activity
20152021
most citedDynamic Bayesian Influenza Forecasting in the United States with Hierarchical Discrepancy

15 citations · 31 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CY2021

Impact of COVID-19 Policies and Misinformation on Social Unrest

Martha Barnard, Radhika Iyer, Sara Y. Del Valle +1

The novel coronavirus disease (COVID-19) pandemic has impacted every corner of earth, disrupting governments and leading to socioeconomic instability. This crisis has prompted ques…

cs.LG2020★ 4 cited

Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models

Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh +3

A crucial aspect of managing a public health crisis is to effectively balance prevention and mitigation strategies, while taking their socio-economic impact into account. In partic…

cs.LG2020★ 5 cited

Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates

Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer +3

Calibrating complex epidemiological models to observed data is a crucial step to provide both insights into the current disease dynamics, i.e.\ by estimating a reproductive number,…

stat.AP2020★ 4 cited

Time Series Methods and Ensemble Models to Nowcast Dengue at the State Level in Brazil

Katherine Kempfert, Kaitlyn Martinez, Amir Siraj +8

Predicting an infectious disease can help reduce its impact by advising public health interventions and personal preventive measures. Novel data streams, such as Internet and socia…

q-bio.PE2019★ 2 cited

Nowcasting Influenza Incidence with CDC Web Traffic Data: A Demonstration Using a Novel Data Set

Wendy K. Caldwell, Geoffrey Fairchild, Sara Y. Del Valle

Influenza epidemics result in a public health and economic burden around the globe. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1…

stat.AP2017★ 15 cited

Dynamic Bayesian Influenza Forecasting in the United States with Hierarchical Discrepancy

Dave Osthus, James Gattiker, Reid Priedhorsky +1

Timely and accurate forecasts of seasonal influenza would assist public health decision-makers in planning intervention strategies, efficiently allocating resources, and possibly s…