Focusing on Zoonotic Diseases

Jones: What are the key challenges when it comes to mitigating zoonotic threats?
Lauren Charles: In the United States, the most important challenge is the lack of disease surveillance for wildlife and domestic animals. There’s also a lack of coordinated response efforts—humans and animals are treated separately without a way to share medical data. There are very limited resources for wildlife, and they are often neglected despite their enormous role in emerging infectious diseases. There are some efforts in zoos for disease surveillance since the discovery of West Nile virus at the Bronx Zoo, as well as systems in place to identify foreign animal diseases in agricultural animals. But, by and large, zoonotic diseases are mainly identified after humans are infected and get sick.
Jones: What is biosurveillance? What role does it play in preventing outbreaks of zoonotic diseases?
Charles: Biosurveillance is defined as the process of gathering, integrating, analyzing, interpreting, and communicating essential information that might relate to disease activity and other threats to human, animal, or plant health. It can reveal where a disease is located, who is susceptible, and how it is spreading. When combined with disease forecasting, predictions can be made to determine when and where a disease outbreak may occur and how it will spread in the population. This can quickly provide information on the best way to disrupt the disease cycle and mitigate as well as prevent the disease.
Jones: Detecting and monitoring zoonotic diseases are an important piece of the mitigation puzzle. How does your research in biosurveillance and disease forecasting contribute to this?
Charles: Through a One Health lens, my data science research looks at the whole picture, using a mix of traditional sources—such as medical records and diagnostic reports—and nontraditional data sources like news reports, social media, socioeconomic data, animal populations, weather, and landscape. This gives us a deeper understanding of the biothreat event life cycle and helps us identify early warning signatures faster. It can also enable more effective forecasting, prevention, detection, and mitigation through advanced analytics, new tools, and better warning systems.

Jones: Why should we be concerned about the growing threat of zoonotic diseases?
Charles: Over the past 50 years, emerging infectious diseases have nearly quadrupled, and about 70% of those infect both humans and animals. These types of diseases, called zoonoses, have been the causal agent in all the pandemic outbreaks since the ’70s, including HIV, SARS, influenza H1N1, Ebola, MERS, and now COVID-19. There are many reasons for this—from increased movement of humans, animals, and animal products; to human population growth and expansion into wild areas; to changing climate and weather effects. For example, with the increase in temperature, wildfires, and drought, animals seek refuge in new areas, which means humans have a greater chance of being exposed to wildlife diseases.
Jones: What are the key challenges when it comes to mitigating zoonotic threats?
Charles: In the United States, the most important challenge is the lack of disease surveillance for wildlife and domestic animals. There’s also a lack of coordinated response efforts—humans and animals are treated separately without a way to share medical data. There are very limited resources for wildlife, and they are often neglected despite their enormous role in emerging infectious diseases. There are some efforts in zoos for disease surveillance since the discovery of West Nile virus at the Bronx Zoo, as well as systems in place to identify foreign animal diseases in agricultural animals. But, by and large, zoonotic diseases are mainly identified after humans are infected and get sick.
Jones: What is biosurveillance? What role does it play in preventing outbreaks of zoonotic diseases?
Charles: Biosurveillance is defined as the process of gathering, integrating, analyzing, interpreting, and communicating essential information that might relate to disease activity and other threats to human, animal, or plant health. It can reveal where a disease is located, who is susceptible, and how it is spreading. When combined with disease forecasting, predictions can be made to determine when and where a disease outbreak may occur and how it will spread in the population. This can quickly provide information on the best way to disrupt the disease cycle and mitigate as well as prevent the disease.
Jones: Detecting and monitoring zoonotic diseases are an important piece of the mitigation puzzle. How does your research in biosurveillance and disease forecasting contribute to this?
Charles: Through a One Health lens, my data science research looks at the whole picture, using a mix of traditional sources—such as medical records and diagnostic reports—and nontraditional data sources like news reports, social media, socioeconomic data, animal populations, weather, and landscape. This gives us a deeper understanding of the biothreat event life cycle and helps us identify early warning signatures faster. It can also enable more effective forecasting, prevention, detection, and mitigation through advanced analytics, new tools, and better warning systems.