IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics Mini Seminars
Sep 9, 2021
Welcome - The meeting will start at 3PM EDT
NOTE: THE MEETING WILL BE RECORDED, STREAMED AND PUBLICLY AVAILABLE�FOR THOSE MEMBERS UNABLE TO ATTEND
Agenda
People
Co-Lead: Reinhard Laubenbacher, PhD
Department of Medicine
Laboratory for Systems Medicine
University of Florida
reinhard.laubenbacher@medicine.ufl.edu
Co-Lead: James A. Glazier, PhD
Dept. of Intelligent Systems Engineering and Biocomplexity Institute
Indiana University, Bloomington
Web Administration, Slack: James P. Sluka, PhD
Dept. of Intelligent Systems Engineering and Biocomplexity Institute
Indiana University, Bloomington
Activities Coordination: Bruce G. Shapiro, PhD, PMP
Laboratory for Systems Medicine
University of Florida
bruce.shapiro@medicine.ufl.edu
Slack Channel
https://Msm-working-group.slack.com
Our IMAG/MSM Wiki page
https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics Feel free to suggest additional content!
Or, use the Tiny URL: https://tinyurl.com/hkr97vfe
IMAG’s LinkedIn
YouTube “MSM Working Group on Multiscale Modeling” https://www.youtube.com/channel/UCuDFvhgFziRRDcpRnT3vlrw
Announcements
�Any short (~1 minute) items such as;
Schedule for Upcoming Meetings and mini-Seminars
Sep 16:
Sep 23:
Sep 30:
Request for future speakers (Sept. 30, …)
Rules of the Meeting
Please mute your microphone and hold questions until after the presentations
Mini-Seminar�The Biomathematics Program at the US Army Research Office (ARO)
Virginia Pasour�ARO biomath program
Introduction to research at ARO as well as the specific goals of the Biomathematics Program and will welcome questions about opportunities related to the Working Group members’ interests.
Mini-Seminar�Super-spreading events initiated the exponential growth phase of COVID-19 with ℛ0 higher than initially estimated
Tomasz Lipniacki�Institute of Fundamental Technological Research, Poland
The basic reproduction number R0 of the coronavirus disease 2019 has been estimated to range between 2 and 4. Here, we used an SEIR model that properly accounts for the distribution of the latent period and, based on empirical estimates of the doubling time in the near-exponential phases of epidemic progression in China, Italy, Spain, France, UK, Germany, Switzerland and New York State, we estimated that R0 lies in the range 4.7–11.4. We explained this discrepancy by performing stochastic simulations of model dynamics in a population with a small proportion of super-spreaders. The simulations revealed two-phase dynamics, in which an initial phase of relatively slow epidemic progression diverts to a faster phase upon appearance of infectious super-spreaders. Early estimates obtained for this initial phase may suggest lower R0.
Requests for Input/Suggestions
We would like the subgroup leads to prepare brief presentations for the Thursday meetings, please let us know when you would like to present
Ideas/help for publicising our Thursday mini-seminars more effectively and for speakers to invite
Suggestions for agenda items and approaches to organizing the Steering Committee Meetings more effectively
There have also been a number of requests for more explicit statements of goals and tasks from the WG leadership, we would appreciate your suggestions
Please contact Reinhard Laubenbacher, James Glazier, James Sluka or Bruce Shapiro with your ideas on all of these issues
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Mini-Seminar�Optimizing predictive models to prioritize viral discovery�in zoonotic reservoirs
Daniel Becker�University of Oklahoma
Identifying and monitoring the wildlife reservoirs of novel zoonotic viruses remains logistically challenging and costly. Statistical models can be used to guide sampling prioritization, but predictions from any given model may be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of likely reservoir hosts. In the first quarter of 2020, we generated an ensemble of eight statistical models that predict host-virus associations and developed priority sampling recommendations for potential bat reservoirs. Over a year, we tracked the discovery of 40 new bat hosts of betacoronaviruses, validated initial predictions, and dynamically updated our analytic pipeline. We find that ecological trait-based models perform extremely well at predicting these novel hosts, whereas network methods consistently perform roughly as well or worse than expected at random. These findings illustrate the importance of ensembling as a buffer against variation in model quality and highlight the value of including host ecology in predictive models. Our revised models show improved performance and predict over 400 bat species globally that could be undetected hosts of betacoronaviruses. Although 20 species of rhinolophid bats are known to be the primary reservoir of SARS-like viruses, we find at least three-fourths of plausible betacoronavirus reservoirs in this bat genus might still be undetected. Our study is the first to show via systematic validation that machine learning models can help optimize wildlife sampling for undiscovered viruses and illustrates how such approaches are best implemented through a dynamic process of prediction, data collection, validation, and updating. Lastly, we discuss next steps to systematically integrate within-host data streams into future modeling efforts.
