Johns Hopkins APL modeling tool affirms critical role of testing in pandemic response
The COVID-19 pandemic highlighted how crucial testing is for disease preparedness and response, and new research from the Johns Hopkins Applied Physics Laboratory (APL) and a team of collaborators underscores that principle.
Published in the Jan. 2 edition of The Lancet Public Health, the research included simulation and analysis that suggests public-private partnerships to develop, produce and distribute COVID-19 diagnostic tests saved an estimated 1.4 million lives and prevented about 7 million patient hospitalizations in the United States during the pandemic.
APL, based in Laurel, Maryland, teamed with the Administration for Strategic Preparedness and Response (ASPR), the U.S. Centers for Disease Control and Prevention, and consultants from MITRE Corporation on the study.
“The analysis found that the early development, manufacturing and distribution of tests significantly reduced severe COVID-19 outcomes,” said Gary Lin, a computational epidemiologist at APL and a study co-author. “Through modeling and simulation, we’ve shown how national coordination can effectively leverage resources and capabilities.”
APL researchers developed a digital twin prototype — a virtual simulation environment — to model the testing and diagnostic supply chain. The tool was used to simulate baseline scenarios and assess the effects of potential pandemic interventions.
“The digital twin helps us quantitatively understand the impact and consequences of disruptions and changing infection levels on test availability,” said Elizabeth Currier, the APL digital twin project manager. “It can also evaluate the impact of policies and investments and be used in planning and evaluating supply needs, aiding in response and ensuring a secure supply chain for future medical crises.”
The prototype model integrated diverse data sources, including manufacturing, retail and government stockpile information as well as wastewater and inpatient data, which enabled the team to assess complex scenarios. It simulated forecasting for infectious disease cases to reflect demand for tests, production of tests, and supply and distribution logistics.
Between January 2020 and December 2022, government efforts produced more than 6.7 billion COVID-19 tests in the United States. These included laboratory tests, point-of-care tests and over-the-counter tests, with more than 2.7 billion tests performed in U.S. laboratories, in health care facilities or at home.
“The findings underscore the importance of robust and rapid test development, production and distribution to address future public health threats,” Currier said. “The insights gained from integrating data go beyond responding to COVID-19: They prepare us for future pandemics with a scalable framework to allocate resources effectively.”
APL’s digital twin modeling has since expanded to monitor nationwide testing for COVID-19, influenza, respiratory syncytial virus (RSV) and other public health threats under an all-hazards approach.
Journal
The Lancet Public Health
Method of Research
Computational simulation/modeling
Subject of Research
Not applicable
Article Title
The SARS-CoV-2 test scale-up in the USA: an analysis of the number of tests produced and used over time and their modelled impact on the COVID-19 pandemic
Article Publication Date
3-Jan-2025
From outbreak to vaccine: Artificial intelligence's contribution to pandemic preparedness
Peer-Reviewed Publicationimage:
A visual representation of Artificial Intelligence applications in pandemic response, highlighting key areas like epidemiological modelling, vaccine development, healthcare optimization and challenges & considerations.
view moreCredit: Praveen Kumar
A recent article published in Molecular Biomedicine by researchers at Datta Meghe Institute of Higher Education and Research explores the multifaceted role of Artificial Intelligence (AI) in pandemic preparedness and response. The team, comprising Dr. Praveen Kumar, undergraduate contributors Mayur Gawande, Nikita Zade and Induni Nayodhara Weerarathna, and faculty members Dr. Swapnil Gundewar and Dr. Prateek Verma, delves deeply into the applications, benefits, and challenges of AI technologies in global health crises.
The review provides a comprehensive assessment of AI's transformative potential, starting with its use in epidemiological modelling. AI-driven models, such as SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible), are highlighted as key tools for understanding and predicting disease transmission. These models have significantly improved outbreak forecasting, allowing policymakers to implement timely and effective interventions. By integrating large datasets from varied sources, AI optimizes resource allocation and enhances the efficiency of public health responses.
The article also investigates AI’s role in vaccine development, one of the most critical aspects of pandemic management. The authors detail how AI expedites the identification of vaccine candidates through molecular simulations and accelerates the design of clinical trials, reducing the time to market for life-saving vaccines. For instance, AI was instrumental in rapidly developing mRNA vaccines during the COVID-19 pandemic, showcasing its ability to tackle unprecedented challenges.
A significant strength of the review is its balanced analysis of the ethical, practical, and societal challenges accompanying AI applications in healthcare. Data privacy, algorithmic biases, and equitable access to AI-driven healthcare innovations are thoroughly discussed. The authors emphasize the need for responsible governance and robust ethical frameworks to ensure AI technologies are applied fairly and inclusively, particularly in resource-constrained settings.
In addition to its technical applications, the review explores AI's impact on real-time disease surveillance and monitoring. AI algorithms process data from diverse sources, including electronic health records, mobile applications, and social media platforms, to detect and track outbreaks early. These insights enable health authorities to act swiftly, potentially preventing the escalation of localized outbreaks into global pandemics.
The article also highlights the collaborative potential of AI. Researchers and public health officials can create integrated systems that enhance pandemic preparedness and response by combining expertise from multiple disciplines. The review underscores the importance of international cooperation, shared data infrastructures, and interdisciplinary research in realizing AI’s full potential for global health security.
Finally, the authors call for continued research to address the gaps and challenges in implementing AI technologies. The review stresses the importance of ethical AI deployment and its alignment with public health goals, advocating for its use to anticipate, mitigate, and ultimately overcome global health crises.
This comprehensive review is an essential resource for healthcare, technology, and policymaking stakeholders, providing a roadmap for leveraging AI to create resilient and adaptive health systems in the face of future pandemics.
See the article:
The Role of Artificial Intelligence in Pandemic Responses: From Epidemiological Modeling to Vaccine Development.
https://doi.org/10.1186/s43556-024-00238-3
Journal
Molecular Biomedicine
Article Title
The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development
Article Publication Date
3-Jan-2025
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| 1 MILLION DEAD FROM COVID UNDER TRUMP |
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