Using data-driven agent-based models for forecasting emerging infectious diseases
Open Access
- 1 March 2018
- journal article
- research article
- Published by Elsevier BV in Epidemics
- Vol. 22, 43-49
- https://doi.org/10.1016/j.epidem.2017.02.010
Abstract
No abstract availableKeywords
Funding Information
- National Science Foundation (CNS-1011769, 5U01GM070694)
- National Institutes of Health (CNS-1011769, 5U01GM070694)
This publication has 12 references indexed in Scilit:
- Ebola — Underscoring the Global Disparities in Health Care ResourcesNew England Journal of Medicine, 2014
- The Parable of Google Flu: Traps in Big Data AnalysisScience, 2014
- A Simulation Optimization Approach to Epidemic ForecastingPLOS ONE, 2013
- Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) PandemicPLOS ONE, 2011
- Computer Model Calibration Using High-Dimensional OutputJournal of the American Statistical Association, 2008
- Understanding the dynamics of Ebola epidemicsEpidemiology and Infection, 2006
- Modelling disease outbreaks in realistic urban social networksNature, 2004
- Bayesian Calibration of Computer ModelsJournal of the Royal Statistical Society Series B: Statistical Methodology, 2001
- Emerging Infectious Diseases of Wildlife-- Threats to Biodiversity and Human HealthScience, 2000
- A Simplex Method for Function MinimizationThe Computer Journal, 1965