Mini-Seminar�Quantitative Modeling and Simulation to Drive Critical Decisions from Research through Clinical Trials
John Burke
CEO, President, and Co-founder, Applied BioMath
Quantitative Systems Pharmacology (QSP) is a mathematical modeling and engineering approach that aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms.
Several examples will be shown which highlight QSP efforts to accelerate the discovery and development of best-in-class therapeutics and impact critical decisions, in the continuum from preclinical exploration to clinical research
Have you made new research contacts or collaborations based on the Viral Pandemics working group?
Additional Business
We ask that everyone sign up for subgroups using the Google Form at
https://forms.gle/Vf6RtapTeXfXLBaq6
People are welcome to post tools and software to IMAG/MSM website, but be careful to be clear that a posting does not include endorsement by NIH
Please register on IMAG/MSM web site https://www.imagwiki.nibib.nih.gov/index.php/�(Details are on the next slide)
Charge to subgroups�(review):
Deliverable: White paper on the subgroup focus areas.�Due date: February 26, 2021
Steps to be taken:
Should be added to the subgroup’s Wiki page
IMAG/MSM Wiki Pages
The Viral Pandemics WG has an IMAG/MSM Wiki page at:�https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics
In addition, each subgroup can have their own WIki page.
IMAG/MSM Wiki Pages
We ask that:
To register for the MSM�(Multiscale Modeling Consortium):
“Multiscale Modeling and Viral Pandemics”
If you have any problems please contact JSluka@iu.edu
Current Subgroup Updates
Subgroup Roll Call and Feedback
Subgroup leads quick check in (subgroup list on next slides):
Subgroups 1 of 2�(28 total subgroups)
Leads Names
Physiological Models
[Innate and Adaptive Immune Response] J Shoemaker, R Datta, V Zarnitsyna, E Schwartz
[Host-pathogen Interactions] Y Liu, J Thakar, W Garira
[Tissue Damage and Recovery] Y Jiang, K Ye
Virus Models
[Viral Transport and Modes of Entry and Barrier Functions] MG Forest
[Viral Replication and Release] J Faeder, P Rangamani, EY Kim
[Viral Evolution] F Adler, A Zilman
Therapeutics and Medicine
[Drug Development] R Stratford
[Vaccine Development] K Ye, E Schwartz
[Modeling individual responses to disease and treatment] G An, E Schwartz, T Mapder
[Modelling Decontamination of Surfaces/Materials] K Kiradjiev
[Machine Learning for Health Monitoring] G Lin, Y Jiang
Individual Organ Systems
[Lungs] Y Jiang
[Heart],[Vasculature] C Lynch
[Kidney and Liver] M Rafailovich, C Mazza, C Mahapatra, C Yedjou
[Comorbidities] J Barhak, G Gonzalez-Parra
Subgroups 2 of 2
Data
[Experimental and Clinical Data for Model Construction and Validation] S Schnell
[AI-based Data Processing, Heterogeneous Data Fusion] O Gevaert, Y Kevrekidis
[Infection in experimental models including Relationship between in vivo � and in vitro responses and Infection in vivo model organisms] tbd
[Infection in zoonotic reservoir animals and Interspecies Transmission] G An, J Rice, T Mapder
[Coinfection and/or other pathogens] H. Dobrovolny
[Emerging and Reemerging Diseases] A Gumel
Modeling Technology
[Aerosol Transport in Lung, Lymph and Blood] M Tawhai, C Darquenne
[Integration] ** J Barhak, R Bowness, Y Liu, R Thompson
[Knowledge Acquisition and Modeling] SMR Naqvi, J Thakar
[Crowd-sourcing Models] R Laubenbacher, P Macklin
[Model Standards, Credibility, and Annotation] J Barhak, R Sheriff
�Social Issues
[Dissemination, training and outreach to the public, � research community and Liaisons] T Helikar, B Madamanchi, J Rice
[Health Equity] *** B Madamanchi
[Dissemination and Communication to funding agencies] J Glazier, R Laubenbacher
** Merged two groups – � [Integration Within and Across Scales and challenges]
[Integration Between Within-host and Population Scales]
*** Merged
Please Sign Up For Subgroups!
Subgroup Sign up
We ask that everyone sign up for subgroups using the Google Form at:
https://forms.gle/Vf6RtapTeXfXLBaq6
�The form allows you to join a group and volunteer to lead. If you think subgroups overlap, feel free to sign up for multiple groups. We will likely combine some of the groups based on the number of participants and the number of people common across related groups.
Discussion of Recruitment of Subgroup Leads, Subgroup Members and WG Members
Procedure for the establishment of new subgroups:
New subgroup proposals should include a brief description of the focus, at least one person who has agreed to lead the subgroup, and a rationale why the proposed subgroup focus is not covered by already existing subgroups.
Review of Web Site and Contents
https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics
We can add linked pages for each subgroup.