s needed is to maintain the current level of vigilance and keep pressing forward as hard as we can,” urges Prof. Drake.
The model takes into account important variables such as infection and treatment setting, the extent to which infection rate can vary from person to person, the actual build-up of hospital capacity over time and changes in burial practices.
The model uses the latest methods of applying branching processes – a way of keeping track of all possible epidemic results in proportion to their probabilities.
The team primed the model with data from previous Ebola outbreaks – such as numbers of hospitalized patients and health care workers infected – so they could also estimate levels of potential under-reporting, rates of spread in hospitals and outside, and the effectiveness of disease controls.
They then fine-tuned the model with data from the World Health Organization (WHO) and the Liberia Ministry of Health covering early July to early September 2014. Liberia continued adding more hospital beds after this, so the team updated that variable in mid-December.
By using actual data rather than estimates from earlier runs of the model, the range of future scenarios is much more limited and shows how the efforts by international groups and the Liberian authorities have significantly reduced the chance of a huge epidemic.
The team hopes the model will prove useful beyond the current Ebola epidemic. They have devised a way of re-tuning it using “plausible parameter sets” so it can fit future rapid response scenarios, says Prof. Drake.
Case incidence has declined to low levels in Liberia, but it is still up and down in Guinea, “with no identifiable downward trend,” say the UN health agency. In Sierra Leone, there are signs that incidence has leveled off, “although transmission remains intense in the west of the country.”
Meanwhile, Medical News Today recently learned about a lab in a suitcase that can rapidly detect Ebola virus on the spot. The hope is the invention will improve control of Ebola by removing the delays and obstacles that health professionals face when trying to diagnose the disease far away from labs.