Science & Technology

Database Aims to Predict New Viral Threats

Since the beginning of modern medicine, science has been playing catch-up with viral outbreaks and pandemics; resources are allocated and effort dedicated only when viruses appear and begin to wreak havoc on human populations. Peter Doszak, the president of health research organization EcoHealth Alliance, aims to bring an end to this approach and encourage the scientific community to take on a more proactive response to viruses by predicting them before they happen.

Known as the Virome Project, this initiative aims to catalogue hundreds of thousands of viruses found in animals (some of which have yet to be discovered) and compile them into an open database. The goal is to use this complete database to predict which animal viruses are most likely to mutate and cross over into the human population. Based on these predictions, scientists can begin working on possible treatments and prevention methods that can be deployed to avoid a pandemic.

The large price tag for a complete virus database, an estimated $1.2 billion, means that EcoHealth Alliance has had to make concessions on the scope of this project. As a result, the current target of the Virome Project is to obtain samples of the 71% most common viruses found in animals that are most likely to find vectors to the human population. The remaining viruses, Doszack attests, are so rare that they pose a much smaller threat to humans and are incredibly costly to obtain. Still, even with these limitations, he believes that the Virome Project database has the capability to be a game changer in the virus research community.

Fieldwork on this groundbreaking project will begin this fall on rodents, primates, and bats (three animals that pose some of the greatest viral threats to humans) in China and Thailand. Blood samples, and oral and genital swabs will be taken, viruses extracted, and then findings uploaded as soon as possible onto the database, which is planned to be free to the public and scientific communities.

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