What if public health officials had a way pandemic forecast How do meteorologists forecast the weather?
We already have ways to slow the spread of COVID-19, but going forward we need to be more direct and precise with our approach to all epidemics. Image credit: Dorieo qua Wikimedia (CC-BY SA 4.0)
An interdisciplinary team of scientists from the University of Georgia’s Center for Infectious Disease Ecology was awarded a $1 million grant by the National Science Foundation to figure out how to do exactly that.
The researchers, led by Regents Professor John Drake of the Odum School of Ecology, will use the funding to build infectious disease intelligent systems that can predict — and ultimately help prevent — new pandemics like COVID-19.
The goal of the project is to enable public health authorities and other decision-makers to understand in real time where and how it spreads — when a disease spreads from wild animals or animals. person-to-person — what is likely to happen, how diseases start to spread, and information that can be used to encourage different groups of people to take actions to keep themselves and their communities safe .
Drake, director of CEID, said: “I have been studying the dynamics of infectious diseases for more than 15 years and I believe that infectious disease models can be developed for real-time explanations of epidemics. spread anywhere on the planet. “I am inspired by the success of atmospheric models for weather prediction, which have become increasingly sophisticated over the past seventy years. We need the same for infectious diseases. This grant will help us realize technologies and cures for infectious diseases that do not yet exist.”
The team, which includes several faculty members from UGA as well as researchers from the University of Michigan and the Cary Ecosystem Research Institute, have 18 months to demonstrate that their technological innovations can help industries , governments, nonprofits, and global society dealing with infection following a disease outbreak or spread event.
Researchers will follow a pioneering approach to solving complex engineering problems, collaborating on six demonstration projects based on their core expertise. Each project will be modeled on highly pathogenic avian influenza (HPAI), but lessons learned are expected to be transferable to other pathogens, including emerging diseases that have yet to be discovered. determined.
Team member Pejman Rohani, Professor of Regents at the Odum School and College of Veterinary Medicine in Infectious Diseases, said: “The highly pathogenic influenza is an ideal pathogen to model. “Like SARS-CoV-2, HPAI is a highly transmissible respiratory virus and it has a similar pathology. While our attention remains on COVID-19, a pandemic caused by the spread of HPAI bacteria remains a constant concern among epidemiologists and public health officials. . Much of what we’ve learned during COVID-19 — how people behave, the effectiveness of non-pharmaceutical interventions like mask wearing, vaccine hesitancy, and the biology of pathogen transmission — can be applied directly to HPAI. “
The demonstration projects will target different aspects and stages of spillover, outbreak, and control efforts. These include the development of artificial intelligence platforms that can predict how environmental interactions between humans and wildlife lead to the transmission of pathogens that cause infectious disease outbreaks, surveys to understand understand how different human populations are affected by prevention and vaccine acceptance announcements, determine the underlying cause of the processes that affect HPAI dynamics, and determine which HPAI viruses pandemic potential through molecular virology and immunology studies.
The individual demonstration projects are designed so that the output of each of these projects is connected to the others; The resulting information aggregation will be much more powerful than any project on its own.
Glen Nowak, co-director of Grady College’s Center for Health and Risk Communication, said the method had not previously been used in infectious disease modeling.
“As the COVID-19 pandemic began to spread across the globe and the United States, many organizations quickly launched surveys and polls to learn more about what people were thinking and doing. when wanting to reduce the spread of the virus and prevent serious illness,” he said. “Traditionally, very little of that information has been used to inform infectious disease models and forecasts, although human beliefs and behaviors greatly influence the severity and duration of disease. a pandemic. I am excited about this project because information can not only inform public health messages, but it can also help us identify beliefs and behaviors that should be prioritized in public health communication. copper. “
Drake and his colleagues must submit their research results by January 2024. Within the next two years, the National Science Foundation is expected to publish a call for proposals for Phase II funding to development of the Center for Pandemic Prediction and Prevention. A Center of this magnitude could position the University of Georgia as a global leader in Infectious Disease Intelligence research and forecasting.
Along with Drake, Rohani, and Nowak, the grant’s co-investigators are Justin Bahl of the UGA College of Veterinary and Public Health, Bogdan Epureanu of the Michigan Technological University, and Barbara Han of the Biosystems Research Institute. Thai Cary.
“I have worked extensively with all of these scientists, who have different professional backgrounds and experiences,” says Drake. “I am excited about the advances we will add to the evolving field of infectious disease intelligence.”
Source: University of Georgia
