2022 MIDAS Network Annual Meeting: registration is open!
July 28, 2022
MIDAS
MODELS OF INFECTIOUS DISEASE AGENT STUDY
MIDAS is a global network of scientists and practitioners who develop and use computational, statistical and mathematical models to improve the understanding of infectious disease dynamics. Through education, research, service, and sharing of ideas, the MIDAS network aims to advance science to improve global preparedness and response.
Training & Events
Dates: September 7-9, and September 23, 2022
Location: Bethesda, Maryland, USA, and online
MIDAS Network Visualization (Beta Release)
The MIDAS Network Visualization is a view of the MIDAS-related collaborations in graph form with two types of nodes: member nodes and institution nodes. Member nodes represent MIDAS members and edges link to collaborators on an infectious disease paper published by the member. Institution nodes represent institutions with members in the MIDAS network and edges link to all MIDAS members of the institution.
This is a beta release. Please explore the graph and send any comments/bugs/suggestions to questions@midasnetwork.us.
Membership
MIDAS membership is open to any infectious disease scientist, practitioner, or student who supports the mission and vision of the network. MIDAS is defined by broad inclusivity and diversity of its members, fostering collaboration to advance the science and application of infectious disease modeling. MIDAS members enjoy many advantages of being part of the network, free of charge.
MIDAS Members
Harel Dahari
Associate Professor
Loyola University Chicago
RaNashia Boone
Master’s Student
Fisk University
Angel Paternina-Caicedo
Professor
Universidad del Sinu
Daniel Larremore
Assistant Professor
University of Colorado Boulder
Qimin Huang
Lecturer
Case Western Reserve University
COVID-19 Researchers
Samuel Fernandes
Graduate Student
University of California Berkeley
Dan Han
Assistant Professor
University of Louisville
Xiaomeng Yuan
graduate student
University of Florida
Carlo Graziani
Computational Scientist
Argonne National Laboratory
Louis Shekhtman
Research Scientist
Northeastern University
MIDAS at a Glance
Our Vision and Mission
MIDAS is a global network of scientists and practitioners who develop and use computational, statistical and mathematical models to improve the understanding of infectious disease dynamics.
Membership
MIDAS network membership is open to any infectious disease scientist, practitioner, or student who supports our mission. The MIDAS network is defined by its broad member inclusivity.
Coodination Center
MIDAS creates educational, training, mentoring and career development opportunities in computational and statistical modeling, and is dedicated to train a broad community of scientists and practitioners.
Training
MIDAS creates educational, training, mentoring and career development opportunities in computational and statistical modeling, and is dedicated to train a broad community of scientists and practitioners.
Computing
HPC Services are funded by the NIH National Institute of General Medical Sciences (NIGMS) and are free of charge for MIDAS members from non-commercial organizations.
Students
MIDAS enables students to create professional relationships across the network, foster future collaborations, share educational resources, and provide a relaxed environment to share research and progress.
MIDAS Member Papers
Infectious Disease Papers
The importance of community during rapid development: The influence of social networks on acute gastrointestinal illness in rural Ecuador.
SSM – population health
Hegde ST, Trostle JA, Mukherjee B, Eisenberg JNS
2022-07-08
Intrinsic generation time of the SARS-CoV-2 Omicron variant: An observational study of household transmission.
The Lancet regional health. Europe
Manica M, De Bellis A, Guzzetta G, Mancuso P, Vicentini M, Venturelli F, Zerbini A, Bisaccia E, Litvinova M, Menegale F, Molina Grané C, Poletti P, Marziano V, Zardini A, d’Andrea V, Trentini F, Bella A, Riccardo F, Pezzotti P, Ajelli M, Giorgi Rossi P, Merler S,
2022-07-07
Effectiveness of CoronaVac and BNT162b2 COVID-19 mass vaccination in Colombia: A population-based cohort study.
Lancet Regional Health. Americas
Paternina-Caicedo A, Jit M, Alvis-Guzmán N, Fernández JC, Hernández J, Paz-Wilches JJ, Rojas-Suarez J, Dueñas-Castell C, Alvis-Zakzuk NJ, Smith AD, Hoz-Restrepo F
2022-07-07
Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care.
Annals of surgery
Loftus TJ, Ruppert MM, Ozrazgat-Baslanti T, Balch JA, Shickel B, Hu D, Efron PA, Tighe PJ, Hogan WR, Rashidi P, Upchurch GR Jr., Bihorac A
2022-07-06
MIDAS Member Projects
Test-based guideline to end isolation of patients
Midas Coordination Center Urgent Grant Program – Supplemental
People: Keisuke Ejima
2021 – 2021
Modelling University Responses to COVID-19
Midas Coordination Center Urgent Grant Program – Supplemental
People: Kyle Dahlin
2021 – 2021
Using climate & mobility data to model SARS-CoV-2
Midas Coordination Center Urgent Grant Program – Supplemental
People: Elizabeth Carlton
2021 – 2021
Data Mining & Transfer Learning for Modeling COVID
Midas Coordination Center Urgent Grant Program – Supplemental
People: Shi Chen
2021 – 2021
MIDAS Coordination Center
Follow @MIDAS_Network
I'm excited to announce that I'll be starting a lab @CUBoulder in the Department of Computer Science in fall 2023! Our aim is to use mathematical models to characterize the cross-species and cross-scale dynamics of respiratory pathogens.
Home
Welcome to the Kissler Lab
kisslerlab.github.io
First day at the new office @PublicHealthUGA! If you’re interested grad school or post-doc in disease modeling, stay tuned!
Thrilled to receive a @NIH/@NIAIDNews New Innovator (DP2) Award, which is a 5-year #NIHHighRisk grant that will support my research group to develop predictive models for public health departments to combat infectious diseases. I am thankful to so many! #IDtwitter #Epitwitter 🧵
L👀king for data scientist in San Francisco! https://bit.ly/3JbGgon
@NathanLo3579 https://profiles.ucsf.edu/nathan.lo
@IDDjobs @WBioinformatics @UCLAQCBio @KroganLab @rafalab @Bioinfo4women @dmaccannell @WOBionetworks @QIAGENBiox @SFBNJobs @BioinformaticsJ
Forward to amazing candidates
An exciting new opportunity to work with us in the mathematical modelling team at @ECDC_EU in Stockholm, Sweden. Informing infectious disease prevention and control policy in the EU. Apply now!
https://www.ecdc.europa.eu/sites/default/files/documents/VN-Expert-mathematical-modelling-2022.pdf
New preprint with @ZacharySusswein and @bansallab! Using 8+ million survey responses from Sept 2020 thru May 2021, we develop the first county-scale debiased spatiotemporal estimates of self-reported face mask-wearing in the US during the COVID-19 pandemic. (1/8) https://twitter.com/medrxivpreprint/status/1550506848226349067
Characterizing spatiotemporal trends in self-reported mask-wearing behavior in the United States https://medrxiv.org/cgi/content/short/2022.07.19.22277821v1 #medRxiv
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Thank you to NIGMS Grant U24GM132013 for supporting the work at the Coordination Center.
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