Disease modelers mark Fogarty’s 50th anniversary
November / December 2018 | Volume 17, Number 6
Accomplishments of Fogarty
modeling programs
| Number of articles | 1,002 | 433 |
| Number of citations | 36,077 | 22,826 |
| Median citation count per article | 38 | 23 |
Fogarty’s staff recently reviewed the productivity of the
Research and Policy in Infectious Disease Dynamics
(RAPIDD) and Multinational Influenza Seasonal Mortality
Study (MISMS) programs.
Fogarty’s team of infectious disease modelers used the occasion of the Center’s 50th birthday to review its achievements, consider lessons learned, and explore possible future directions in an article published by the journal
Epidemics.
“Enhancing global capacity to study and interpret infectious disease surveillance data and develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic,” the authors suggested in the open-access paper.
Emerging infections and data from past pandemics provide new opportunities for validation of computational models, they said, while cutting-edge technologies and the “big data” revolution present innovative tools for studying outbreaks in real time.
For the past two decades, Fogarty’s
Division of International Epidemiology and Population Studies (DIEPS) has spearheaded two synergistic programs that identified and addressed critical gaps in infectious disease modeling research. To prepare for future influenza pandemics, the Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. Spurred by the bioterrorism events in 2001, the Research and Policy in Infectious Disease Dynamics (RAPIDD) program has
established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries.
Photo courtesy of Dr. Shweta Bansal
Fogarty’s Division of International Epidemiology and
Population Studies has spearheaded programs that
identified and addressed critical gaps in infectious disease
modeling research.
These activities have provided evidence-based recommendations for disease control during bioterror events and natural outbreaks, and coordinated global collaborative networks to advance the study of emerging disease threats. A worldwide community of researchers and policymakers has used computational tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts and inform control policies.
Knowledge of the mode of spread of a pathogen and the subpopulations at highest risk of transmitting the pathogen and experiencing severe disease can inform key decisions about social distancing and prioritization of therapeutics and vaccines, the authors said. Designing disease models rooted in empirical data, enhancing existing tools for data analysis, and teaching collaborators around the world how to apply these tools represent “highly cost-effective” ways to prepare for the next infectious disease outbreak, they said.
The increasing availability of large, electronic datasets, or “big data,” presents new opportunities for scientists to understand drivers of disease. Full-genome pathogen sequences, electronic health records, social media, satellite imagery and cellphone records provide highly granular information on transmission patterns, disease burden, human behavior and the environment.
Key accomplishments of MISMS include analyses that led to new national and regional vaccination strategies, improved understanding of children’s role in disease transmission, and insights into how viruses migrate long distances and evolve over time, according to the article. The program also has helped provide publicly available genome sequencing of flu virus collections, and worked to connect human and veterinary research communities studying virus transmission.
Meanwhile, RAPIDD’s work has been at the “forefront” of responding to the greatest infectious disease crises of recent years, the authors said, particularly the 2013-16 Ebola epidemic in West Africa and the Zika epidemic in the Americas. Modeling work helped to identify key routes of Ebola transmission and characterize the effectiveness of intervention policies. Also, RAPIDD collaborators have developed predictive maps of the spread of the Zika virus in the Americas, driven by environmental conditions and population mobility. Another RAPIDD study analyzed factors shaping the efficacy of screening air travelers for emerging pathogens, including Ebola and MERS-coronavirus. Careful literature surveys of prior modeling work, in addition to primary research done by RAPIDD, form a substantial body of “case law” for infectious disease modeling, the authors said, which can be used as reference to understand and model future outbreaks.
Together, the MISMS and RAPIDD programs have strengthened infectious disease modeling on a global scale, the authors said. “Most critically, these programs have been catalysts for other larger U.S. agencies and governments worldwide to expand support for infectious disease modeling research and to incorporate models into policy decision-making.”
MISMS was supported by the HHS Pandemic Threat Unit, Office of Global Affairs and Fogarty. RAPIDD received funding from the Department of Homeland Security and Fogarty.
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