Modeling Framework to Evaluate Vaccine Strategies against the COVID-19 Pandemic
Name
systems-09-00004.pdf
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2.95 MB
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Unknown
Checksum (MD5)
cfbd3fd8205eb82d78a006592d7a119d
Author(s)
Guttieres, Donovan G.
Sinskey, Anthony J
Springs, Stacy
Date Issued
January 13, 2021
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Systems 9 (1): 4 (2021)
Version
Final published version
Abstract
SARS-CoV-2, with an infection fatality rate between 0.5 and 1%, has spread to all corners of the globe and infected millions of people. While vaccination is essential to protect against the virus and halt community transmission, rapidly making and delivering safe and efficacious vaccines presents unique development, manufacturing, supply chain, delivery, and post-market surveillance challenges. Despite the large number of vaccines in or entering the clinic, it is unclear how many candidates will meet regulatory requirements and which vaccine strategy will most effectively lead to sustained, population-wide immunity. Interviews with experts from biopharmaceutical companies, regulatory and multilateral organizations, non-profit foundations, and academic research groups, complemented with extensive literature review, informed the development of a framework for understanding the factors leading to population-wide immunity against SARS-CoV-2, in particular considering the role of vaccines. This paper presents a systems-level modeling framework to guide the development of analytical tools aimed at informing time-critical decisions to make vaccines globally and equitably accessible. Such a framework can be used for scenario planning and evaluating tradeoffs across access strategies. It highlights the diverse and powerful ways in which data can be used to evaluate future risks and strategically allocate limited resources.
MIT Department
Massachusetts Institute of Technology. Center for Biomedical Innovation
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/systems9010004
