Is it really possible to predict the next disease outbreak?
The International Livestock Research Institute estimates that over two billion people each year fall ill with a zoonotic disease. It’s a staggering number.
But with the rate of disease emergence and re-emergence across the globe, it means that discovering a cure for every disease is an impossible task. One way we can tackle this challenge is with better surveillance and data gathering that prepares countries for the next potential outbreak.
A project launched by the US Agency for International Development (USAID), called PREDICT, does just that. Working in 28 key geographical “hotspots”, the initiative helps to gather ecological insights about local wildlife, livestock and people and the potential zoonotic viruses which they share with local government ministries of agriculture, environment and health.
We spoke to Dr. William Karesh, Executive Vice President for Health and Policy at EcoHealth Alliance which is a partner in the PREDICT project, to find out how they help to prevent the next outbreak.
You promote a One Health movement by working with the local ministries of agriculture, environment and health in each country – how do you collect and share your data?
We work with local partners and train people to safely collect diagnostic samples in remote areas all the way through to the lab. The project is testing humans and running the same tests on the humans for viral diseases that are run on the wildlife and livestock. All results are shared across ministries and approved prior to public release. For example, results from human testing, anonymized of course, is shared with government livestock and wildlife authorities.
How do you use this data to ‘predict’ the movement of infectious diseases?
What we do is a bit like earthquake or forest fire prediction. What we’re saying is that some conditions and activities in some places in the world have a higher probability than other places of the disease emerging.
We’ve taken an ecological approach. We analysed the underlying factors where emerging diseases have been occurring over the last 50 years and mapped those factors, not the diseases themselves. Then you have a risk profile of where the factors are that lead to disease emergence. We use that to target surveillance in countries and parts of the world which have more of those risk factors coming together.
Can this data help to eradicate diseases?
You’ll never eliminate all outbreaks, you’ll never eliminate all epidemics. But we certainly can reduce the number and we can reduce the intensity.
But now we have data for countries to use. It belongs to them, it’s not our data it’s their data. And probably more important is facilitating a One Health discussion and ways to work together. For example, in Cameroon they had chimpanzees being affected with monkey pox, which is a potential risk for humans. So, the government organizing committee responsible for One Health issues met and planned how the different departments could work together to handle the next outbreak. So when someone did report monkey pox again they saved 10 or 12 days in their response time, because they already had pre-approval for what that response would be and for them to work together. They didn’t have to start from scratch.
So what’s amazing is when you start to shorten response times, you have a huge impact on the epidemic curve.
How else has PREDICT helped to spot a potential disease threat?
We’ve had some great findings. Just this year there were reports of pigs dying in China. I think the first outbreak killed around 29,000 pigs on five farms and the agent was identified as a coronavirus.
When the original SARS Corona Virus broke out in China (in 2004), it took months and months to find out the source of that, and actually years to then find that it originally came from bats.
But in this case, because of the PREDICT project, the Chinese government was able to act quickly because bats had been previously sampled, and all coronaviruses were catalogued and put into a database. It meant they knew immediately where the source of the outbreak came from and they could focus prevention efforts on improved biosecurity approaches.
While working with PREDICT what has been the biggest surprise?
It’s really been around how seriously so many countries have really embraced One Health and are putting it to use, as that Cameroon example shows. It’s great to see Kenya has a special zoonotic disease branch.
I think it’s harder in some ways in rich countries, like in North America or in Europe, for One Health to get a foothold because every sector has enough money to do their own thing, so they don’t naturally tend to work together. But in low or middle income countries they actually see the efficiencies and cost effectiveness of those approaches. So that’s been a very pleasant surprise.
Do we need to invest more money in this?
One of the benefits of One Health is about thinking more about sharing our resources. I’m not sure it’s always about needing more money. But I think it’s about discussing where that money is invested to create the best outcome.
There is the example of rabies: the cost of treating rabies in humans is really expensive and that puts a burden on the public health sector. The best prevention is to vaccinate dogs, but there’s a different group that has to pay for that and they might not have all those resources. So, you end up having money tied up in human treatment. In Israel, the ministry of health started moving part of their budget to the ministry of agriculture for rabies vaccination in dogs. This could mean that one department could actually save money by giving it to another department! But it’s not necessarily requiring more money, it’s about a better national allocation of resources.
Dr Karesh has a doctorate in veterinary medicine. He has been President of the Working Group on Wildlife at the World Organization for Animal Health (OIE) for 10 years and at Eco Health Alliance for seven years.
Read on for more information about zoonoses and their impact on the world.