At the start of this year, Yemen saw the largest cholera out on record in a single year. There were 1 million suspected cases and over 2,000 deaths since the end of April 2017. It was already a challenging situation, expected to get worse with the coming rains.
“We had significant concerns about the rainy season which would start in March or April, given the fact that the conflict hadn’t slowed down in any way. If anything the situation had gotten worse,” says Fergus McBean, a humanitarian advisor at the Department for International Development.
The disease is preventable and treatable if it’s identified early, so the challenge was finding a way to work on better preventative methods.
In response to the risk, McBean led a groundbreaking project to use weather forecasting and cholera risk modelling to better inform prevention in the war-torn country.
When he joined DfID’s Yemen team in December last year, academics from organisations such as MSF, the World Health Organisation and the United Nations children’s agency Unicef, were looking at the indicators that lead to spikes in outbreaks of cholera.
“What they found in these risk assessments is that the June spike in cases was heavily correlated with accumulated rainfall,” McBean says.
“They could show an 80% correlation between where you had heavy cumulative rainfall and attack rate (how quickly the disease spreads) increasing nine days later.
“So that lead me to think if we’ve got a nine-day window, if we had forecasting of that rainfall we could buy ourselves more time and could target interventions much more specifically.”
Because weather intelligence isn’t readily available in Yemen, DfID worked with the Met Office who gave them access to weather forecasting for Yemen on a weekly basis.
At the same time, McBean approached academics in the US who had already developed an algorithm for cholera prevention, using funding and data from Nasa. They agreed to give the DfID team monthly risk assessments.
“In most cholera outbreaks, you’d normally wait to see if cases were increasing, and you should then start deploying resources to respond.
“In our case we’re trying to respond before cases emerge. At each stage the benefit of acting early means you minimise the height of that curve [of the disease spread],” says McBean.
“We’re trying to catch the disease before it goes from the environment into people, and if you cut it off at that stage then you shouldn’t see cases coming in.”
McBean was awarded the 2018 Civil Service Use of Evidence Award for his work in Yemen, and hopes the project will continue to develop and grow. “There’s a lot of excitement around where this could go, especially in terms of bringing in other academics and additional algorithms.”