UC Davis's One Health Institute (OHI) focuses on problem-solving for emerging infectious diseases and conservation challenges to address global health issues.

Executive Director Jonna Mazet shares their Predict project's current findings, including

• How they have discovered numerous viruses and  more than a hundred different coronaviruses, the family to which COVID-19 (SARS CoV-2) belongs;
• How they identify high-risk transmission zones where people are working with animals in a especially stressful way that would cause virus spillover; and 
• What risk factors they've developed to gauge the viruses themselves through the help of 70 different international researchers. 

In addition to her work as Executive Director, Joanna Mazet is a Professor of Epidemiology and Disease Ecology at the UC Davis school of Veterinary Medicine. OHI has been working since 2009 to understand viruses that spill over from animals. For the COVID-19 version specifically, they've been using their Predict platform to help global communities predict, understand, and identify its spread.

OHI and their Predict project is especially looking ahead to prevention for future global health issues. She discusses the various approaches, from bringing together ministries of health, agriculture, and environment in countries with less resources to communicate and identify high transmission zones. She describes the factors they use to identify high risk zones and means for mitigation.

Dr. Mazet also describes the essential efforts to prevent future global health issues such as pandemics, including the need to understand as much about viruses as we do about bacteria. She explains that predicting a virus's harm potential is more about its ability to jump to multiple host species rather than its relatedness to other harmful viruses.

In addition, they are testing species that weren't the target host to understand SARS CoV-2 (COVID-19) better and figure out clues to help scientist fight other viruses.

To find out more, see the list of published literature on predict.global, where maps of their surveillance work with test results and affected species are also posted.