Towards Epidemic Prediction: Federal Efforts and Opportunities in Outbreak Modeling [open pdf - 420KB]
"Infectious disease outbreaks threaten global health, economic vitality, and U.S. national security. Infectious disease emergencies prompting U.S. and international response efforts have involved previously unknown pathogens, such as Middle East Respiratory Syndrome Coronavirus and Severe Acute Respiratory Syndrome Coronavirus, as well as known pathogens causing outbreaks of unprecedented magnitude, such as Zika virus and Ebola virus. These and many other emerging or re‐emerging infectious diseases of humans are zoonotic--they originate, and may persist, in non‐human animal species. Other pathogens affecting only animals or plants, such as foot‐and‐mouth disease and sudden oak death, respectively, may threaten food security, trade, and ecosystems. A convergence of factors including globalized travel and trade, climate change, urbanization, and agricultural practices contributes to infectious disease outbreaks of humans, animals, and plants. In recent years, a new, interdisciplinary science has drawn on advances in pathogen biology, genomics, bioinformatics, and machine learning to develop computer‐based models to predict infectious disease outbreaks, or project their course. These computational tools increasingly support a range of decisions in outbreak preparedness and response, and were used extensively in recent outbreaks. U.S. public health preparedness strategies recognize the potential of these tools to improve outbreak preparedness and response, and many Federal agencies fund research and development programs in outbreak prediction and modeling. Drawing on this broad interagency experience, the Pandemic Prediction and Forecasting Science and Technology Working Group (PPFST WG), of the National Science and Technology Council, in this report identifies challenges in outbreak prediction and modeling and offers recommendations for Federal actions to advance the development and effective application of outbreak prediction capabilities."
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