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Srinivasan Venkatramanan
Srinivasan Venkatramanan
Research Assistant Professor, Biocomplexity Institute, Univ. of Virginia
Verified email at virginia.edu - Homepage
Title
Cited by
Cited by
Year
Mathematical models for covid-19 pandemic: a comparative analysis
A Adiga, D Dubhashi, B Lewis, M Marathe, S Venkatramanan, A Vullikanti
Journal of the Indian Institute of Science 100 (4), 793-807, 2020
2122020
Commentary on Ferguson, et al.,“Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand”
S Eubank, I Eckstrand, B Lewis, S Venkatramanan, M Marathe, CL Barrett
Bulletin of mathematical biology 82, 1-7, 2020
2112020
Using data-driven agent-based models for forecasting emerging infectious diseases
S Venkatramanan, B Lewis, J Chen, D Higdon, A Vullikanti, M Marathe
Epidemics 22, 43-49, 2018
1962018
Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates and nonpharmaceutical intervention scenarios—United States, April–September 2021
RK Borchering
MMWR. Morbidity and Mortality Weekly Report 70, 2021
1552021
The united states covid-19 forecast hub dataset
EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ...
Scientific data 9 (1), 462, 2022
922022
Epidemiological and economic impact of COVID-19 in the US
J Chen, A Vullikanti, J Santos, S Venkatramanan, S Hoops, H Mortveit, ...
Scientific reports 11 (1), 20451, 2021
762021
Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints
S Venkatramanan, J Chen, A Fadikar, S Gupta, D Higdon, B Lewis, ...
PLoS computational biology 15 (9), e1007111, 2019
71*2019
Causalgnn: Causal-based graph neural networks for spatio-temporal epidemic forecasting
L Wang, A Adiga, J Chen, A Sadilek, S Venkatramanan, M Marathe
Proceedings of the AAAI conference on artificial intelligence 36 (11), 12191 …, 2022
662022
A framework for evaluating epidemic forecasts
FS Tabataba, P Chakraborty, N Ramakrishnan, S Venkatramanan, ...
BMC infectious diseases 17, 1-27, 2017
632017
Evaluating the impact of international airline suspensions on the early global spread of COVID-19
A Adiga, S Venkatramanan, J Schlitt, A Peddireddy, A Dickerman, A Bura, ...
Medrxiv, 2020
57*2020
Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness
J Chen, S Hoops, A Marathe, H Mortveit, B Lewis, S Venkatramanan, ...
MedRxiv, 2021.02. 04.21251012, 2021
562021
Forecasting influenza activity using machine-learned mobility map
S Venkatramanan, A Sadilek, A Fadikar, CL Barrett, M Biggerstaff, J Chen, ...
Nature communications 12 (1), 726, 2021
532021
Calibrating a stochastic, agent-based model using quantile-based emulation
A Fadikar, D Higdon, J Chen, B Lewis, S Venkatramanan, M Marathe
SIAM/ASA Journal on Uncertainty Quantification 6 (4), 1685-1706, 2018
522018
Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines
S Pollett, MA Johansson, NG Reich, D Brett-Major, SY Del Valle, ...
PLoS medicine 18 (10), e1003793, 2021
482021
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
K Sherratt, H Gruson, H Johnson, R Niehus, B Prasse, F Sandmann, ...
Elife 12, e81916, 2023
462023
Medical costs of keeping the US economy open during COVID-19
J Chen, A Vullikanti, S Hoops, H Mortveit, B Lewis, S Venkatramanan, ...
Scientific reports 10 (1), 18422, 2020
432020
Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination
S Truelove, CP Smith, M Qin, LC Mullany, RK Borchering, J Lessler, ...
Elife 11, e73584, 2022
402022
Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: A multi …
RK Borchering, LC Mullany, E Howerton, M Chinazzi, CP Smith, M Qin, ...
The Lancet Regional Health–Americas 17, 2023
282023
All models are useful: Bayesian ensembling for robust high resolution covid-19 forecasting
A Adiga, L Wang, B Hurt, A Peddireddy, P Porebski, S Venkatramanan, ...
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
282021
Using mobility data to understand and forecast covid19 dynamics
L Wang, X Ben, A Adiga, A Sadilek, A Tendulkar, S Venkatramanan, ...
MedRxiv, 2020
272020
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